In March 2018, after a long digital drumroll of anticipation, Google announced that it was rolling out mobile-first indexing. What does this mean for your SEO? In short, if your ecommerce site isn’t optimised for mobile, you’re losing out on a huge source of traffic. Source: Google After much research into the way people are now interacting with search engines, the conclusion is that there has been a marked shift towards mobile. In typical Google fashion, what searchers want, searchers get. So, it was decided that mobile would be a top priority. But how dramatic has this turn towards mobile been? The answer is definitely substantial enough to warrant this new shift in Google’s priorities. According to this Statista report, in 2018, 52.2% of all web traffic comes through mobile channels. While that is indeed significant, it is not the most telling fact about the current state of mobile traffic. What is even more noteworthy is the steady pace with which this form of traffic is increasing. The same Statista study shows a rise from 50.3% the year before, which built on 35.1% in 2015. This is not a trend which is fly-by-night. As you already know, when it comes to eCommerce, the success of your business depends on keeping up with search engine best practices and ranking criteria. These best practices can help you boost your ecommerce search traffic. With this in mind, you simply cannot afford to ignore mobile-first. Before I tell you how to adopt this for your eCommerce store, it’s necessary to explore what mobile-first indexing entails. Let’s dive in. What is mobile-first indexing? In a nutshell, mobile-first indexing refers to a method of search engine ranking that makes use of the mobile version of websites to organize SERP items. Google looks for relevant data to decide how best to answer the questions their searchers are asking. If the army of crawling bots find relevant information on your site, you may be moved up the ranks. In the past, Google rankings were based on desktop versions of websites. With mobile-first, the move is towards crawling and indexing mobile sites, rather than their desktop companions. This means that websites must be responsive and suitable for use on mobile, or mobile versions must have the same comprehensive content as the desktop. If you are breaking into a cold sweat as the realisation dawns that all your SEO efforts have been concentrated on your desktop site, take a deep breath. As Google has said, the move is gradual, and will not happen without notification in the Search Console. If they deem your site ready for the move over to mobile-first indexing, you will receive the following notification: Source: Google It’s important to note at this point that the Mobile-first index is not a separate index. Google continues to only have one index, as it always has. The shift means that the mobile version of websites will be prioritised, rather than being a move towards an additional type of indexing system. But how can you optimise for this change? 3 key steps to mobile optimisation 1. Switch to one responsive website As Littledata recently outlined on this blog, moving to responsive web design can be a very good move. What is this responsive design I speak of? Quite simply, it refers to web design that works well across a range of platforms. It prioritises user experience to ensure that the person interacting with your site is able to navigate it with ease, regardless of which device they use. A major perk of this is that whomever is in charge of the upkeep of your store does not have to monitor two (or more) different versions of your site. They have one site to take care of which will, if intelligently-constructed, work for an optimal user experience. If you do prefer to keep things separate, make sure that you pay attention to the mobile version of your site, rather than it merely acting as a subsidiary of your desktop site. As we will look at in step 3, it’s not a given that your SEO efforts will migrate over to the mobile version without some cognisant intervention on your part. 2. Get speedy Hopefully, page loading speed has already been a major priority when it comes to your SEO efforts. Sales in the eCommerce sphere are highly dependent on being able to keep your shoppers engaged and open for conversion to a sale. If your page does not load quickly enough, your customers will not stick around. Note: Check out these case studies on HubSpot for examples of how the speed of your site can affect your profit margins. When it comes to mobile-first however, page load speed is even more integral to your success. It is most certainly a top priority for Google in terms of how they allocated their ranking positions, and should be for you too. Luckily, there are numerous methods to both test and increase your page load speed: Start by looking at what Google’s very own Search Console has to offer. Through their Webmaster Lab Tools, you’ll quickly be able to see how well your site is performing and whether you need to step up your game. Third party tools such as Think With Google can be excellent accompaniments to other Google Analytics tools when it comes to deciphering how your site is faring. Ensure that your web design is not slowing down your whole operation. If you don’t have the technical knowhow yourself, get a developer to run an audit to see if your server speed, content configuration, or baseline coding is placing any obstacles between your users and an instantly-loading page. 3. Ensure your SEO tactics are still powerful If you have spent a lot of time and energy ensuring that your desktop site is fully ”SEOd”, make sure that your efforts carry over into the mobile iteration of your eCommerce store. Here’s a very brief checklist: Is all that beautiful content you created crawlable in the mobile version of your site? Those titles and descriptions that you put so much effort into? Make sure all your metadata carries over! Is the mobile version of your site verified with Google’s Search Console? Some final tips As an eCommerce shop owner, your concerns are not only getting customers to your site, but ultimately converting them. When it comes to mobile, there are specific trends that CROs are highlighting when it comes to transforming your customers into paying ones. In this comprehensive analysis by Shopify, they take an in-depth look at a study done by inflow on Mobile Conversion Optimization Features used in Best-In-Class Retailers. What is particularly useful in this report is what they refer to as a don’t and a do in terms of what is currently leading to optimal conversion rates for eCommerce business owners. As a parting gift, I’d like to share these two insights with you as ways to bolster your own efforts. In summary: Say no to hero slider images. In-depth research into mobile conversion rates has illustrated that customers are less than moved by them. Usher in the age of the top navigation menu. A relatively unused feature in the eCommerce world, all the data is pointing towards its efficacy in terms of mobile conversion rates. The takeway... Point 1: Don’t panic. Google will notify you if they’re switching you over, and will prioritise sites they deem more ready. Point 2: Start thinking with an on-the-go mindset. Make sure your store’s UX for mobile is as streamlined as possible. Make sure that your SEO efforts have carried over. Point 3: Don’t stop at optimising your mobile site for traffic - optimise for conversions too. Understand what will compel mobile customers to a sale. Good luck!   This is a guest post by Charlie Carpenter. He is the co-founder and CEO of Kite. He is a mobile advocate with over ten years of industry experience. After working for large and small agencies for many years, he co-founded Kite; a software solution for print-on-demand, zero inventory merchandise, and personalised photo print goods. As well as an entrepreneur, Charlie is a seasoned product strategist with experience of various types of digital projects which include: Responsive and Adaptive Websites, Mobile & Tablet Apps, Hybrid Apps, Cross Platform App development. You can connect with Charlie on LinkedIn, and follow him on Twitter.

The holiday shopping period has us obsessed with one of our favourite ecommerce metrics: average order value (AOV). How does your site compare? A new infographic breaks down the stats. Increasing average order value usually has a dramatic impact on profits and ROI from marketing spend. It is also a gift that keeps on giving, as optimisation in this area is something that can deliver ongoing results over the long term. What does ‘average’ look like? Well, that’s going to depend on your sector, as well as the level of optimisation maturity reached by your peers. There’s not much point comparing the AOV of a small jewellery site with a large travel website. It doesn’t tell you anything meaningful. It’s more interesting to deep dive into your niche, and the good news is that we have some sector-specific ecommerce benchmarks to share with you, based on data from the 12,000+ ecommerce websites that have connected to the Littledata app. Below is a visualisation to show you some of our numbers (there's much more to explore within the app). Compare your own performance To see your own data alongside the industry averages, simply hook up your Google Analytics account with Littledata, and the app will show you how you’re performing relative to your peers (it’s free to connect). The app will also show you benchmarks for the other key ecommerce metrics, alongside AOV. No doubt you’re also interested in things like conversion rate, checkout completion rate, product list CTR, and so on. Are you benchmarking your ecommerce site in the best sector to help you increase revenue? We use the IBM Watson API and some smart logic to categorise websites automatically, though you’re able to manually override that should you need to do so. For example, you can compare against similar sized SEO-driven websites in your location, or look specifically at retailers in your vertical (eg. health and beauty products by subscription). Underperforming? We’ve got your back... There’s no need for panic if your numbers don’t look as good as your peers, as the Littledata app will recommend specific optimisation ideas via our new Missions feature. You can launch missions to improve your ecommerce performance and increase sales. I'd love to know what you've done to increase average order value. Do leave a comment below if you have tips to share. PS. Feel free to share this infographic, or include it in your own blog posts, as long as you include a link back to this post and our main website (www.littledata.io).

In two high-profile data breaches this year – at Ticketmaster and British Airways – over half a million credit cards were stolen via a compromised script inserted on the payment pages. Google Tag Manager is a powerful tool which enables you to insert any script you want onto pages of your website, but that power can used against you by hackers if you're not careful – and below we’ll look at how to stop GTM being a security risk on your payment pages. Firstly, how did the hackers get the card details from these sites? And how is it relevant to GTM on your site? Security firm RiskIQ has traced the breach to a compromised Javascript file which skimmed the card details from the payment form. So when a user entered their credit card number and security code on BritishAirways.com (or their mobile app) those details were posted to a third party server, unknown to British Airways or the customer. This is a high-scale equivalent of placing a skimming devices on an ATM, which reads one card at a time. In Ticketmaster’s hack the script was one loaded from a chatbot vendor on their site, Inbenta. Inbenta claims not even to have been aware the script was used on payment pages. The changes to the script were subtle: not breaking any functionality, and in BA’s case using a domain ‘baway.com’ which looked somewhat authentic. To protect your site against a similar attack you obviously need to lock down accounts used by your developers to change scripts in the page source code, but you also need to secure GTM – which can be used to deploy such scripts. We have a few rules at Littledata to help reduce risks in using tag management on payment pages: 1. Use pixels over custom JavaScript tags on payment pages You probably need a few standard tags, such as Google Analytics, on payment pages but try to avoid any custom scripts which could possibly skim card details. Many non-standard tags use JavaScript only to create the URL of a tracking pixel – and it is much safer (and faster) to call the tracking pixel directly. Contact the vendor to find out how. (Littledata's Shopify app even removes the need to have any script on the payment pages, by hooking into the order as it's registered on Shopify's servers) 2. Avoid loading external JavaScript files in GTM Many vendors want you to load a file from their server (e.g. myvendor.com/tracking.js) from GTM, so they can update the tracking code whenever they want. This is flexible for them, but risky for you. If the vendor gets hacked (e.g. with Inbenta above) then you get compromised. It’s less risky to embed that script directly in GTM, and control version changes from there (although a fraction slower to load the page). Of particular risk is embedding a tag manager within a tag manager – where you are giving the third party rights to publish any other scripts within the one tag. Don’t do that! 3. Lock down Edit and Publish rights on GTM Your organisation probably has a high turnover of contract web developers and agencies, so have you checked that only the current staff or agencies have permission to edit and publish? It's OK to have external editors use 'workspaces' for version control in GTM, but ideally someone with direct accountability to your company should check and Publish. 4. Blacklist custom JavaScript tag on the payment pages You can set a blacklist from the on-page data layer to prevent certain types of tags being deployed on the payment pages. If you have a GTM container with many users, this may be more practical that step 3. 5. Remove tags from old vendors There are many thousands of marketing tools out there, and your company has probably tried a few. Do you remove all the tags from vendors when you stop working with them? These are most at risk of being hacked. At Littledata we run a quarterly process for marketing stakeholders opt-in tags they still need for tracking or optimisation. 6. Ensure all custom JavaScript tags are reviewed by a developer before publishing It can be hard to review minimised JavaScript libraries, but worth it for payment pages if you can’t follow rules 1 and 2. If you’re still worried, you can audit the actual network requests sent from payment pages. For example, in Chrome developer tools, in the 'Network' tab, you can inspect what requests sent out by the browser and to what servers. It’s easy for malicious code to hide in the patchwork of JavaScript that powers most modern web experiences, but what is harder to hide is the network requests made from the browser to external servers (i.e. to post the stolen card information out). This request to Google Analytics is fine, but if the domain of a request is dubious, look it up or ask around the team. Good luck, and keep safe with GTM!

Over the past few months we’ve been working on a new feature for Littledata users. Our new Missions feature is a data-driven recommendation engine for ecommerce optimisation. The Missions concept is simple, yet powerful. First, you connect Google Analytics in order to see how your site is performing relative to the benchmarks in your sector. Then, if you are underperforming in any given area, the app will suggest some specific optimisation missions. Now, you might think that in 2018 the vast majority of ecommerce websites are serious conversion machines, but that’s simply not the case. Most websites remain woefully under-optimised and are leaving way too much money on the table. Checkouts are abandoned, users bounce before pages load, forms are left uncompleted, and so on. This is becoming a big problem, given the competitive landscape in many sectors. Acquiring new customers is increasingly expensive. A surefire way to make your marketing budget go further is to optimise your website, but where should you start? This is precisely where Missions comes into play: you launch individual missions and work your way through the suggested tasks to improve ecommerce performance, metric by metric. Missions: website optimisation made simple We’ve spent a lot of time researching optimisation techniques that have been shown to work for other companies. That’s not to say that they’ll definitely work for you, but proven ideas are usually well worth testing. We now have hundreds of actionable ideas, which have been clustered together into launchable ‘missions’. Missions are aligned to key ecommerce goals, such as increasing average order value, product list CTR, add to cart rate, checkout completion rate and conversion rate. Individual missions cover areas such as persuasion, merchandising, user experience, copywriting, pricing, CTAs, findability and trust. And since Littledata is good at measuring the little data, you’ll be able to see the results of your efforts within the app. Who should use Missions? Missions is for anybody that wants to optimise a website. It can be used by large digital organisations, SMBs and micro businesses. It is particularly useful for agencies with multiple clients, especially where there are recurring optimisation tasks over multiple websites. The ideas in each mission include guidance on who should be involved in implementation. Roles include ecommerce manager, web developer, copywriter, marketing strategist, and UX designer. How to launch a mission Start by connecting Google Analytics, so we can help you measure success and prove ROI. Once connected we’ll run a quick check to make sure your analytics setup is in good shape (the app will suggest fixes, if anything is awry). You can then compare your performance against your peers, to identify areas that are ripe for improvement. We’ll show you this at the top of your dashboard: By drilling down into each of the above categories you’ll be able to see the detail. As an example, let’s look at the main metrics in the ecommerce category. You’ll see your own data alongside ecommerce benchmarks from your sector (based on data from more than 12,000 websites). This makes it easy to compare and contrast performance. It looks like this: In the above example you can see that ‘add to cart rate’ and ‘conversion rate’ are both considerably lower than the norm. Both of these areas are ripe for improvement. Another metric in the ecommerce category is average order value. For this particular sector the average is $28, and while this particular website is doing reasonably well, it isn’t yet a top performer. Increasing AOV is one of the quickest ways of growing revenue, so we can launch the following mission: So, this first mission - ‘Average order value fundamentals’ - will help you to incrementally increase AOV. It includes ideas in areas such as product bundling, cross-sells, up-sells, wishlists, pricing strategies, personalisation, social proof, and so on. Here’s what the mission looks like - note that each tip can be expanded to reveal more information: You can work your way through the mission and implement (or skip) the ideas. Press the ‘mark as complete’ button to start tracking performance. Once you have done that we will start monitoring performance: Reach your goals, faster Missions should generate considerable - and provable - ROI for the SMBs, corporates and agencies that use it. Work your way through the missions to improve the customer experience, and remove the friction from the buying process. The first iteration of Missions is natural next step for Littledata. Our long-term goal is to develop Missions into an AI-driven optimisation engine for ecommerce teams. We hope you’ll join us for the ride. People trust Littledata to audit, fix and automate reporting. They also use our benchmarks to check and compare their performance, relative to their peers. And now, with Missions, digital teams can set about actively increasing ecommerce revenue. We hope that Littledata Missions will help you to fast-track your goals and KPIs. Give Missions a try today and shoot for the moon.

Paying attention to the right ecommerce metrics can help you establish the best customer base and shopping experience for long-term growth. But many retailers still focus only on the most popular metrics -- especially during the online shopping craze of Black Friday and Cyber Monday (#BFCM). Over the next few weeks ecommerce managers will be obsessing over data, but which stats are the most important? Two popular metrics -- ecommerce conversion rate and average time on site -- may be misleading, so I recommend looking instead at longer-term benchmarks. Here's how it all breaks down. Littledata's ecommerce benchmark data now contains indicators from over 12,000 sites, making it an ideal place to get a realistic view of Black Friday stats. Last year we found that the impact on Black Friday and Cyber Monday was larger in 2017 than in 2016. Using that same data set of 440 high-traffic sites, I dove into the numbers to see how this affected other metrics. Metrics to avoid I think that overall ecommerce conversion rate is a bad metric to track. From the leading ecommerce websites we surveyed, the median increase was 30% during the BFCM event last year...but nearly a third of the stores saw their conversion rate dip as the extra traffic didn’t purchase, with this group seeing a median 26% drop. Some stores do extremely well with deals: four sites from our survey had more than a 15-fold increase in ecommerce conversion rate during BFCM, and nearly a quarter saw more than double the conversion rate over the period. But the real question is: will tracking conversion rate hour-by-hour help you improve it? What could you possibly change within in day? Another misleading metric is average time on site. You may be looking for signs that the the extra traffic on the holiday weekend is engaging, but this is not the one to watch. The time on site for visitors who only see one page will be zero, which will mask any real increase from engaged visitors. Where to focus instead Now, do you know what good performance on funnel conversion metrics would look like for your sector? If not, have a look at Littledata’s industry benchmarks which now cover over 500 global sectors. Littledata’s benchmarks also include historic charts to show you how metrics such as add-to-cart rate vary for the average retailer in your sector month by month. Next try the ‘speed’ performance page to see how fast a user would expect a site in your sector to be. If you see site speed (as measured in Google Analytics) drop below average during Black Friday trading it’s time to pick up the phone to your web host or web operations team. Then, are you tracking return on adverting spend for extra Facebook Ads you're running during the quarter? Ad costs will spike during the peak trading period, and you make not be getting the same volume of traffic conversion into sales. Here are some quick pointers. Facebook Ads. Littledata’s Facebook Ads connection will ensure accurate data, with a dedicated Facebook report pack for automated insights. Shopify. If you're running your site on the Shopify platform, read up on which metrics are most important for Shopify stores and check out Shopify's BFCM Toolbox for seasonal online marketing. Missions. Use Missions in the Littledata app to make permanent improvements to your user experience. BFCM may be over before you can make the changes, but customers will keep buying the rest of the year. For example, can you increase add-to-cart rate with tips such as highlighting faster selling items or recommending an alternative to out-of-stock products? So focus on some clearer metrics and I hope Black Friday brings you every success!

We recently flagged up 15 proven techniques to help you increase average order value, which is one of the fastest ways of growing ecommerce revenue. Many of Littledata's customers use the Shopify platform, so I thought I'd take a look in the app store to see what's available to help implement some of these techniques. I found dozens of great apps that can be used to quickly test some of our ideas. In doing so you might just increase conversion rates and other key metrics too. Below are 15 of the best ones - click on the screenshots to check them out in more detail. Many of these apps are paid-for, though normally offer free trials, and in any case the monthly cost is low. You should make back your investment and then some. I've focused on the apps that have high review scores. By installing these apps and launching Littledata's optimisation missions you'll be able to quickly improve ecommerce performance. Do let us know how you get on! CartHook CartHook's app allows you to create a customisable one-page checkout, which helps to simplify the user experience and can improve conversion rates. It also allows you to upsell, by showing customers relevant products after they have completed their initial purchase. CartHook also provides you with the option of showing customers a final thank you page. You can also use the app to build custom funnels for each product. Neat. Littledata integrates seamlessly with CartHook's one page checkout so you can track every part of the ecommerce sales flow. Enquire This app allows you to show customers post-purchase surveys, to help gain valuable insight into what made them buy. You can ask customers all kinds of questions. The default is 'How did you hear about us?', but other questions can help you profile your customers, to gather feedback, testimonials, reviews, or to segment email lists. Use the survey data to refine your marketing efforts, in order to attract the right kind of buyers. Plus, I've heard through the grapevine that a Littledata - Enquire integration is coming soon. Stay tuned! Cross Sell As you might have already gathered, this is a comprehensive cross-selling app. Persuading customers to add more products to their cart is a proven way of increasing average order value. With Cross Sell, you simply hand-pick the products you want to attempt to cross-sell with each item. It comes with the “Smart Cart” feature which recommends cross-sells based on the last product that the user added to their cart. The app will also cover you when the ones you select are out of stock, by showing default products. Upsell Bundled Products Here's another app that does what it says on the tin. Use it to create product bundles. Bundling reduces cognitive load and can be incredibly persuasive, especially when discounts are on offer. This app allows you to package up related products so that customers can buy them with one click. You can create unlimited bundles with the same product, to test different ideas. Discounts can be applied as a set price or a percentage (we advise that you do both, but definitely the former). Countdown Cart This is a widely used countdown app, which has been very well rated. It lets you choose from a wide range of themes to suit your store. The app is free, lightweight and installs very quickly. Features include a classic countdown timer, which puts pressure on the shopper to purchase before the clock hits zero. It also makes use of real-time social proof by show shoppers how many people are viewing items, and how many times something has been sold. This can increase the motivation to buy. Enforcing principles of scarcity can lead to an uplift in conversion rates and AOV. Discounted Pricing You can generate more sales by offering discounted pricing at different thresholds. This app allows you to offer shoppers volume discounts, which is a proven technique to increase order values. Show shoppers how bulk buying becomes more cost efficient, and they might just add more items to their cart to qualify for the bigger discounts. The app allows these discount tables to be visible on all devices, and is quick to set up. AfterShip Returns Center Reduce friction between your shoppers and your store by allowing free returns. This helps to encourage higher spending by creating a ‘risk-free’ purchase experience. With the app, customers are able to submit return requests in a few clicks. The best thing is that you don't necessarily need to lose the spend, as you have the option of adding credits to a customer's account (as well as issuing a refund back to their bank account). Wishlist Plus Wishlist Plus allows users to add products to a wishlist without needing to be logged in. It also syncs wishlists across devices. These features help to remove purchase barriers, and when checking out a shopper may be tempted to add products that are sitting in their wishlist, which will increase order value. The app has gained a 4.9 rating on the Shopify App store, and the reviews reference the "excellent customer service" provided by the developers. Rewardify Rewardify allows you to add credit to your customer’s account when they complete certain tasks such as meeting a minimum spend, selecting a specific shipping option or buying certain items. All great ways to increase AOV. Gift Cards, Loyalty & Rewards You can use this app to offer deals such as a free $10 gift card with the purchase of a $100 gift card, or selling $100 cards for $85. Show these kinds of offers to the right people at the right time and you might just increase AOV. The app also allows you to send gift cards to other people, and to use store credit as an upsell tool. Product Reviews Product Reviews is a simple app that provides a platform for social proof - a key psychological phenomenon to keep in mind when trying to increase AOV. It sends review scores to Google to enhance your listings, and you can also determine which reviews to show and hide. Gift Wrap Plus Many shoppers are happy to pay a few extra pounds to have their products gift-wrapped before they arrive. Installing this app allows you to offer that option, and it is one which can definitely increase your AOV. The app allows for extras such as gift messages, and lets you see your best performing gift-wrap styles. Ultimate Sales Boost Here's another app that focused on urgency and scarcity to boost conversion rates and average order value. It has plenty of features to help you improve merchandising, calls to action, and highlight social proof, such as low stock warnings and 'recently sold' alerts. The app is easy to use and configure, which helps to explain its 4.9 star rating. Smart Shipping Bar Use this to promote shipping offers via a bar at the top of the page, which updates as items are added to the cart. It will show customers when they qualify for free shipping. This is excellent for any store that offers free shipping when a minimum order amount has been reached, such as $50. And that's a proven way to increase AOV. Littledata Before optimising your store you must make sure that you have accurate data, in order to measure the results. We've found that almost nine out of ten Shopify stores have a broken analytics setup, so the chances are that you'll need to make some tweaks. https://www.youtube.com/watch?v=hE4nzZycVLE#action=share The Littledata Shopify app fixes your tracking automatically. It also provides benchmarks against over 12,000 ecommerce sites, so you can compare your own performance vs your peers, and includes a suite of AI-based reporting. What should you do with all that data? Littledata's new Missions feature recommends specific ideas to help you improve the crucial ecommerce metrics such as AOV, add to cart rate, product list CTR, checkout completion, and conversion rates. Missions provide step-by-step instructions for proven ways to optimise sales and conversions. Work your way through the missions and get ahead of the pack!

Today PwC's retail survey found the British high street is being reshaped as shoppers shift online - especially in fashion, where a net 100 high street stores closed. This misses the positive side of the story: all those shoppers are buying from independent UK brands online instead, which is one of the fastest growing area of the UK economy. We looked at 30 mid-sized online fashion retailers (with average sales of £1m per month) who get a majority of their traffic from the UK. This collection had grown their sales by an aggregate 21% from October 2017 to October 2018 (year on year). Fashion shoppers love to browse unique designs on Instagram and Pinterest, compare prices and get easy home deliveries. Independent ecommerce brands are bringing original designs to the British wardrobe, and we should celebrate their success.   Behind the research Littledata gathers benchmark data from Google Analytics on over 12,000 websites, including many types of ecommerce businesses. Our customers get insights into their performance and recommendations on how to improve online conversion.

With 3.8 million apps available for Android users and 2 million apps in Apple's App Store, it can be tough for an app developer to stand out among the competition. But with Google's Universal App Campaigns (UAC), developers have an opportunity to market their mobile apps with targeting options based on audience demographics and behavior. It all happens automatically -- as long as you set up the campaigns correctly. In this post I take a look at how you can put machine learning to work for you, using the power of Google’s Universal App Campaigns. Campaign set up Getting started with a UAC is relatively easy. The three steps are to identify an audience, ensure conversion tracking is set up correctly, and relevant text, video, and images are available for the campaign. The two major actions for UACs are to find new users who will install the app or those who will perform an action inside the app, such as making an additional purchase. One the UAC is set-up, it is eligible to show on Search, Display, YouTube and the Play Store. The initial setup is straightforward. The advertiser only needs to provide four lines of text with images and with machine learning, Google decides which combination to show to a particular user. Goals When you consider goals for your UAC, the install action is an obvious one regardless of the app category. Targeting options includes people who are likely to install the app or who are likely to install it and perform in app action. It is up to the advertiser to determine what a valuable action looks like and ensure conversion tracking is set up before launching a campaign. In-app actions, or goals, or can be either success actions or proxy actions. With a success action, the app user makes a purchase inside the app, upgrades the service, or signs up for a paid subscription; something that generates revenue. Assuming success actions happen at least ten times a day with users, the system has enough data to identify and target the right audience for your UAC. If volume of success actions is low, there is not enough data for machine learning to make decisions. In that case, the advertiser can identify a proxy action which is a behavior that is likely to lead to success action. An example of this is someone who added payment information to upgrade service but did not follow through with upgrading. Or it could be tracking which of your users share incentives with their network. Advertisers need to think carefully about what a proxy action truly is. When it it is too early in the funnel, it includes people who are less likely to convert and not a good representation of those who will later perform a success action. If a mid funnel behavior is identified as a proxy action, rather the the top of the funnel, it may better represent people who are closer to converting so it is more likely to later result in a success action. Conversions Setting up and collecting conversion data is a crucial piece to success because these campaigns look at past searches, browsing behavior, and other apps used to determine who is most likely to convert. Before launching a UAC, ensure this conversion tracking is set up correctly or your will not be measuring goals that matter. For e-commerce sites, the primary conversion is clearly to drive revenue in the form of an in-app purchase or perhaps subscriptions. With luxury retail, it is especially important to have conversion recording correctly because of the multiple touch points. And Shopify users can use the Littledata reporting app to gain even more insight on the user journey through that platform. Measurement and optimization There are immediate metrics to monitor - app installs and in-app purchase - but there are also long term considerations such as the customer lifetime value (CLV), that should be part of your overall strategic marketing plan. A single user who makes a purchase provides direct revenue. If they refer someone to your app, that is considered indirect revenue. The first number is clear-cut revenue and easy to measure. The second is one that you determine based on your internal data, meaning what type of behavior and interaction with customers generally leads to a sale. The value of both of these actions contribute to the CLV. Lifetime is the length of time they interact with your app. If they install the app and use it to buy things over the course of a year, then stop, their CLV time period is one year. Once you have identified your CLV, use this value to set your target CPA and optimize it based on performance. Decide what you are willing to pay for a success action and what you will pay for a proxy action, knowing that number will likely change over time. As data comes in from your UAC, you can compare the lifetime value of your different customers through segments. Segments help you uncover those customers who purchase every couple months compared to those who only make an initial purchase. Those the make multiple purchases represent segments with a higher value. Drilling into data with segments allows you to see who gives you the best return for your investment. This level of detail helps you identify how much you paid in your UAC for to acquire each type of customer so you can adjust accordingly. Review what you paid initially for the type of users that you bring in and compare that to their lifetime value. Are you investing your budget in a UAC that brings in users that generate recurring revenue? When you bid strategically based on a lifetime value, you are not overly focused on short-term transactions. It is less expensive to keep a customer than to acquire a new one so you want to think in those terms. What next? Decide on UAC goals that make sense for the purpose of your app. What should users do in addition to downloading the app and what behaviors indicate they are getting close to a conversion? Gather assets - text, video, and image - that are enticing for users and ensure conversion tracking is setup properly. Without proper conversion tracking, you miss out on the data you need to determine success. Monitor performance of your campaigns, and if you run an ecommerce site, track a wealth of data with the Littledata app. Think about the CLV and optimize your campaigns to reach the right users rather than any users. Your bottom line is generating revenue so keep that in mind with every UAC. With careful planning and well managed campaigns, your app can stand out in a crowded marketplace.

Average order value (AOV) is a bona fide north star metric for Shopify stores, and ecommerce companies more broadly. Increasing AOV is a priority goal for ecommerce teams as it directly boosts revenue (and profits, if you’re doing things right). Growing revenue often requires retailers to acquire more traffic, but with AOV you can increase sales simply by convincing shoppers to spend that little bit more. AOV can be improved by adopting a number of proven optimisation techniques. Many of these have their roots in offline retail, where price, promotion, placement and merchandising all play a part in persuading customers to buy additional - or more expensive - items. We’ll get onto these tactics soon enough, but for now let’s start at the beginning. What is average order value? AOV is the average amount spent by customers when they place an order. To calculate AOV you divide total sales by the total number of orders (typically over a certain period of time). You can monitor AOV via Google Analytics. If you’re using Littledata then you’ll see it on your dashboard and in ecommerce report packs. Why is average order value important? AOV is one of the primary KPIs in ecommerce. It is a measure of sales trends and reflects customer behaviour and buying preferences. This insight can be used to optimise your website, pricing strategy, and guide decisions on what you choose to sell. It is also a good indicator of your ability to optimise ROI, as your marketing budget will go that much further if you increase AOV. It is worth investing time and money into moving the AOV needle, as it will create universal uplift. Implement the right kind of tactics - and technology - and we are sure that you will see some positive results, especially if this is an activity you haven’t yet spent too much time on. The results? New and existing customers are likely to spend more with you whenever they buy. Better sales numbers, bigger profits, and various additional benefits. Just like the other ecommerce KPIs, it is best not to view AOV in isolation. Related metrics include customer lifetime value (CLV) and customer acquisition cost (CAC), particularly for ecommerce subscription businesses. How do I know if my average order value is in good shape? Littledata has robust benchmarking data from a sample of 12,000 ecommerce sites. You can drill down by category and revenue to see how you compare vs your peers. For example, we analysed AOV across 379 medium-sized ecommerce sites in September and found that $123 is the typical amount spent. But average is relative - it very much depends on the sector. Start a free Littledata trial to see your AOV alongside the benchmark for your sector (we will show you some other juicy metrics and benchmarks too). It will look like this: Pretty cool, huh? If you happen to be underperforming in any area then our app will suggest some proven optimisation ideas to help you improve your store. Other stores have used our ecommerce benchmarks to grow sales, and we're confident that you will experience similar results. What affects average order value? Lots of things influence how much people spend when they buy from your site. Consider the last time you bought a higher priced item, such as a TV, laptop or mobile phone. More often than not there are upsells and cross-sells as you progress down the purchase path. You end up buying related items (mobile phone cases), upgrading your initial choice (256MB memory vs 64MB), purchasing add-ons (extended warranty), or clicking on a compelling product bundle (phone + case + warranty = 15% off). This kind of buying behaviour helps ecommerce teams to sleep soundly at night. It is to be encouraged. A real world example Apple is an absolute master of maximising AOV. Let’s take a quick walkthrough of one of its purchase pathways. First, we’ll select a Macbook Pro and will then see the following page, which invites us to customise our order. Add a little more memory and one item of software, and the order value increases by about 30%. Boom. Now let’s click the ‘Add to Bag’ button. We’ll progress to an ‘Essentials’ page. Yet more ideas to help us spend extra money. Think we’re all done? Not so fast. Click on ‘Review Bag’ and you’ll enter the checkout. Note the ‘Related Products’ that appear underneath the basket summary. Is it any wonder that Apple is valued at more than one trillion dollars? How can I increase my average order value? The million dollar question (or maybe a few billions, in the case of Apple). The researchers for our newest product feature - called Missions - have discovered plenty of ideas for you to try out. Littledata Missions provide step-by-step guides to help ecommerce teams optimise performance, and AOV was one of the very first metrics we wanted to explore. The following ideas are taken from our Average Order Value Fundamentals mission. There are a bunch of others in there to try too. Missions automatically generate based on your ecommerce benchmark data in the Littledata app (try Missions for free today). I’ll wager that at least one of the following will help you to grow AOV. And a super combo might seriously move the dial. Once you’ve optimised AOV - and there might be a ceiling - you can work on increasing purchase frequency, customer referrals, and then scale up your customer acquisition efforts. So then, here are 12 ideas to help you start to grow average order value... 1. Provide free shipping for orders above a certain amount Betterware grew AOV by 20% after introducing free shipping for orders above £30. M&S also provides free standard delivery for orders that exceed £30, as seen in the screenshot. A study by UPS found that 58% of consumers would add extra items to their cart in order to qualify for free delivery. As such this is a great way of increasing average order value. Free delivery is an expectation these days, so if you're late to the party - and concerned about margins - then a minimum threshold is worth testing. 2. Offer minimum spend discounts Much like introducing a free shipping threshold, you can provide a discount if the customer spends a certain amount on your site. Although it might seem to go against the goal of increasing average order value, setting offers such as this can tempt visitors into spending whatever is necessary to achieve the discount, because it appears like a deal. There are a number of ecommerce plugins to help with this. A lot of happy Shopify stores use the Product Discount app. 3. Make the most of up-selling Up-selling is the art of convincing prospective customers to increase their spend, typically by buying a more expensive item to the thing they're looking at. For example, in the screenshot below we can see how Amazon shows higher priced TVs to the one initially selected. By listing out the features side by side it may be enough to convince the prospective buyer that the next model up is a more attractive option. This is a sure-fire way to increase average order value, though it's not without its risks as you'll need to change the shopper's mind about something ("You don't really want that, you want this."). So be careful when experimenting with up-selling techniques. 4. Embrace cross-selling Amazon has attributed around 35% of its revenue to cross-selling. Not exactly small change. As such it is crucial to find a cross-selling strategy that works for your website. Cross-selling is the science of persuading customers to buy additional products related to the thing they’re about to purchase. For example, buy a camera and you might see recommendations for camera cases, bigger memory cards, battery chargers, etc. Adding items to the basket in this way is highly likely to increase average order value. However, it is important to specify which customers receive cross-sell offers. You should certainly think twice before cross-sells to customers who regularly return items. 5. Allow customers to use live chat A Forrester study found that there is a 10% increase in order value from customers who used the live chat function. The study also discovered that live chat helps to increase revenue by 48% per chat hour, and increased conversion rate by 40%. The business case for live chat would appear to be strong. Why is this? Mainly because customers like the immediacy - and familiarity - of chat. It has been reported that 73% of consumers who have used live chat were pleased with the experience. So, live chat is good for AOV, sales, conversion rates and customer satisfaction. What's not to like? 6. Show how others have enjoyed the product Average order value is 6% higher among shoppers who read reviews, compared with those who don't bother, according to a Bazaarvoice study. Positive social proof is incredibly powerful. It goes a long way towards encouraging people to progress to the checkout. Social proof comes in many forms, from reviews and ratings to testimonials and buyer videos. Make it highly visible at key points in the buyer journey, to build trust and reinforce the decision to buy. 7. Offer financing for high-ticket items Analysis by Divido has shown that sales can increase by 40% when high-ticket items are offered in monthly instalments. Your most expensive items are the ones which can be heavily responsible for driving up your average order value. If you offer customers the option to pay in instalments it can help you sell more of these higher valued products. For example, Goldsmiths offers shoppers 0% interest-free credit on purchases which total more than £750. This may appeal to people looking at items in the £500+ range - they might end up being tempted to spend more once they see the financing available. 8. Offer volume-based discounts Office supplies company Paperstone generated a 19% average order increase when a bulk discount deal was offered. As well as helping to grow AOV, strategic discounting can be great for clearing out excess inventory. However, remember that it is important to calculate bulk discounts very carefully. You need to offer deals that attract customers, but which do not hurt your profit margins. 9. Use dynamic retargeting to increase average order value Stella & Dot increased AOV by 17% after experimenting with dynamic retargeting, which allows ecommerce firms to show shoppers the right kind of ads during the shopping journey (such as product recommendation ads, based on their browsing behaviour or purchase history). This technology also recaptures lost sales from visitors who leave websites, by showing them personalised offers to re-engage them. 10. Send personalised emails OneSpot found that average order value increased by 5% upon the personalisation of emails. Simply put, customers are more likely to feel valued by your site if you provide them with messages that are relevant to their specific interests. Personalisation often starts at the customer's name ('Dear sir' won't cut it), but extends to the content of the email. If this is based on prior browsing and purchase history then you're more likely to engage the shopper, to reinforce - or complete - the purchase. 11. Offer a gift card or loyalty scheme By offering customers rewards for shopping with you, you’re likely to see an increase in orders, as well as an increase in the size of those orders. It has been shown that offering rewards for purchases 15-20% above average order size can increase the amount people are willing to spend. Encouraging big spenders to buy more frequently will also have the effect of increasing AOV. A study by BigDoor found that loyal customers make up 70% of total sales in some cases, so it is important to give something back to those customers once in a while. 12. Create product packages A case study into BaubleBar, a jewellery site, showed that average order value increased significantly when product bundling was offered. One pair of its earrings costs $30, but a bundle of three is just $48. This bundle screams “deal” to a customer. BaubleBar saw its average order increase by $22 in a matter of days. Bundling reduces cognitive load. If you can help shoppers avoid thinking too much then you're onto a good thing. Bundles can be viewed by visitors as a valuable deal, especially if they contain products which supplement the one they are already interested in. Packaging up items this way can be incredibly persuasive, particularly when you're offering a discounted price. They can also save the shopper time - no need to browse for add ons. Start the AOV mission today In summary, trying to increase average order value is worth the effort, and will be a gift that keeps on giving once you move the dial in the right direction. You can launch the Average Order Value mission directly from your Littledata dashboard. Our app will track your progress as you test ideas to discover what works best for your site. People trust Littledata to audit, fix and automate reporting. They use our benchmarks to check and compare their performance, relative to their peers. And now, with Missions, digital teams can actively set about increasing ecommerce revenue.

Ecommerce conference season is upon us. In the past few weeks, the Littledata team was at Shop.org in Las Vegas, Paris Retail Week, and the Google Expert Summit in Waterloo, Canada -- three very different events in three rather different countries. Then we also hit up Agile Cambridge and Technology for Marketing in the UK, the UPRISE fest in Dublin, TechDay LA in sunny Los Angeles and the BigCommerce partner summit in Austin. And while we unfortunately couldn't make ReCharge's Recur event for the subscription industry, or Hawke Media's Hawkefest, the ultimate anti-conference, many of our partners and merchants were there and had awesome things to say. But wait a second. Slow down! With so many exciting events to potentially attend during what is already one of the busiest times of year for those of us in the industry (Black Friday is just around the corner from a marketer's perspective), how do you choose? Is that conference you've been debating attending really worth it? If we've learned anything... Over the years I've had a mixed experience with conferences. But with Littledata we've found a good rhythm. Of course it helps that we're on the cutting edge of new technology, actually using AI and machine learning as opposed to just talking about it, and that we already have major customers around the world, even though we're technically still a 'startup'. This gives us a wide range of high-quality speaking and learning opportunities. But at the same time our productive conference experiences haven't happened by accident, whether for ecommerce or general tech events. We've found such a good conference rhythm -- a dance that produces a consistently high ROI on in-person events -- by looking closely at our own data on a quarterly and yearly basis. Our strategy is always evolving, but some stats have been consistent. For example, we discovered that at the right events: Though we don't necessarily have a higher win rate for enterprise leads from conferences, the sales cycle is condensed, on average 3x faster from meeting to close. This saves our sales team valuable time chasing down leads, and also helps us improve our product, pitches and processes at a faster rate. Agencies we meet in person are 4x more likely to refer us a customer within the next 30 days -- even if we never did a formal product demo. What's your company's take on conferences? Here are a few insights that might help you get more out of the conference experience, whether that means big tech industry events or smaller, focused meetups. There is no such thing as a must-attend conference The great irony with ecommerce conferences is that they tend to be scheduled at what are already busy times for those of us in the industry. Whether it's the shows we attended these past 6 weeks that overlapped with everyone getting back to work after summer holidays, or European standbys like NetComm Suisse's later fall events and One to One in Monaco every March, right after SXSW in Austin, it's either an embarrassment of riches or -- depending on your perspective -- a really confusing hodge podge of hard-to-classify opportunities. There are simply too many choices, and it's especially hard to decide whether to attend a tech conference or meetup if your company has never attended that particular show before. One thing I love about our industry is that merchants (stores and ecommerce managers) and vendors (apps, platforms, consultants, designers and agencies) are all in the same boat. In short, we have no time for BS. We want events that focus on real information, emerging technologies and human connection. So how do you decide? First things first, make your own list. There are a ton of blog posts out there about 'must attend' conferences, those 'not to miss'. Give me a break! Every business is unique, and you're only as viable as your buyer personas. So make a list of conferences, events and meetups that might help connect you with your prime customers and best partners. Brainstorm, look online, ask around. Make your own list and plan to review every quarter. Then once you've made that list, on paper or Trello or however you work best, go through the following checklist with as many members of your team as possible, especially if you can bring in decision makers from both Product and Marketing. A simple checklist When deciding if you should attend a conference for the first or second time, it's useful to have a checklist for quick, consistent analysis. The checklist I use is deceptively simple. It has only 5 indicators. Would one significant sale pay for itself in terms of customer acquisition cost (CAC)? If the conference did work out, is it something you would attend every year? Would it be the right place for you to speak, either now or in the future? Is this your scene, your community? Are there companies, merchants, agencies, vendors etc. attending whom you wouldn't see any other time this year? (Even just one counts, if sufficiently high-value.) In short, if you can tick all five boxes then you should attend the conference. If you can only tick four, it's probably worth attending but needs more debate. If this is the case, then considering point number one in detail -- looking at your current LTV/CAC ratio and considering how the conference could help improve or at least maintain it -- is essential. For ecommerce tech companies like our own, this generally means one big sale or partnership. For ecommerce sites it can also take the form of discovering new tech (like Littledata, Klickly or ReCharge) that will help increase sales and marketing ROI. If you can tick all five boxes then you should definitely attend the conference The checklist works even if you've already attended the conference in the past. Just consider point two already covered and proven! If you're in the ecommerce space, definitely consider platform-specific conferences. Shopify and Magento have regular events and meetups around the world, and word on the street is that BigCommerce will be really ramping up their local partner events in 2019. Shopify Unite has consistently been that rare conference that ticks all the boxes for us here at Littledata, but that doesn't mean we're ignoring others that only tick four. We've cast our net wide (using the checklist of course) and are still seeing results. If you want to get a head start on conference browsing for next year,  Veeqo has created a calendar of best worldwide ecommerce conferences for 2019. Across the board remember this: success at a conference almost never comes in the form of expected outcomes. Yes, the best outcomes will be aligned with your sales and marketing goals, but sometime the biggest benefits will not be clear for 3, 6 or even 12 months down the line. That's why we do quarterly and yearly reviews of all in-person activities, from networking events to large conferences. I suggest you do the same. Most importantly, have fun! Gone are the days of boring trade shows. Show up. Make connections. And if we're there too, come say hi! Maybe nobody can make analytics sexy, but we at least promise to make them useful. And usefulness is a good place to start...

When Littledata first started working with benchmark data we found the biggest barrier to accuracy was self-reporting on industry sectors. Here’s how we built a better feature to categorise customer websites. Google Analytics has offered benchmarks for many years, but with limited usefulness since the industry sector field for the website is often inaccurate. The problem is that GA is typically set up by a developer or agency without knowledge or care about the company’s line of business - or understanding of what that industry sector is used for. To fix this problem Littledata needed a way to categorise websites which didn’t rely on our users selecting from a drop-down list. Google Analytics has offered benchmarks for many years, but with limited usefulness since the industry sector field for the website is often inaccurate. The first iteration: IBM Watson NLP and a basic taxonomy Our first iteration of this feature used a pre-trained model as part of IBM Watson’s set of natural language APIs. It was simple: we sent the URL, and back came a category according to the Internet Advertising Bureau taxonomy. After running this across thousands of websites we quickly realised the limitations: It failed with non-English websites It failed when website homepage was heavy with images rather than text It failed when the website was rendered via Javascript Since our customer base is growing most strongly outside the UK, with graphical product lists on their homepage, and using the latest Javascript frameworks (such as React), the failure rate was above 50% and rising. So we prioritised a second iteration. The second iteration: Extraction, translation and public APIs The success criteria was that the second iteration could categorise 8 sites which the first iteration failed with, and should go on to be 80% accurate. We also wanted to use mainly public APIs, to avoid maintaining code libraries, so we broke the detection process into 3 steps: Extracting meaningful text from the website Translating that text into English Categorising the English text to an IAB category and subcategory The Watson API seemed to perform well when given sufficient formatted text, at minimal cost per use, so we kept this for step 3. For step 2, the obvious choice was Google Translate API. The magic of this API is that it can detect the language of origin (with a minimum of ~4 words) and then provide the English translation. That left us focussing the development time on step 1 - extracting meaningful text. Initially we looked for a public API, and found the Aylien article extraction API. However, after testing it out on our sample sites, it suffered from the same flaws as the IBM Watson processing: unable to handle highly graphical sites, or those with Javascript rendering. To give us more control of the text extraction, we then opted to use a PhantomJS browser on our server. Phantom provides a standard function to extract the HTML and text from the rendered page, but at the expense of being somewhat memory intensive. Putting the first few thousand characters of the website text into translation and then categorisation produced better results, but still suffered from false positives - for example if the text contained legal-ease about data privacy it got categorised as technical or legal. We then looked at categorising the page title and meta description, which any SEO-savvy site would stuff with industry language. The problem here is that the text can be short, and mainly filled with brand names. After struggling for a day we hit upon the magic formula: categorising both the page title and the page body text, and looking for consistent categorisation across the two. By using two text sources from the same page we more than doubled the accuracy, and it worked for all but one of our ‘difficult’ websites. This hold-out site - joone.fr - has almost no mention of its main product (diapers, or nappies), which makes it uniquely hard to categorise. So to put it all the new steps together, here’s how it works for our long-term enterprise client MADE.com's French-language site. Step 1: Render the page in PhantomJS and extract the page title and description Step 2: Extract the page body text, remove any cookie policy and format Step 3: Translate both text strings in Google Translate Step 4: Compare the categorisations of the title vs page body text Step 5: If the two sources match, store the category I’m pleased that a few weeks after launching the new website classifier we have found it to be 95% accurate. Benchmarking is a core part of our feature set, informing everything that we do here at Littledata. From Shopify store benchmarks to general web performance data, the improved accuracy and deeper industry sector data is helping our customers get actionable insights to improve their ecommerce performance. If you’re interested in using our categorisation API, please contact us for a pilot. And note that Littledata is also recruiting developers, so if you like solving these kind of challenges, think about coming to join us!

Physical or digital? We found merchants doubling down on both at Paris Retail Week. At the big event in Paris last month, we found retailers intent on merging the online and offline shopping experience in exciting new ways. See who we met and what the future of digital might hold for global ecommerce. Representatives from our European team had a great time at the big ecommerce event, one of the 'sectors' at Paris Retail Week. Outside of the event, it was great to have a chance to catch up with Maukau, our newest Shopify agency partner in France. (Bonjour!) Among the huge amount of digital sales and marketing trends we observed throughout the week, a few emerged again and again: mobile-first, phygital experience, and always-on, multi-channel marketing. Getting phygital Phygital? Is that a typo? Hardly. It’s the latest trend in ecommerce, and it was prevalent everywhere at Paris Retail Week. Phygital combines “physical” and “digital” experiences in a new ecosystem. This offers the consumer a full acquisition experience across different channels. From payment providers to marketing agencies, everyone was talking about going phygital. One of our favourite presentations was by AB Tasty. They focused on how optimising client experience can boost sales and conversions in the long-term. It’s not enough to promote your products, nor to link to an influencer for social proof -- you need to create a full customer experience. Starbucks and Nespresso are good examples of how this works offline, assuring that a customer who comes in to drink a coffee will linger around for the next 20-30 minutes. By keeping the customers in the shop, they will eventually order more. The goal is to reproduce this immediately sticky experience online too, and focusing on web engagement benchmarks is the best way to track your progress here. Using the example of conversion rate optimisation (CRO) for mobile apps, AB Tasty's Alexis Dugard highlighted how doing data-driven analysis of UI performance, on a very detailed level, can help clarify how mobile shopping connects with a wider brand experience. In the end, customer experience means knowing the customer. 81% of consumers are willing to pay more for an optimal customer experience. Brands that are reluctant to invest in customer experience, either online or offline, will hurt their bottom line, even if this isn't immediately apparent. Those brands that do invest in multi-channel customer experience are investing in long-term growth fuelled by higher Average Order Value (AOV). 81% of consumers are willing to pay more for an optimal customer experience -- the statistic speaks for itself! Another great talk was from Guillaume Cavaroc, a Facebook Academie representative, who discussed how mobile shopping now overlaps with offline shopping. He looked at experiments with how to track customers across their journeys, with mobile login as a focal point. In the Google Retail Reboot presentation, Loïc De Saint Andrieu, Cyril Grira and Salime Nassur pointed out the importance of data in retail. For ecommerce sites using the full Google stack, Google data represents the DNA of the companies and Google Cloud Platform is the motor of all the services, making multi-channel data more useful than ever in assisting with smart targeting and customer acquisition. The Google team also stated that online shopping experiences that don’t have enough data will turn to dust, unable to scale, and that in the future every website will become, in one way or another, a mobile app. In some ways, "phygital" really means mobile-first. This message that rang out clearly in France, which is a mobile-first country where a customer's first encounter with your brand or product is inevitably via mobile -- whether through a browser, specific app or social media feed. Multi-channel experience (and the data you need to optimise it) Physical marketing is making a comeback. Boxed CEO Chieh Huang and PebblePost founder Lewis Gersh presented the success of using online data for offline engagement, which then converts directly back on the original ecommerce site. Experimenting heavily in this area, they've seen personalised notes on invoices and Programmatic Direct Mail (with the notes based on viewed content) generate an increase of 28% in online conversion rate. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard, to name just a bit of the physical collateral that's becoming popular again -- and being done at a higher quality than in the years of generic direct mail. Our real-world mailboxes have become an uncluttered space, and customers crave the feel of a paperback catalogue or simple postcard. However, data is still the backbone of retail. In 2017 Amazon spent approximately $16 billion (USD) on data analysis, and it was worth every penny, generating around $177 billion in revenue. Analysing declarative and customer behaviour data on the shopper’s path-to-purchase is a must for merchants to compete with Amazon. Creating an omni-channel experience for the user should be your goal. This means an integrated and cohesive customer shopping experience, no matter how or where a customer reaches out. Even if you can't yet support an omni-channel customer experience, you should double down on multi-channel ecommerce. When Littledata's customers have questions about the difference, we refer them to Aaron Orendorff's clear explanation of omni-channel versus multi-channel over on the Shopify Plus blog: Omni-channel ecommerce...unifies sales and marketing to create a single commerce experience across your brand. Multi-channel ecommerce...while less integrated, allows customers to purchase natively wherever they prefer to browse and shop. Definitions aside, the goal is to reduce friction in the shopping experience. In other words, you should use anonymous data to optimise ad spend and product marketing. For marketers, this means going beyond pretty dashboards to look at more sophisticated attribution models. We've definitely seen this trend with Littledata's most successful enterprise customers. Ecommerce directors are now using comparative attribution models more than ever before, along with AI-based tools for deeper marketing insights, like understanding the real ROI on their Facebook Ads. The new seasonality So where do we go from here? In the world of ecommerce, seasonality no longer means just the fashion trends of spring, summer, autumn and winter. Online events like Black Friday and Cyber Monday (#BFCM) define offline shopping trends as well, and your marketing must match. "Black Friday" saw 125% more searches in 2017, and "Back to School" searches were up 100%. And it isn't just about the short game. Our own research last year found that Black Friday discounting is actually linked to next-season purchasing. Phygital or otherwise, are you ready to optimise your multi-channel marketing? If not, you're missing out on a ton of potential revenue -- and shoppers will move on to the next best thing.

Your website is an essential tool for attracting and converting customers. Driven by the uptake in online shopping, having a well-designed ecommerce site is no longer a luxury. It’s now a necessity -- you need to regularly convert browsers into buyers. Web design has the power to really grab your customers attention and portray your messaging. But when it goes wrong, the customers you lose will rarely come back. In this post I take a look at common web design fails that drive customers away, so you can avoid them. They may be common mistakes, but they're often overlooked! Fail #1: The CMS, plugins and theme are outdated You don’t need to modernize your website every day, or even every week, but you do need to make sure it doesn’t feel outdated. That means you should regularly update your website theme, your plugins and your content. Updating your theme and plugins will ensure you have the latest features and boost your security, while regularly updating your content will improve your SEO ranking and make your website more interesting for repeat visitors. Fail #2: Your website is not mobile responsive Over 50% of online traffic is from mobile phones and tablets, so having a website that properly displays itself on those devices is essential. If your website is non-responsive, you’ll be missing out on a massive amount of potential business. Below is the website Dribble, a powerful example of a responsive website (here's a big list of mobile-responsibe web design done well). Plus, your SEO will suffer and it makes your business look unprofessional. Common issues with non-responsive websites are text being displayed too small to read, irregular formatting, un-clickable links and images not loading. How many of your customers are shopping on mobile? Where are they falling out of the checkout funnel? Use this tool to find out. Fail #3: Stock photos and generic content Building customer loyalty and trust -- both of which are vital for repeat business -- begins with establishing credibility and authenticity. Nobody wants to read the same blog they have already read 50 times on your website, or look at stock photos they have seen on other brands websites. Good writing should be original, punchy and relevant to your target audience. And copy should be matched with credible, original imagery. Stock photos are easy to spot a mile off. Using original imagery significantly helps to build a website design that stands out and wins customer trust. Fail #4: It’s slow and your bounce rate is high Speed matters. If your website loads too slowly, you can say goodbye to the impatient modern-day consumer and watch your bounce rates rise. First impressions of a website are made immediately, so if your website takes more than a few seconds to load, your content and design won’t be given the chance to see the light of day. Make sure your images are compressed, limit the amount of videos and animations published within, make sure your hosting provider can handle fluctuating amounts of traffic, and disable any plugins you aren’t actually using. Then make sure to check your speed and performance rates against other sites. Benchmarking is the most accurate way to do this, so you can see how you compare to similar sites in your industry. Fail #5: Your site is unbranded and doesn’t stand out The minute a possible customer comes to your website, they should know exactly whose website they are on. Having a nicely designed logo is, therefore, critical for making a good first impression and improving brand awareness. And best of all, it’s really easy to do. Online tools are readily available to create stunning high-resolution logos in second, such as Shopify’s logo maker. Fail #6: Face it, your site's just not that interesting There is nothing worse than going on to a website and finding it incredibly boring. Content needs to compliment design, so it’s vital you have interesting content throughout to keep your customers engaged and coming back for more. Using banners, photos and graphics, along with authentic and interesting copy is the right way to grab your customers’ attention and encourage them to make a purchase or opt-in via a form. Fail #7: It’s not made for converting If your website doesn’t have clear calls to action (CTAs), then it’s not going to have good conversion rates. Plain and simple. This 'fail' can easily be eradicated by using smart opt-in offers, having clear navigation menus ('nav menus' in designer jargon), and writing relevant, targeted content. Evernote use an excellent CTA.   Without a clear CTA, how are your customers meant to know what you want them to do? Simply put, they won’t - they will leave. Every page (including your blog posts) should have a clear CTA to guide your online visitors down the buyer journey. Fail #8: It’s not optimized for SEO Optimizing each aspect of your website begins with understanding what works well and what doesn’t. The only way of doing this accurately is by using analytics to get deeper insights into how your potential buyers are using your site. You’ll be able to see which pages perform well, which keywords attract the best traffic (SEO is an area that you should be continually optimizing), which promotions work best, and which images resonate with your customers the most. As search engines become smarter, continually optimizing for SEO is an excellent way to get a clearer view of what's working and clarify anything that isn't clear. Then you'll be on the road to becoming an SEO-driven business - an easy way to improve revenue. Fail #9: It’s cluttered and noisy If your website is too cluttered, it will create a bad customer experience for any visitor. It will also distract potential buyers away from doing what you want them to do, such as making a purchase, filling out a form or requesting more information via chat. Don’t make the mistake of cramming too much into each page, or filling your web pages with in-your-face advertising. Your website should be easy to navigate, simple and concise. Customers should be able to convert with minimal effort. Conclusion The bottom line: if your ecommerce site has many design fails that impact the user experience, your company may lose out on potential profits. Use the tactics mentioned in this article to get started on improving the design of your website today!   Michelle Deery is the content writer for Heroic Search, a digital marketing agency based in Tulsa. She specializes in writing about eCommerce and loves writing persuasive copy that both sells and educates readers.

Littledata launched benchmarks for websites two years ago. They quickly became a key feature of our app, and as customers became more engaged, so did ideas for how to improve our benchmarking and the algorithms that learn from those benchmarks. In response to customer feedback and deeper research into industry sectors, we've made some really exciting improvements over the last few months to make the comparisons even more useful -- and even more dynamic. The changes are five-fold. Detailed sectors and sub-sectors. Almost every customer we talked to said the benchmark comparison was most useful if it was for very similar sites. Previously we only had 50 high-level sectors to compare with; now we have hundreds of low-level sectors. You can visualise the full range. Smarter auto-categorisation of your website. Our machine learning process now has a 95% chance of finding the best sector for your website, meaning you can compare against the most useful benchmark without filling in a single form! Ability to manually change industry sector. And of course, if you're in that 5% that needs human input, then you (or your Enterprise account manager) can pick a better sector in the general app settings page. You might also want to change sectors just to see how you compare. No problem. Benchmarks for technology stacks. Want to see if you are making the most of a technology such as Shopify or Yieldify? Now you can compare with other sites using the same technology, making our ecommerce benchmarking even more powerful for agencies and web developers. Benchmarks for starter websites. Previously we only generated benchmarks for sites with at least 500 monthly visits. We dropped that to 200 monthly visits, so starter websites can see a comparison - and see more detail as they grow. We've launched a live visualisation of how our AI-based website categorizer is mapping a range of industry sectors. It offers a full overview of website categories and segments. And you can drill down to see more details. For example, we've seen a big rise in wine, coffee and health shake retailers this year, many of whom are using our ReCharge integration to get insight into their subscription business models. As our algorithms learn about ecommerce businesses selling beverages of many varieties and automatically categorises sites accordingly, you can now look closely at a particular segment to see how your site compares. Littledata is an Agile company. We're constantly iterating, and continuously improving the benchmarks to make them more actionable, so please give us feedback if you'd like to see more. Happy benchmarking!

For the past decade Facebook’s revenue growth has been relentless, driven by a switch from TV advertising and online banners to a platform seen as more targetable and measurable. When it comes to Facebook Ads, marketers are drawn to messaging about a strong return on investment. But are you measuring that return correctly? Facebook has spent heavily on its own analytics over the last three years, with the aim of making you -- the marketer -- fully immersed in the Facebook platform…and perhaps also to gloss over one important fact about Facebook’s reporting on its own Ads: most companies spend money with Facebook 'acquiring' users who would have bought from them anyway. Could that be you? Here are a few ways to think about tracking Facebook Ads beyond simple clicks and impressions as reported by FB themselves. The scenario Imagine a shopper named Fiona, a customer for your online fashion retail store. Fiona has browsed through the newsfeed on her Facebook mobile app, and clicks on your ad. Let’s also imagine that your site -- like most -- spends only a portion of their budget with Facebook, and is using a mix of email, paid search, affiliates and social to promote the brand. The likelihood that Fiona has interacted with more than one campaign before she buys is high. Now Fiona buys a $100 shirt from your store, and in Facebook (assuming you have ecommerce tracking with Pixel set up) the sale is linked to the original ad spend. Facebook's view of ROI The return on investment in the above scenario, as calculated by Facebook, is deceptively simple: Right, brilliant! So clear and simple. Actually, not that brilliant. You see Fiona had previously clicked on a Google Shopping ad (which is itself powered by two platforms, Google AdWords and the Google Merchant Center) -- how she found your brand -- and after Facebook, she was influenced by a friend who mentioned the product on Twitter, then finally converted by an abandoned cart email. So in reality Fiona’s full list of interactions with your ecommerce site looks like this: Google Shopping ad > browsed products Facebook Ad > viewed product Twitter post > viewed same product Link in abandoned cart email > purchase So from a multi-channel perspective, how should we attribute the benefit from the Facebook Ad? How do we track the full customer journey and attribute it to sales in your store? With enough data you might look at the probability that a similar customer would have purchased without seeing that Facebook Ad in the mix. In fact, that’s what the data-driven model in Google Marketing Platform 360 does. But without that level of data crunching we can still agree that Facebook shouldn’t be credited with 100% of the sale. It wasn’t the way the customer found your brand, or the campaign which finally convinced them to buy. Under the most generous attribution model we would attribute a quarter of the sale. So now the calculation looks like this: It cost us $2 of ad spend to bring $1 of revenue -- we should kill the campaign. But there's a catch Hang on, says Facebook. You forgot about Mark. Mark also bought the same shirt at your store, and he viewed the same ad on his phone before going on to buy it on his work computer. You marked the source of that purchase as Direct -- but it was due to the same Facebook campaign. Well yes, Facebook does have an advantage there in using its wide net of signed-in customers to link ad engagement across multiple devices for the same user. But take a step back. Mark, like Fiona, might have interacted with other marketing channels on his phone. If we can’t track cross-device for these other channels (and with Google Marketing Platform we cannot), then we should not give Facebook an unfair advantage in the attribution. So, back to multi-channel attribution from a single device. This is the best you have to work with right now, so how do you get a simple view of the Return on Advertising Spend, the real ROI on your ads? Our solution At Littledata we believe that Google Analytics is the best multi-channel attribution tool out there. All it misses is an integration with Facebook Ads to pull the ad spend by campaign, and some help to set up the campaign tagging (UTM parameters) to see which campaign in Facebook brought the user to your site. And we believe in smart automation. Shhhh...in the past few weeks we've quietly released a Facebook Ads connection, which audits your Facebook campaign tagging and pulls ad cost daily into Google Analytics. It's a seamless way to pull Facebook Ads data into your overall ecommerce tracking, something that would otherwise be a headache for marketers and developers. The integration checks Facebook Ads for accurate tagging and automatically pulls ad cost data into GA. The new integration will normally only be available in higher-tier plans, but we're currently offering it as an open beta for ALL USERS, including Basic plans! For early access, just activate the Faceb|ook Ads connection from your Littledata dashboard. It's that easy! (Not a subscriber yet? Sign up for a free trial on any plan today.) We believe in a world of equal marketing attribution. Facebook may be big, but they’re not the only platform in town, and any traffic they're sending your way should be analysed in context. Connecting your Facebook Ads account takes just a few minutes, and once the data has collected you’ll be able to activate reports to show the same kind of ROI calculation we did above. Will you join us on the journey to better data?

After you've created an ecommerce startup, the initial goals are all about recovering costs and expenses. As soon as the profit margins rise and you've broken even, you face some big decisions that will decide the growth of your online business. First of all, should you start outsourcing? Because many first-time entrepreneurs think it's more cost-effective to do everything on their own, it is a common mistake to pass on hiring freelancers. In this post I’ll highlight the core benefits of outsourcing your ecommerce operations. Focus & growth There are many aspects to promoting your product, and ecommerce operations is an integral component of your company's growth. By outsourcing your ecommerce operations, you have the time to focus on the goals and growth of your company. When hiring a freelancer from a reputable marketplace such as FreeeUp.com, your contract will protect both parties. The roles are clearly defined and you get expert advice in key areas. Your time is valuable, and when you free up your days to re-focus on growing sales, the sky is the limit. Short-term & long-term options First of all, this isn't an all-or-nothing decision. Hiring freelancers can be short-term or long-term depending on the needs of your business. By delegating specific tasks to various experts, your business has the opportunity to grow and flourish as you originally intended. You also have the unique opportunity to scale as needed without the commitments that traditional employment requires. And experts are exactly that - experts! Why reinvent the wheel? The need for a skillset As your company grows, your knowledge grows. Creating an ecommerce startup has a steep learning curve, however, and outsourcing for expert advice makes a lot of sense. Coaching a freelancer is not required as they are already specialized in their skillset. By hiring freelancers, your business can grow outside of your core expertise. For instance, why spend time learning about optimizing landing pages for conversions when you can just hire an Optimizely expert? Furthermore, professionalism is a must when running a business. Your company will gain a professional profile with experts at your side. Until you've gained the expertise, winging it is just bad business. If you've spent countless hours (or possibly weeks) researching ecommerce operating skills, it is time to consider hiring outside of your skillset. Freelancers are highly knowledgeable in their specific niches, and outsourcing your ecommerce operations (and other important roles such as social media and marketing), will benefit your business. Working at full capacity Being more efficient with your time is a smart business decision. When you're stretched too thin or feeling overwhelmed with all the tasks of the company, hiring a freelancer is a no-brainer. Avoiding business burnout is key. As the owner/founder/boss (and probably CMO/CEO to boot), your business needs you to be working at full capacity. Making a list of the tasks that need to be completed is a smart business move. The next step is to start outsourcing as needed. You can learn from these experts and expand your business while optimising your time in the areas you already know -- while maintaining a clear overview of your ecommerce site. Excellent customer service (doesn't necessarily start with you) There's no question that customer service is a key component for the success of your business. Platforms like Shopify have emphasized this to their merchants to help them grow. Today's consumers are demanding, and catering to your customers’ needs can quickly take all your time and energy. Remaining professional requires focus and support, which is why hiring freelancers to maintain exceptional customer service is a key component to the growth of your company. Upgrades & maintenance Ultimately, the goal is to keep everything running smoothly. When you regularly hit profit margins and your goals are being met, upgrades and maintenance will be an ongoing issue. You might want to expand your server capacity due to increased traffic, for instance, or revamp your blog. It's no surprise that the top benchmarks for growing a Shopify store include page load speeds and server response time. Even though upgrades and maintenance to support growth are positive issues, it can be time-consuming to keep everything afloat. Moreover, once you meet your goals, you’ll want to expand. Hiring freelancers allows you to make sure that everything runs smoothly as you venture out into new areas or even new businesses. The bottom line is that one person cannot do it all. Outsourcing for various skillsets will make a world of difference for your company -- and your peace of mind. Start outsourcing your ecommerce operations The benefits of outsourcing your ecommerce operations to freelancers are countless. By outsourcing your ecommerce operations, you free up valuable time to remain focused and goal-oriented. Your business started from passion -- it is important to maintain that vision and hire freelancers to help meet your targets and objectives.   This is a guest post by Connor Gillivan, CMO and co-owner of FreeeUp, a rapidly growing freelance marketplace making hiring online simpler (check out their info on hiring for ecommerce). He has sold over $30 million online and hired hundreds of freelancers himself to build his companies.

We recently launched the Littledata Help Center to make it easier for customers to find the most relevant answers to their analytics questions. You can think of it as the more formal, technically-minded cousin of our popular analytics blog (which you're reading right now). With detailed new articles on Shopify tracking and how our ReCharge integration works, the Littledata Help Center is a go-to resource for current customers and ecommerce managers looking for a clearer view of how to use Google Analytics effectively. About our Help Center Like many startups, we began by using our blog as the main support resource, with articles on everything from Google Analytics to GDPR. Yet as we've grown, so have the number of setup guides and technical details we feel we should provide for a seamless user experience. In short, our support articles have outgrown the blog! Not to worry, blog fans. The blog will continue to be a resource for anyone interested in ecommerce analytics. We've been honoured at all the industry attention our blog has received, and we look forward to growing both resources side-by-side in the coming years. Shopify tracking Until you know what to look for, choosing the right Shopify reporting app can seem like a daunting process. There are a number of apps that are good at tracking just one thing, or helping you visualise some of the tracking you already have set up. Littledata's Shopify app is different. It's become especially popular with Shopify Plus stores and medium-sized Shopify sites on the enterprise growth path because it fixes your tracking and provides a full optimisation suite, including automated reports, benchmarks and buyer personas, to help optimise for dramatically higher revenue and conversions. New support articles help break down how this all-in-one solution works, including what you can track with our Shopify reporting app and setup guides for basic and custom installations. ReCharge integration Advanced Google Analytics integration for stores using ReCharge is one of our most popular integrations. It's a streamlined way to get accurate subscription analytics, including marketing attribution and LTV reporting. New support articles break down how ReCharge integration works with Littledata. You'll find guides on everything from how to check if the integration is working, to FAQs and more technical articles about tracking first-time versus recurring payments with GA views. We hope you take full advantage of Littledata's Help Center. Of course, you can always reach out to our support team directly from the Intercom popups on our blog, public site and app. We're available Monday to Friday in time zones around the world. Don't hesitate to get in touch, and remember -- your success is our success!

How does the Littledata app work? It's magic! Or at least it feels that way. This new video gives a quick overview of how it all fits together. Our ecommerce analytics app is the only one on the planet to both fix your tracking and automate reporting. Our customers see dramatic growth, from higher add-to-cart rates to better return on paid search. But what happens first, and what happens next? If you're an ecommerce marketer using Google Analytics, Littledata will make your job a whole lot easier. The process breaks down to four core steps, which you can repeat as often as you'd like. First you connect your analytics account, marketing channels like Google AdWords and Facebook Ads, and website data from tools like Shopify, ReCharge and CartHook. (And yes, we'll help you comply with GDPR). Then you use the Littledata app to audit your analytics setup and fix your tracking. Shopify stores can fix tracking automatically -- other sites get clear recommendations on what to do. If your goals include higher marketing ROI and increased conversions, the next step is to automate reporting with report packs and a smart dashboard, available directly in the app. And then it's time to optimise revenue with industry benchmarks, enhanced reporting and buyer personas, all built automatically. Sign up today for a free audit of your analytics setup, or book a demo to learn more. A complete picture of your ecommerce business is just around the corner!

When is the last time you audited your Google Analytics account? If the answer is 'never', I understand, but you could be wasting a ton of cash - not to mention potential revenue. It's easy to put off an analytics audit as a 'someday' project considering the multitude of other tasks you need to accomplish each day. But did you know that auditing your Google Analytics account can save you money and add a big bump to online revenue, even with sites that are not ecommerce? Whether people spend money directly on your site, or your site is primarily for lead generation, you spend money to get those site visitors through your marketing channels. When you view a channel like AdWords, there is a clear financial cost since you pay for clicks on your ads. With organic traffic, such as from Facebook fans, you spend time crafting posts and measuring performance, so the cost is time. With an investment of any resource, whether time or money, you need to evaluate what works - and what does not - then revisit the strategy for each of your marketing channels. In this post, I’ll walk you through some of the automated audit checks in Littledata and take a look at what they mean for your online business. If your analytics audit doesn't ask the following questions, you're probably wasting money. Is your AdWords account linked to Google Analytics? If you run AdWords campaigns, linking AdWords and Analytics should be at the top of your to-do list. If AdWords and Analytics are not linked, you cannot compare your AdWords campaign performance to your other channels. Although you can still see how AdWords performs within the AdWords interface, this comparison among channels is important so you can adjust channel spend accordingly. If you discover that AdWords is not delivering the business you expected compared to other marketing channels, you may want to pause campaigns and reevaluate your PPC strategy. Are you tracking website conversions? There should be several conversion goals set up on your website because they represent visitor behavior that ultimately drives revenue. The above example shows a warning for a lead generation website. Although it is possible that no one contacted the site owner or scheduled an appointment in 30 days as indicated in the error, it does seem unlikely. With this warning, the site owner knows to check how goals are set up in Google Analytics to ensure they track behavior accurately. Or, if there really was no engagement in 30 days, it is a red flag to examine the strategy of all marketing channels! Although the solution to this warning will be different based on the individual site, this is an important problem to be aware of and setting up a goals in Google Analytics, such as for by destination, is straightforward. You can also get creative with your goals and use an ecommerce approach even for non-ecommerce websites. Do you use campaign tags with social media and email campaigns? This is an easy one to overlook when different marketing departments operate in silos and is a common issue because people do not know to tag their campaigns. Tagging is how you identify your custom social media and email campaigns in Google Analytics. For example, if you do not tag your paid and organic posts in Facebook, Google Analytics will lump them together and simply report on Facebook traffic in Google Analytics. In addition to distinguishing between paid and organic, you should also segment by the types of Facebook campaigns. If you discover poor performance with Facebook ads in Google Analytics, but do great with promoted posts in the Facebook newsfeed, you can stop investing money in ads at least for the short term, and focus more on promoted posts. Are you recording customer refunds in GA? Refunds happen and are important to track because they impact overall revenue for an ecommerce business. Every business owner, both online and offline, has dealt with a refund which is the nature of running a business. And this rate is generally fairly high. The return rate for brick-and-mortar stores is around 9% and closer to 20% for online stores, so less than 1% in the above audit seems suspicious. It is quite possible the refund rate is missing from this client’s Google Analytics account. Why does this matter? Let’s assume the return rate for your online store is not terrible - maybe 15% on average. However, once you track returns, you see one product line has a 25% return rate. That is a rate that will hurt your bottom line compared to other products. Once you discover the problem, you can temporarily remove that product from your inventory while you drill into data - and talk to your customer support team - to understand why that product is returned more than others, which is a cost savings. Are you capturing checkout steps? Most checkouts on websites have several steps which can be seen in Enhanced Ecommerce reports in Google Analytics. Shoppers add an item to their cart, perhaps log-in to an existing account or create a new one, add shopping information, payment etc. In the ideal world, every shopper goes through every step to ultimately make a purchase, but in the real world, that is rare. Last year alone, there was an estimated $4 trillion worth of merchandise abandoned in online shopping carts. Reasons for this vary, but include unanticipated extra costs, forced account creation, and complicated checkouts. By capturing the checkout steps, you can see where people drop out and optimize that experience on your website. You can also benchmark checkout completion rates see how your site compares to others. Are you capturing product list views? If you aren't tracking product list views correctly, your biggest cash cow might be sleeping right under your nose and you wouldn't even know it! Which products are the biggest money makers for you? If a particular product line brings in a lot of buyers, you want to make sure it is prominent on your website so you do not leave money on the table. Product list views enable you to see the most viewed categories, the biggest engagement, and the largest amount of revenue. If a profitable product list is not frequently viewed, you can incorporate it in some paid campaigns to get more visibility. The good news An audit is not only about what needs fixing on your website, but also can show you what is working well. After you run an audit, you will see the items that are set up correctly so give yourself a pat on the back for those - and know that you can trust reporting based on that data. Either way, remember to run an analytics audit regularly. Once a month is a good rule. I have seen cases where a website was updated and the analytics code was broken, but no one noticed. Other times, there may be a major change, such as to the customer checkout, so the original steps in your existing goal no longer work. Or an entirely new marketing channel was added, but with missing or inconsistent tagging. It is worth the time investment to ensure you have accurate Google Analytics data since it impacts influences your decisions as a business owner and your bottom line. Littledata's automated Google Analytics audit is especially useful for ecommerce sites, from online retailers to membership sites looking for donations. It gives a clear list of audit check results, with action plans for fixing your tracking. And Shopify stores can automatically fix tracking to capture all marketing channels and ensure that data in Google Analytics matches Shopify sessions and transactions (not to mention the data in your actual bank account!), even when using special checkouts like ReCharge and CartHook. When you're missing out on the revenue you should already have, an audit is the first step in understanding where it's falling away, or where you're over-spending. Run an audit. Make a list. Fix your tracking. Grow your revenue. Sometimes it really is that simple!

We're excited to announce that Littledata now fully integrates with CartHook. The integration provides automatic tracking for sales from CartHook's one-page checkout and connects that data to marketing channels and shopper behaviour. Littledata -- CartHook integration is the easiest way to get accurate data and smart reporting to improve sales and marketing ROI. All you need is a Shopify store with CartHook Checkout installed (even for just one product) and a Google Analytics account! What is CartHook? CartHook makes it easy for Shopify stores to add customisable one-page checkouts and post purchase one-click upsells. Their intuitive funnel builder lets any store customise the checkout process to increase conversions and decrease abandonment. Features include: Customisable one-page checkout One-click post-purchase upsells, including for subscription products (works great with our ReCharge integration) Product Funnels allow you to send traffic to a pre-loaded checkout page from any landing page Native Shopify integration means no custom coding required! How it works Integrating CartHook with Littledata ensures that all sales activity is tracking correctly in Google Analytics. Littledata weaves together your Shopify and CartHook data and connects it with your marketing channels and campaigns. Why spend developer time on custom scripts and events when you can just activate the integration in a couple of minutes? Benefits of CartHook integration: Sales tracking - Get automatic tracking for sales from CartHook, seamlessly synced with sales made via standard Shopify checkout Marketing attribution - Connect marketing channels and campaigns with shopping cart activity and buyer behaviour Optimisation - Scale the smart way with Littledata's industry-leading optimisation tools, including a personalised dashboard, report packs, benchmarks and buyer personas It's all about accurate data. Littledata's script runs in the background, pulling from CartHook, Shopify, and any other source you've connected to your analytics. If you're an advanced Google Analytics user, you can dig into the improved data collection directly in GA. Read more about why CartHook customers should use Littledata. Setup guide For the Littledata -- CartHook integration to work, you need to have both apps installed for your Shopify store, then connect them by activating the integration. Install CartHook and Littledata Follow these steps to activate the integration Yes, it's that easy! Shopify Plus If you run a larger Shopify store on Shopify Plus, we're here to help you scale. Both Littledata and CartHook offer enterprise plans that include custom setup and a dedicated account manager. Larger stores looking for an enterprise plan or managed services are encouraged to sign up directly and then contact us for a free consultation. If you're a digital agency with multiple customers on Shopify using CartHook, even better! Check out our agency partner program for Shopify experts.

It happens. Every now and then, Facebook disapproves ads when they violate the platform’s terms and conditions in some way. When this happens, you, of course, want to know exactly why so you can avoid ad disapproval going forward or make appropriate adjustments to a recently disapproved ad. It’s how we learn. Most ecommerce sites have a huge Facebook presence for both branding and sales. Whether you're selling directly through Facebook with BigCommerce and advertising for those products, or running FB ads for a Shopify plus store or any other kind of website, here are 10 possible reasons Facebook disapproved your ad. This article will describe each reason in detail to help you determine why Facebook rejected the proposed ad, and how you can avoid these issues going forward. Reason #1: A non-functioning landing page There’s nothing more frustrating than clicking on an ad only to be directed to a web page that doesn’t function. How annoying would it be if you can’t click on the “Contact Us” tab because the tab wasn’t linked to the right web page? How frustrating would it be if a video in the landing page wouldn’t play? If your ad leads users to a non-functioning landing page containing poor navigation or broken links, Facebook will disapprove your ad. To prevent a non-functioning landing page, you or your web developer should conduct a thorough examination of the landing page to ensure it’s easy to navigate and to ensure it contains no broken links. Reason #2: A landing page that doesn’t match the ad content More commonly known as clickbait, ads promoting content that doesn’t match the landing page violate Facebook’s advertising policies. Clickbait is deceptive, promising users one thing but then giving them something completely different and unexpected. Facebook is especially cracking down on clickbait ads in light of the Cambridge Analytica scandal and the prominence of “fake news.” To avoid disapproval because of clickbait, make sure your ad content accurately indicates what users will see on the landing page. If you're having trouble figuring out which ads to run, try creating user personas to understand your customers, then create and optimise ads based on those personas. Are you advertising to the right buyer personas? Reason #3: Inappropriate or offensive ad content Ads that contain profanity, sexual innuendo and discrimination are considered inappropriate or offensive and will be disapproved. Since the earliest age a user can join Facebook is 13, the network strives to foster a family friendly environment that everyone can enjoy. If your ad contains inappropriate or offensive content, consider altering the ad and the angle you want to take to deliver your message. Reason #4: Content encouraging illegal or unethical behavior Facebook is not the platform for you if your message involves promoting illegal or unethical behavior, for example, promoting spy and malware products. As previously mentioned, Facebook is focused on family friendly experiences. Ads that promote negative behaviors will be disapproved without a second thought. Reason #5: Third-party infringement Whether intentional or unintentional, sometimes ads infringe or violate a third-party’s copyright or trademark. If it does, and Facebook disapproves it as a result, you may only be required to make a slight alteration. For instance, if your ad contains a copyrighted photo, you may only need to change the photo. To avoid third-party infringement, create original content for all of your ads rather than taking, for example, an image for your ad from a stock-photo site. In addition to complying with Facebook’s policies, doing so will also make your ads unique to your brand. Reason #6: Misleading or false content Content that is false or misleading will not be tolerated, as it qualifies as “fake news.” It may be tempting to make claims about products or services that are untrue in order to build interest. But authenticity and truthfulness are essential for establishing trust and credibility with your customers. Make sure there is nothing in your ad’s text or creative that is misleading or false. For example, if your ad has the title “Kim Kardashian reveals her fitness secret,” but takes users to a landing page that only contains promotions for weight loss pills with no mention of Kim Kardashian or her fitness secret anywhere, this ad would be disapproved. Reason #7: Prohibited products or services Facebook’s Advertising Policies list all of the products or services it prohibits. Prohibited items and services include: • Surveillance equipment • Payday loans • Counterfeit documents • Tobacco • Unsafe supplements • Adult content, products, or services • Weapons • Marijuana If your business revolves around selling or promoting any products or services from this list, Facebook advertising is not for you. Reason #8: Low-quality or disruptive content If your ad contains slow loading pages, broken links, or poor grammar, Facebook will disapprove it. Yes, poor grammar is truly a reason for ad-rejection! Facebook has a standard it tries to maintain across the platform, and a big part of maintaining that standard includes putting out high-quality ads. To avoid submitting low-quality or disruptive ads, carefully review your content to make sure it looks polished and professional, as well as provides a seamless experience with no disruption. Reason #9: Disruptive animation that plays automatically Video ads that play automatically, taking away a user’s decision to click or not to click, are disruptive to the user experience. Soundless video ads that play automatically are acceptable if the quality is exceptional. But flashing animations or loud and obnoxious ads are not conducive to Facebook’s standards of quality and will be disapproved. Reason #10: Controversial content for commercial purposes This reason is especially important in light of the recent focus on misuse of the Facebook platform in political sectors. In one instance, Russian troll accounts distributed politically divisive ads, and in another, the Cambridge Analytica data firm deceptively collected information from over 80 million profiles to deliver manipulated messages during the 2016 US Presidential Election. In response, Facebook is not pulling any punches for controversial ad content. Ads highlighting issues like abortion or gun control for financial gain will be disapproved. What to do if your ad is disapproved Luckily, Facebook recognizes that no one is perfect and offers you two options if your ad is disapproved. Option 1: Edit your ad. Option 2: Appeal Facebook’s disapproval decision. There are three steps to Option 1: Step 1: Read the email your advertising account received when your ad was disapproved. Step 2: Edit your ad per the instructions in the email. For instance, you may be required to edit your ad’s text, images, or call-to-action. Step 3: Save your changes and resubmit your ad. If you choose option two, you can complete an Appeal a Decision form. By doing so, you’re requesting that Facebook review your ad once again to consider the possibility that a mistake was made in the decision to disapprove your ad. This option is appropriate if it isn’t entirely clear whether Facebook’s justification for disapproving your ad matches its Advertising Policies. Mistakes are an opportunity to learn. If your Facebook ad gets disapproved, simply use it as a growing experience and you will succeed.   This is a guest post by Anna Hubbel, staff writer at AdvertertiseMint, a Facebook advertising company. Hubbel writes on various topics, including social media, digital advertising, and current events.

It’s World Cup fever here at Littledata. Although two of the nationalities in our global team didn’t get through the qualifiers (US & Romania) we still have England and Russia to support in the next round. And I think the World Cup is a perfect time to explain how marketing attribution works through the medium of football. In football (or what our NYC office calls 'soccer'), scoring a goal is a team effort. Strikers put the ball in the net, but you need an incisive midfield pass to cut through the opposition, and a good move starts from the back row. ‘Route one’ goals scored from a direct punt up the pitch are rare; usually teams hit the goal from a string of passes to open up the opportunity. So imagine each touch of the ball is a marketing campaign on your site, and the goal is a visitor purchasing. You have to string a series of marketing ‘touches’ together to get the visitor in the back of the net. For most ecommerce sites it is 3 to 6 touches, but it may be more for high value items. Now imagine that each player is a different channel. The move may start with a good distribution from the Display Ads defender, then a little cut back from nimble Instagram in the middle. Facebook Ads does the running up the wing, but passes it back to Instagram for another pass out to the other wing for Email. Email takes a couple of touches and then crosses the ball inside for AdWords to score a goal – which spins if off the opposing defender (Direct). GOAL!!! In this neat marketing-football move all the players contribute, but who gets credit for the goal? Well that depends on the attribution model you are using. Marketing attribution as a series of football passes Last interaction This is a simplest model, but less informative for the marketing team. In this model the opposing defender Direct gets all the credit – even though he knew nothing about the end goal! Last non-direct click This is the attribution model used by Google Analytics (and other tools) by default. In this model, we attribute all of the goal to the last campaign which wasn’t a Direct (or session with unknown source). In the move above this is AdWords, who was the last marketing player to touch the ball. But AdWords is a greedy little striker, so do we want him to take all the credit for this team goal? First interaction You may be most interested in the campaign that first brought visitors to your website. In this model, Display ads would take all the credit as the first touch. Display often performs best when measured as first interaction (or first click), but then as a ‘defender’ it is unlikely to put the ball in the net on its own – you need striker campaigns as well. Time decay This model shares the goal between the different marketing players. It may seem weird that a player can have a fraction of a goal, but it makes it easy to sum up performance across lots of goals. The player who was closest to the goal gets the highest share, and then it decays as we go back in time from the goal. So AdWords would get 0.4, Email 0.5 (for the 2 touches before) and Instagram gets 0.1. Data-driven attribution This is a model available to Google Analytics 360 customers only. What the Data-driven model does is run through thousands of different goals scored and look at the contribution of each player to the move. So if the team was equally likely to score a goal without Facebook Ads run down the wing it will give Facebook less credit for the goal. By contrast, if very few goals get scored without that pass from Instagram in the midfield then Instagram gets more credit for the goal. This should be the fairest way to attribute campaigns, but the limitation is it only considers the last 4 touches before the goal. You may have marketing moves which are longer than 4 touches. Position based Finally you can define your own attribution weighting in Position Based model, based on which position the campaign was in before the goal. For example, you may want to give some weight to the first interaction and some to the last, but little to the campaigns in between. Still confused? Maybe you need a Littledata analytics expert to help build a suitable model for you. Or the advice of our automated coach known as the analytics audit. After all, every strategy could use a good audit to make sure it's complete and up-to-date. So go enjoy the football, and every time someone talks of that ‘great assist’ from the winger, think of how you can better track all the uncredited marketing campaigns helping convert customers on your site.

We're excited to announce a new partner program for agencies! The pilot version was a huge success, so now we're opening up the program to any agency looking for a smarter ecommerce analytics solution. If you're using a BI dashboard and maybe some tools like Data Studio and Supermetrics, that's great, but you still need an advanced analytics solution like Littledata. Our app takes data science to the next level by actually fixing your customers' Google Analytics setups to ensure accurate tracking at every customer touch point. Then the app uses that data to automatically build smart, relevant reports. Additional benefits for partners include advanced setup with GTM and Facebook Pixel, custom reporting and analytics training. It's a win-win! If you're a digital agency with ecommerce clients, Littledata will make your job a whole lot easier. Ecommerce analytics for agencies Partnerships are at the centre of our business. At Shopify Unite this year, we announced the pilot phase of this new program that makes it easier for marketing agencies and ecommerce site developers to bring accurate analytics to their clients. But while Shopify is our most extensive integration, our agency partner program is designed for anyone working the ecommerce space, whether your clients are on Shopify Plus, Magento, Demandware, another platform or a custom build. As long as they're using Google Analytics to track marketing and shopping behaviour, Littledata will help you help them. Key benefits for agencies: Guarantee accurate data for your customers Save time by automating Google Analytics setup and reporting Automated reporting with proven results for ecommerce growth Custom views and dimensions in GA that you can use however you want Google-certified account managers to answer customer questions about analytics Easy access to client reports with our team members feature Analytics training for your team Complete ecommerce analytics suite: Scan and fix tracking issues with our industry-leading analytics audit tool Automate reporting with both pre-built report packs and custom reports for your client base Smart marketing tools, including buyer personas and Enhanced Ecommerce tracking for more effective AdWords retargeting Web and ecommerce benchmarks, plus an option for private benchmarks among your clients Subscription analytics for clients selling subscription boxes or offering subscription plans (we offer the only advanced Google Analytics integration for ReCharge stores) Easy integrations with apps like Refersion and Carthook How it works Our onboarding process for ecommerce agencies is very straightforward. It starts with a conversation where we can learn about each other's businesses. If it's a good match, we move on to sign a partnership agreement with clear terms for referrals and revenue share, then get you started with a test account for your first referral. The Littledata app creates a test property so that you - and your client, if you wish - can see how our tracking compares against the current Google Analytics setup. Once you go live with the new tracking, we work directly with your team to help you get the most out of the app's functionality, and begin to develop custom reports and private benchmarks, depending on what's most relevant to your agency business model. We also build a co-marketing plan with your team to help the partnership reach the right customers at the right time. And then - you got it - we grow together to take over the universe! Or at least we help growing ecommerce sites reach exponential levels of growth. (Read some customer stories.) Littledata's agency partner program is highly selective, but we do try to respond to all inquiries. So if you're looking for better ecommerce analytics for your clients, please do get in touch.  

Our European team had a fantastic time presenting Littledata's ecommerce analytics technology at this year's Techsylvania conference. But we weren't just there to speak, we were also there to listen, learn and be inspired. Here are some of our core takeaways from the 2018 event. If your mindset is set on innovation, Techsylvania is the place for you. It's the leading technology event in Eastern Europe for a reason - tech enthusiasts and business innovators come together in a spirit of collaboration and friendly competition to connect, hack and share ideas. What we learned Edward Upton, CEO: I learned so much from pitching at the Startup Avalanche competition at Techsylvania. The competition attracted startups from all over Europe and Asia, and Littledata was honoured to be chosen for the finals. After a few days of rehearsing the pitch and refining the slides, with intensive coaching from the Risky Business team, I have a much better idea of what investors want to hear - and how to communicate it succinctly. Hearing how Intercom uses speed of product development as a competitive advantage made me remember how our (already Agile) process could be improved Aside from the pitch competition, I listened to some of the great speakers from across the industry. My favorite was from Rich Archbold, a technology leader at Intercom. Hearing how they use speed of product development as a competitive advantage made me remember how our (already Agile) process could be improved. Yet, the greatest learning came from talking to founders of many interesting tech companies, some based in Cluj and others with growing offices here. Rares Ionescu, QA Guru: Techsylvania was a blast! I was especially impressed by Ralph Simon, the chief executive of Mobilium Global, a visionary with a vast experience in the entertainment world. He is known as the founder of modern mobile industry, also referred to as the "Father of the Ringtone" making a lot of trending musical references during his talk. The speech was comprehensive on building a successful start-up ecosystem. Florina Vintan, Analytics Superstar: I was impressed by the number of high-level attendees with strong technical backgrounds. I most enjoyed the conversation on Digital Transatlantic Bridges by Peter Gersak (IBM), Frederic Boulanger (Macadamian), Pat Sheridan (Modus Create) and Lucas Roh (Bigstep). The chat revolved around companies that established offices in different parts of the world to break down the transatlantic barriers. In case you didn’t know, Littledata breaks down those barriers every day with offices in London, New York and Cluj-Napoca! Bianca Dihoiu, Customer Advocate: The conference vibe was amazing, people seemed excited to be there and discuss tech stuff with their fellow enthusiasts. The talk that I enjoyed most was by Ashley Carroll from Social Capital. It focused on product management best practices and helped me to visualize our own product management more clearly. As a customer research at Littledata, I bridge the gap between Product and Support, so this was a perfect fit! Elisabeta (Bety) Crisan, Finance Pro: As an account manager, I found Luke Mawbey’s speech on money laundering the most appealing. The Head of Technology at Comply Advantage talked about a future in technology that will automatically fight financial crime. In the breaks between the conferences we managed exchange a few words on account issues and I learned some useful tips and tricks. Ioana Botian, Marketing Rockstar: Techsylvania was a vibrant event highlighted by the sharing of a lot of valuable information! I loved the Startup Avalanche pitches where startups had a chance to present their unique ideas. We were represented by Edward Upton, founder of Littledata, who charmed the audience with his charisma and insights about the many ways that fixing your analytics can lead to higher revenue -- especially with our smart automation like an analytics audit and automated reporting. I loved the Startup Avalanche pitches where startups had a chance to present their unique ideas. I also attended a mind-blowing conversation between Anda Gansca, CEO and Co-Founder of Knotch, and Katherine Manderfield, Director of Content Strategy at The New York Times about the Future of Advertising. The panel was a real eye-opener for me that made me rethink my strategy as a marketer. Alexandra Dimitriu, Analytics Maven: For me, Techsylvania was highlighted by great questions, lots of ideas and an amazing atmosphere. I had a chance to meet many passionate people that are concerned with the future in technology and are willing to make a difference in the world. My favorite speech was the one from IVCBOX. They illustrated how successfully connecting with customers can drive conversions and increase sales -- all things we're passionate about here at Littledata. What a great event! David Pascu, Biz Dev Guru: I had the chance to network with various representatives of Romanian tech companies and gather knowledge about their business and revenue drivers. Most companies admitted they are facing great difficulties when it comes to talent acquisition, so more and more are starting to invest in internship programmes. With developers in high demand here, more and more Eastern European tech companies are investing in internship programmes Having the chance to hear various experts talk about their experience in starting or managing a company encouraged me to push for roadmaps ruthlessly oriented to success, as these days the key for success in our field is to build up processes oriented and matured to have the most impact with the least drain on resources. Gabriel Bira, Galactic Overlord of Code: Although I started out sceptical about yet another “tech conference”, my opinion quickly took a U-turn. The conference coupled professionals describing an exponential progress curve of the Eastern European country in the world of tech. I had the rare opportunity of attending a speech from a local maverick, a 19-year-old Storyheap entrepreneur, Sebastian Dobrincu. The presentation revealed many insights for me on how to build a successful company from scratch. I also attended a technical event, held by a representative of Slack, Jeremy Apthorp. He presented us Electron, an open source framework that allows creative applications in JavaScript, HTML and CSS to build cross-app platform at low costs. A final thought Techsylvania was a perfect mix of tech enthusiasts, developers and entrepreneurs. A true centre of innovation and inspiration. If you or someone you know is looking to join one of the hottest startups in Cluj, I have good news. We're hiring! Check out our open positions and read about one of our newest employee's first design sprint. We can't wait for next year's conference. See you there?

The number one reason for shopping cart abandonment is that online shoppers are simply not ready to complete the purchase yet. That’s something marketers have little control over. However, there is one thing you can control: the smart use of abandoned cart email flows. The average rate for documented shopping cart abandonment in 2017 is as high as 69.23%. But adjusting for technical performance and improving the checkout funnel can increase conversions for 35.26%. That’s $260 Billion worth of recoverable profit with through check-out optimization and better follow-up emails! No ecommerce owner wants to face cart abandonment. The customer has been so close to making a purchase, yet for some reason, your chance for profit slipped through your fingers. Don't worry though, the loss isn't final yet, because with the help of sales recovery tactics using email marketing automation software, you can win your customers back. SaleCycle reports that around 31% clicked abandoned cart emails proceed to finish their purchases. The series of emails after cart abandonment is substantial because some clients leave their carts unintentionally. Reasons like site time-out, complicated check-out, or a website crash may have interrupted their purchase. Here are the top three email strategies to win back abandoned carts! 1. Set up the right abandoned cart email sequence The right email sequence triggered at just the right time makes a tremendous amount of difference. Marketo recommends a series of three emails scheduled as follows. I've included some actual email examples to help illustrate the points. Send the first email within an hour of cart abandonment You have to drive your clients to continue with the purchase before they leave their computers. The first email aims to address technical glitches. Don’t sound pushy, just aim to help the client just in case the abandonment is not intentional. Below is an example of a gentle reminder for the first email. Send the second email after one day This time, you have to create a sense of urgency. The cart abandonment email below by Grove informs the client that the cart will expire soon. You may also talk about fleeting discounts or stock availability. And send the final email after 48 hours This is your last chance to win your client back so give it your best shot. You can give incentives like free shipping, bonus items or an additional discount. Here's an example of a final abandoned shopping cart email that works extremely well. It comes from the ecommerce site for Aéropostale. 2. Use catchy, personable email copy Your success in re-directing your clients to the shopping cart starts at a smart subject line. It will dictate if your client clicks on your email. So, craft subject lines that drive receivers to click on. One example is this email subject line by Helm Boots: These will look great on you The words strike empathy and curiosity. It gives a sense of compliment which will compel the receiver to click on. Not so different from what a friend would tell you in real life while actually shopping in a store!   Appeal to your clients through creative wordings and graphics. It helps to know your buyer personas so that your copy will be more fitting. Use words that your clients can easily relate too. Humor is also a great way to spice up your content. The email below by Chubbies is clever, cool, and compelling. The visuals and wordings charm their target customers who are carefree and adventurous. 3. Use multiple, eye-catching buttons and links The email above by Chubbies also aced this up. It has three active links that direct the client back to the cart. The title, the main image, and the CTA button at the end of the copy are all clickable. Notice also that all the clickable elements stand-out from the rest of the copy. This makes it easier for your client to notice and click on your CTAs. The button below is cleverly worded. It has a distinct color and size you can’t miss. The copy further explains which elements are clickable in a friendly way. The CTA button is already clear but the added explanation guides the clients on the next steps and avoids confusion. Conclusion: Even before you start these top three tactics to get your customers back, you need the data to know which of your customers have abandoned their carts. Data analytics and triggers do this for you. They provide the information as to whom and when abandoned carts happen. The first step in solving your marketing problems is to identify what the problems are. Data analytics and triggers help you identify these glitches so you’ll know what to do next. After you have accurate data about who’s abandoned their carts, set up an email marketing automation software to automatically send your email series through behavioral triggers like shopping cart abandonment. Then drill down into analytics about every ecommerce checkout step to see where you can improve. With the correct data, effective automation software, perfectly timed emails, topnotch copy, and striking CTAs, you can leverage your losses into profits. You can gain back a part of the $260 Billion worth of recoverable earnings - and start to increase your add-to-cart rate too!   This is a guest post by Kimberly Maceda, a Content Writer for ActiveTrail. Kimberly writes for some top online marketing sites and blogging advice on email marketing and marketing automation. Activetrail is a leading provider of professional-grade email marketing and automation software for growing businesses.

Are you generating enough site traffic? Are there enough visitors each month that engage with your content and spend time on your site? Those are good things, but the important question is how you are doing with conversions, as that is where the magic happens! For many businesses, there will be slumps where conversions are not where you need them to be and increasing conversions is tougher than bringing in visitors. The reasons for not converting are many, which could include a poorly designed landing page or frustration with a slow page load time. Fortunately, the technical aspects of your site are somewhat clear cut and influence all users to the site. Either it loads quickly or it does not. It responds to mobile devices or does not. But there are principles that are about the groups visitors to a site. What do they search for and can you provide it? How are they different from each other? How are they similar? In short, you need smart segmentation if you want to continue to increase conversions. Here's a quick guide to using segments in Google Analytics. Segments vs personas In this post, we will build on some of the work you have hopefully done to create personas and highlight the value of segments when optimizing for conversions. Personas help you be empathetic to your customers. Visualizing a 35-year old professional female makes it easier to create the right message for her rather than general messages to all women. This is not about stereotypes. Personas help you hypothesize about similarities in how people behave. So how is that different from segments? There is confusion with segments versus personas and you want establish a definition for your team so you all work from the same framework. In the simplest terms, you segment your audience with existing data and create campaigns based on personas. Start with your segments. With Google Analytics, you can use segmentation to group people by identifying criteria such as location. Think of segments as the somewhat objective view of your audience based on raw data. (There is still some subjectivity when deciding the makeup of segments). Personas are very subjective - based more how a person thinks or feels. Get to know your audience with Google Analytics Google Analytics provides a lot of data that helps us understand our segments if we go beyond basic metrics, such as pageviews. Below are a few ways to learn more about your segments with the goal of increasing conversions and adding depth to your personas. Pages per Session: This is a basic metric in Google Analytics but you can go beyond scenarios, such as users visiting two pages compared to those visiting seven pages. Look at which pages they visited. Did they visit the intro offerings (probably a newcomer) or the help section (probably an existing customer)? Did they read the entire section about a topic (more methodical) or buy on the first visit (maybe more impulsive)? Note these are assumptions about motivations but you can develop hypotheses based on behavior. Content Grouping: Content grouping categorizes your site content based on rules created in the Admin section of your Google Analytics account.   Once you have these rules, you can view content groups for different scenarios, such as where people are the journey, how they flow through content, how they came into your site (traffic source), and how much time they spent on there. For sites with thousands of pages, this makes it more manageable than viewing individual pages. You can analyze conversions on the categories of your site rather than a specific page. Cohort Analysis: Found in the Audience section of Google Analytics, this is used to examine the behavior and performance of groups of users related by common attributes. It allows you to view a group of visitors based on a shared acquisition date. If you have a drip campaign scheduled for May, you may want a Cohort Date Range of May 1 to May 7 to target people who first visited the site during that time period. You can learn if people who visited on a specific day were more inclined to visit again than other members of that group. User Login: Custom Variables can be fired when users login. That provides additional data for more advanced segments by identifying the behavior of different customer types. Site visitors self-segment when they log into the site to take an action. With Custom Variables, you can see how behavior is different for those who log-in versus those who do not. Bounce Rate: We all get hung up on this metric. People see a site bounce rate of 78% and begin to panic but you need to drill in to see if that matters. Do existing customers and regular visitors bounce from a blog post? That is expected. However, if new people regular bounce from the site, look at the landing pages. There could be a message mismatch with the source that sent them to a particular page. Affinity Segments: Use affinity and in-market segments in Google Analytics to help define your personas. They are broad classifications about users which may be helpful when layered on top of other characteristics. For example, you may discover segments that prefer one content grouping over another. Collect metrics that matter When there is a difference in the conversion rate and user journey among segments, it indicates your identified segments truly represent distinct types of users. Read that again because whether your segments make sense determines whether your data is any good. With the right segments, you can determine which groups to cultivate or which ones to not pursue with limited resources. For example, if one segmented group regularly buys add-ons for product, that might justify allocating more advertising dollars. With target segments identified, you can also look at which marketing effort attracted them to your site. Some of this is obvious. If users in their 30s never respond to a CTA on your site from Facebook, you may not want to pay for ads on that channel or even post to it regularly. So yes, we all care about who converts compared to those who do not. But remember there are stages leading up to a conversion and this Facebook audience could still have a role, so watch where in the process people drop off. And hopefully by now you realize that non-converters are more than just non-converters. View this by segment too to identity what non-converters may have in comment. As data comes in, additional segmenting can be done by on locations, time of conversion, brand search terms versus early stages searches. But do not collect data for the sake of collecting data. Although it is easy to do with the abundance of data available in Google Analytics, it does not guarantee a return for your efforts. Want to know more? Get in touch with Tina’s agency, 360 Internet Strategy, and follow her on LinkedIn.  

Littledata believes that happiness and productivity go hand-in-hand, but what does that look like in practice? In this post I'll share a bit about our workplace culture and most recent design sprint, from the perspective of me, our newest team member! Four years ago a new company emerged - Littledata. Fast forward to today and we have major ecommerce customers around the world, including Made.com, Figleaves and Age UK. Our consulting business has grown to develop a suite of ecommerce analytics technology that anybody can use - including an industry-leading analytics audit, automated reporting with Google Analytics and even a dedicated Shopify reporting app. And the team has continued to expand - Meet our great team here My story I joined Littledata two months ago, and it's already been an amazing journey. I was working as a marketing specialist at a Romanian company when a friend pinged me about the opportunity to work at Littledata. I was not looking for a job at the time but I was impressed about the innovative app they had created, so I knew I had to meet them. Initially, I applied for an open position listed on Littledata's careers page. Unfortunately, my background experience in that field was not so generous and I did not get the job. (True story!) But no worries there, as Littledata saw potential in my good attitude, proactive work ethic and willingness to learn. After some additional interviews and a test project, they gave me a chance and created a new position for me as a marketing assistant. This was a clear sign of an open-minded work culture that invests in its employees and focuses as much on potential as on experience. In short, I accepted the job and joined the European team. It was one of the best professional decisions I've ever made. Since I joined Littledata I've learned more in two months than in an entire year at other companies. My colleagues and supervisor took time and patience to teach me and guide me through skills that otherwise I couldn’t have learned by myself. Littledata is a data company - and Google Analytics isn’t easy stuff - but since we’re dedicated to making analytics as painless and as useful as possible to our customers, it’s an exciting and exhilarating place to work. There are new challenges and great successes every single day in the office. Besides the best mentorship I am receiving, my peers proved to be very fun and sociable. It’s a place where we do work as a TEAM, helping and supporting each other. The only competition we have is from our competitors. Moreover, the perks I got with the job with remote-working hours and annual offsites in a different countries, easily trump the perks of working at big corporations. I discovered that the fast evolution of Littledata is due to its employees. Littledata’s senior staff believes that true innovation comes from happy employees. (Want to see the data? There is statistical evidence that happiness and a positive workplace culture drive both productivity and profit.) By focusing on building a strong internal bond, offering excellent benefits and driving diversity, Littledata created a one-of-a-kind workplace environment. Things weren’t always easy tough. They’ve had their share of challenges. See how Littledata went through the challenges of developing a Shopify integration. Where do we work? As Littledata grew, the team expanded worldwide. Our offices are located in New York City, London and Cluj-Napoca (Romania), and we have employees and consultants in over 8 different cities. Here in Cluj, the workspace was recently renovated and each room is personalised after each employee’s personal mark. In this way, we all feel comfortable and productive at our workspace. Many times we don’t even use our office desks, preferring to work intently on our sofas and bean bag chairs, or outside in the hammocks. We might have a remote work culture, but we stay constantly connected. Our communication strategy includes Skype for official meetings and Google products (Calendar, Drive, etc) and Slack for fast chatting, collaborating and updating. To keep track of our projects we use Trello cards, where we split the team into different boards, depending on their department. We found that it’s the best way to connect all our team and not get lost in a messaging abyss despite the different time zones. My first design sprint In order to bring clarity in our roadmap and kickstart new features, we embrace the Design Sprint philosophy. A design sprint is a five-phase framework that helps answer business questions through a fast-paced prototyping and user testing. Understand (review background and user insights) Diverge (brainstorm what’s possible) Converge (rank solutions, pick one) Prototype (create a minimum viable concept) Test (validate with users) Basically, we pick a time and a place where we all gather up every three months and do some Sprint-Planning focused on a specific goal. The process helps to spark innovation and align team members under a shared vision. Through this hyper-focus, we can build better features and launch them faster. I recently joined a Design Sprint that took place in a beautiful villa on the island of Mallorca. In the first day I assisted at a short introduction from our organizer, followed-up by the schedule presentation of our 5 day sprint-design and reviews from my colleagues regarding the last Sprint. Afterwards, we separated into two groups, the product team and the marketing team. I joined the marketing team, and for the next 5 days we worked on new ways to promote Littledata by answering the needs and the common questions our customers have. After we all agreed on the most important topics to cover we split up into three teams of two people each. One team managed a new promotional video, the other took on the app’s features process and the last one worked on a customer onboarding process. I was in the app’s features team - check them out: Littledata’s features. The product team came up with a way to increase engagement in our Shopify app and started to develop an exciting new feature that we’ll be launching next quarter! On the 4th day the product team and the marketing team reunited, presented their work and ideas, and voted on each other’s ideas. The last working day was the prototype day where both teams tested their prototypes with real customers. This was an essential part of the Sprint and definitely worth doing if you’re thinking of running a Design Sprint yourself! The Sprint-Planning was also a great way for catching up with each other and spend quality time with all the team members. Our leisure time was spent in Spain, traveling and engaging in fun activities. Work hard, play hard! We even spotted one of our customer's products, Micro-scooters, in a shop window Palma's old city! Perks In my opinion, one of the biggest perks of working at Littledata is the remote-working hours. A flexible and personalized work schedule gives the employees the opportunity to balance work and personal life very efficiently. Besides, the company offers the benefit of working from home when needed. We can work from a coffee shop, a HubSpot, a park or wherever we feel like it. You can work from anywhere ... just make sure to have a good internet connection. Healthcare is also assured. No need to worry about this topic, because for employees in Romania, Littledata grants personal health insurance through our Groupama collaborators. Wellness is also supported by weekly fruit baskets, tea, coffee and other yummy snacks. Integrating all of these pieces together we create a comfy and positive environment for our employees. Workplace culture (PS we're hiring) Our growing team is opened in hiring new staff members who bring value and personality into Littledata. A strong professional background helpful, but a drive to learn is just as important - get involved and be proactive, we encourage learning in all of our activities. We look for people that are passionate, ambitious and always want to challenge themselves. Another criteria that we are fond of is respect. Our company has a strong policy in respecting its employees. As we are very diverse in culture, we coordinate to celebrate each person's holiday and major life event. And last but not least, we are fun folks. Be serious in your work but have a positive and cheerful attitude. And guess what? We are hiring! We have big plans building some awesome products. So come join us, either as an employee or as a collaborator, to create new features using the latest analytics technology. Check out our open positions here. We’d love to hear your opinion - what do you think a great workplace looks like? Leave a comment below and subscribe to our newsletter for the latest in everything analytics.

From 25th May 2018 Google allowed you to automatically wipe user-level data from the reporting from before a cut-off date, to better comply with GDPR. We made the change for Littledata's account to wipe user-level data after 26 months, and this is what we found when reporting before February 2016. Reports you can still view before the user data removal  Audience metrics Pageviews ✓ Sessions  ✓ Users  X Bounce rate  ✓  Audience dimensions Demographics  X OS / Browser  X Location  X User Type  X  Behaviour Pageviews ✓ Custom events X

Transitioning your physical business online is a good choice in the modern age of digital business. It’s all about the internet and selling online. Customers aren’t shopping in brick and mortar businesses as much as they did years ago, and it’s obvious the trend is going digital. But where should you start? In 2017, over 40% of shoppers in the US shopped online several times per month according to Statistia. That’s a big percentage, and it’s only going up! You need the best tips and tricks to stay competitive if you’re transitioning your physical business online. Here’s a guide to smoothly making your transition from in-person business to online business. Choose the right selling platform Your first step when searching for the perfect way to sell online is finding the right platform. You have two main options: sell on an existing platform or create your own. Examples of existing platforms include Etsy and eBay which already have a customer base. While it’s easier to find new customers on these existing platforms, you also lose some control when selling with them. If you do choose to build your own website, there are a lot of tools for easily integrating selling on your website. Shopify is the most common platform for e-commerce and it’s easy to get started with. It's easy to modify to fit your brand and products, and everything just works, right out of the box. Your customers don’t have a lot of time to search your website for exactly what they’re looking for. The easier your website is to navigate, the more customers you’ll convert! That said, the choice for the best ecommerce platform often comes down to Shopify vs Magento. Find a good merchant account With your selling platform comes your merchant account. This is how you’ll process payments through your website, and it can make or break the user experience. Your merchant account is one of the most important aspects of e-commerce reported ExpertSure. When choosing a merchant account, less is more. One of the biggest problems facing online sellers is abandoned carts. You can cut down on this number of people leaving before entering their credit card info by making it as quick and simple as possible to checkout on your website. If you master these basics of building an online store on a platform like Shopify, your transition to online will be as smooth as possible! Did you know that you can even use the Shopify POS for selling offline as well? Be active on social media - but not overly salesy Now that you’ve chosen the right selling platform, it’s time to take your online presence to social media. Social media is to business today what print ads were to businesses 20 years ago. Social media has a lot of power today. According to WordSteam, over 60% of Americans are active on Facebook! If you want to make a splash with your marketing, you need to be on social media. As an e-commerce business, you might think you should be selling on social media. This isn't’ the case! Instead, focus on building relationships with your audience. Create valuable content that your users actually will want to share, and you’ll convert more users into buyers! As as an online business, social media is your first line of interaction with your audience. Why move your business online? In today's market, everything is online. It’s not enough to have a brick and mortar store. People want to be able to shop 24/7 and without worrying about holidays or store hours. An online business never takes days off. It doesn’t have to hire a store clerk or a cashier. There’s a lot of upfront work when setting up the website, but once you’ve established the right platform it’s smooth sailing as long as you have the right marketing strategy with free analytics tools to make sure you're tracking sales, marketing and e-commerce checkout steps. You might need to outsource your online marketing work, and with a good reason. This free Google AdWords PPC wasted spend calculator tool by Fang Marketing shows just how much of your marketing budget you can waste away by putting it to a bad use. As you transition online, you cannot afford such wasting, so it’s a smart choice to actually find a professional to help you target buyer personas and increase ROI (Return on Investment) for those campaigns. For example, using buyer personas to adjust Facebook Ads is an art...and a science! One more reason is having your stuff out of the office and working online as a way of taking down the overhead costs. Sure, some may decide to still go to a coworking space like Spacious or WeWork, but those costs won’t come near the downtown shop with office space for all employees. Just keep in mind that some cities may observe local holidays and you should make sure to find a strategy to keep your shop open without breaking any labor laws." Succeed in the digital age It’s not enough anymore to just set up your shop online and expect to see growth! E-commerce today is all about listening to users and connecting with your audience online. It’s easier than ever to transition your business online, but once you’re there you need the right strategy to get seen. Follow these tips above to create a strategy that works today and beyond! Have you had a unique experience bring your brick-and-mortar store online? Do you have tips for other old-school stores looking for the best route to ecommere success? Let me know your thoughts in the comments section below.   This is a guest post by Ashley Lipman, outreach manager at Expertsure.

"Is my conversion rate good or bad?" We built Littledata's benchmarking feature to help you say goodbye to guessing games and start automatically benchmarking your site against top performers. Now that our benchmark tool has been around for awhile, we've started to get a sense for which ecommerce sites are using it most effectively. In other words, we've seen how benchmarks can help websites increase revenue - not in theory but in actual practice. Littledata has now helped hundreds of companies understand where their performance is compared with other websites in their niche, using our benchmarking algorithms and clean user interface. But can benchmarks really help you grow sales? I understand if you want to see the data for yourself. One of our long-term customers makes for an ideal case study. Case study - Pufushop Over the course of 2017, we helped Pufushop, a Romanian ecommerce site, understand if their website changes were helping to increase performance - and where they still had work to do. Pufushop is a retailer of baby goods, with a main focus on baby carriers. The products in their store are all premium quality and from top vendors, so comparing them with just any other baby store wouldn't have been relevant. Instead, we compared their ecommerce metrics with specific benchmark segments that were most relevant to their market landscape and business goals. Ecommerce benchmark segments Benchmarking is used to measure and compare the performance of a specific indicator, and it's most useful when you map that data onto your internal KPIs and compare performance against similar sites. Littledata specialises in ecommerce analytics and our benchmark population now includes Google Analytics data from almost 10,000 sites. We break that data into specific categories, such as Marketing, Ecommerce and Speed (site performance), and within each category you can filter by industry, location, website size, and more. Littledata aggregates reliable data from those thousands of high-performing websites so that you can focus on results. In this customer's case, we analysed their website and business model to provide 5 relevant benchmark segments: Romanian websites to compare KPIs across regional market Small SEO websites because 60% of Pufushop's traffic comes from search engines SEO-driven online stores (more generally, to see how they compare) General online shopping websites across the globe, to get a sense for how their funnel compares And a specific revenue per customer category based on shoppers' average basket spend (sites with a similar average order value, no matter the sector) Key metrics Web behaviour is not necessarily consistent across industries. We started Pufushop's analysis by looking at key ecommerce KPIs such as Checkout completion rate, Ecommerce conversion rate and Add-to-cart rate, but we didn't just pull these metrics blindly. Starting with the first month, February 2017, we looked at how other stores with a similar average basket value were performing. This helped our client establish what was working and what could be improved. As we worked with them to make sure everything was tracking correctly (after all, benchmarks are only as useful as your data is accurate), they could also check these benchmarks directly in the Littledata app. Results Now for the first time, both Pufushop's Marketing Director and Senior UX Designer had clarity on which areas of the website could be improved to increase sales. Based on the benchmark data they could see that the main places to improve were: The checkout process (to increase the checkout completion rate) Product pages (to increase the add-to-cart rate) Resolving those two main issues will automatically resolve the e-commerce conversion rate KPI and will indirectly influence the Revenue per customer. Pufushop decided to use Google Optimize in order to improve the checkout completion rate. Using Google Optimize is an easy-to-use, fast and scalable tool in order to A/B-test different experiences on the checkout page. Pufushop conducted a variety of targeted experiments, including: Shortening the checkout process Eliminating unnecessary fields Testing variants of checkout pages Split-testing different product pages Testing a variety of shipping costs After a couple of months of testing, the results were significant: The add-to-cart rate grew from 3.7% to 5.5% The checkout completion rate jumped from 52.8% to 89.7% Now those are some real results! Having a direction as well as a target helped Pufushop's digital team to focus on clear, achievable goals. As they continue to grow, we're glad to have them as a part of the Littledata family. Ready to benchmark your site? If you're in the same place as Pufushop was a year ago, here's a quick guide for how to use ecommerce KPI benchmarks to improve your store performance. Sign up for Littledata's main app or Shopify app Look at the benchmark data and pick an industry and a set of KPIs - the right sectors and segments will help you optimise campaigns Use tools like Hotjar and Littledata's automated reporting to analyse user behaviour around those benchmarks and define a short list of actions you're going to take Use Google Optimize or hire a developer to put those actions into place Monitor how users are interacting with the changes When you have sufficient data to see a clear relationship between those changes and an increase in traffic, revenue or conversions, make those changes permanent and move on to focus on a new set of KPIs Keep in mind that there are situations where the KPIs will show you issues of wrong messaging, for example of a product page or advertisement - technical issues where the change is fairly easy to make. In other cases, you will need to develop a long-term strategy for radical changes to your website, such as altering your checkout process. The online environment is a fast-moving industry, so you need to be agile and ready to change accordingly. Either way, we're here to help you scale with data-driven strategies for sustainable growth. Now stop reading this post and start benchmarking your site!   Note: In order to maintain data-confidentiality, KPI values have been altered in this case study (the results are real, only the benchmarks have been adjusted).

Conversion Optimisation is rarely a one-off job. You know that you should improve your landing page conversion rate, but where should you start? Whatever you decide to optimise to improve conversions, the process will take time and patience - whether you're optimising through design changes, A/B testing, or copywriting. In this post, I cover a range of landing page optimisation strategies, including CTAs and trust signals. There is always room for improvement on the website pages used for campaigns, especially when generic pages are used or visitors are sent to the home page. In an earlier post, we shared some best practices to reduce this friction. And there are multiple elements to test on a landing page, including the headline, images, use of testimonials, offers, and CTA. When optimizing for conversions, never test all those things at the same time because it will be hard to identify what worked, not to mention be very overwhelming. Below are suggestions of items to test that can have a big impact. 1) The right landing page headline Ideally, the headlines on our landing pages have a unique campaign proposition to get people to take the next step. When this is missing or unclear, there is no continuity from the traffic source that leads people to the page and results in the friction referenced above. Test variations on your campaign landing pages headlines as well as subject lines for emails and the titles for posts and articles. Different subject lines or headlines with the same content can have a big impact. 2) Trust signals Address customer concerns with trust signals, whether it is a product guarantee, testimonials, or a privacy policy. If you do not have brand recognition, you need these signals to make people comfortable with you. First trust signal: Use HTTPS Tech-savvy visitors may look for the https before your web address rather than http. As you can see below, the https indicates it is a secure connection, which protects sensitive information that may be submitted. Second trust signal: Justify form fields Give a reason for why you need information on website forms. If you do not have a good reason for requesting information, you should not make it required. It can turn away prospective customers who are not ready to provide that much information. 3) Remove words Look at copy critically. What can be removed from the page without changing the message? 4) Test alignment Test left aligned text and headlines compared to center aligned to see the different in performance. There are a lot of references on this topic but with testing, you can determine what works for your website. If the copy alignment makes it tough to read, visitors will not be around long enough to convert. 5) Use white space Create landing pages that are easy on the eyes with grouped content and white space. If you discovered words that can be removed - as mentioned above - this becomes easier to do as space is created from omitted content. 6) Group by color Group by color to show which things are related to each other on the page. The below dashboard shows items in green to indicate performance above the benchmark. Yellow indicates some room for improvement. There are different tools available to check the color contrast on your landing pages. 7) KISS (Keep It Simple, Stupid) Determining the offer on your landing page should never be difficult for site visitors. People should be able to see what it is within a couple seconds. If they have to read too much to figure out your offer or it is confusing, they may leave. 8) Reduce steps I received an email this week for a company that needs to reduce their steps. It asked me to click to confirm an appointment I made. When I clicked, it brought me to the homepage of the site with a prompt to log in with a username and password I did not remember. I did not look up my login info so I guess the appointment is not confirmed. (I will deal with it later!) Are there steps in your conversion process that can be eliminated? 9) Test CTAs Finally - and perhaps most importantly - you need a clear and measurable CTA. Ideally, your CTA is right next to the offer, rather than in a different section of the page. It can be a barrier if those elements are not close to each other. Note too if the CTA reflects where people are in the funnel. If I am being introduced to a product, I will respond to learn more. If I am ready to make a decision among several options, the CTA might say help me choose. Remember there are big actions and small actions. The macro action of help me choose puts money in the bank, but if that is my only option, I may not take any action since I am need to first learn more. Similarly, you can answer multiple web visitor questions, such as How much does it cost? and Where do I go to try your app?, with a CTA that says simply Start free trial. As you test the CTA on your landing page, and begin to collect performance data, you can learn how the response varies by segments. Search terms from ad campaigns or with site search can also indicate where people are in the funnel. Ok..but does the CTA really matter? Yes, the CTA really matters! I know small tests on a site can make a big difference, there is still the occasional example that blows my mind, like the Obama campaign donation button experiment results. It makes a case for why the choice of language in your CTA and segmenting your audience has an impact on conversions. In this example, the design features for the button were the same for all segments - a rectangular red button with white copy. But notice the difference in response rates based on the segment and copy on the button. Convinced that A/B testing for the small things matters? This test was done with variations in the CTA. The desired action was still a donation. Had they measured only the performance by CTA copy, they would have missed out on useful information about the segments. But had this experiment also included different colors, styles, and font, it would have been difficult to determine what resulted in a difference for each group. When optimizing for conversions, remember there are multiple areas to test but to never test everything at once. Make small incremental changes and continue to optimize based on performance. Littledata’s benchmarks are an easy way to keep track of where to improve, and there’s also a ton of additional content on the Littledata blog about conversions. We encourage you to look critically at areas to improve on your website pages, and then to take action!   Want to know more? Get in touch with Tina’s agency, 360 Internet Strategy, and follow her on LinkedIn.

At the start of 2017 Littledata released its first Shopify app. A year on, here are my observations on the technical challenges we’ve overcome. This week we're at Shopify Unite in Toronto, and it's no surprise that their app ecosystem continues to grow. We chose Shopify as our first platform partner due to their open APIs, quality documentation and enthusiasm from other developers. Much of that has been as expected, but to help all of you looking to build your own Shopify app I’ll share some of our learnings on the hidden challenges. Littledata's Shopify app makes it a one-click process for stores to set up for Enhanced Ecommerce tracking in Google Analytics, and then get actionable insights based on the Google Analytics data. It has to hook into Shopify orders and products, as well and modify the store's theme and process ongoing transactions. 1. Handling re-installs gracefully The great advantage of Shopify’s app store over, say, Magento marketplace, is that any store admin can install and pay for an app with a couple of clicks. The disadvantage is that stores can be as quick to uninstall as install. Store admins may start, realise they don’t have permissions, time or energy to continue and roll back to try again later in the day. Since our app inserts a snippet into the store’s theme layout (see point two below), uninstalling removes the web-hooks we set up but does not remove the inserted snippet. When a store re-installs our app has to work out what state they were in when they uninstalled (audit, test mode or live), whether the script snippet is still there and what settings have been changed in the meantime. It took us a few months to get a handle on all the possible user flows, and we’ve found automated end-to-end tests to really speed up running through the different scenarios. In our Meteor framework we use Chimp [link] to run tests through Selenium on localhost and on our staging server. We've also found it essential to track our own stats of 'installs + activations' (including the date of first install and time to finally uninstall) rather than relying on the Shopify Partner stats of uninstalls and installs, which can hide the detail in between. 2. Working with script tags The other side-effect of making apps easy to install is that you can assume the early-adopter stores who will try your app already have lots of other installs. Shopify recommends using the Script Tag API to handle scripts linked to the app, so that when a store uninstalls your app it also removes any client-side scripts from the store. Unfortunately, in early tests we found the load latency to be unacceptably high: on some stores, only 50% of the page load events were getting fired before the user moved off the page. So plan B was add a snippet to the store theme, and then load this snippet at the top of the <body> element on all the layout templates. This has worked much more predictably, except when theme editors remove the snippet reference without enquiring what the Littledata app does (see our fifth challenge). 3. Charge activation vs authorisation Now a very simple gotcha. In our first month we had around 60 installs at a flat price of $20/month, but apparently no revenue. After investigation we found we had not activated the recurring charges after the store admin had authorised them. Doh! We're still not sure why an app would want to have authorised charges which are not activated -- seems like over-engineering on Shopify's side -- but luckily it was easy to correct without asking for more user permissions. 4. Tracking adds-to-cart The first version of our app tried to run the script when customers got to the ‘/cart’ page of a store. The problem here is that many stores have AJAX or ‘mini’ carts where customers can checkout without every visiting the cart page. We looked to trigger the script before the user got to the cart the page, but this appeared to run too many risks of interfering with the customer actually adding the item. Our final solution has been to poll the Shopify store for the current cart, and see if products have been added (or removed) since we last polled (and stored the previous cart contents in memory). This is somewhat inefficient, as it requires continuous network activity to grab the cart JSON from Shopify, but we’ve reduced the network requests to one every 4 seconds – judging that customers are very unlikely to add a product and checkout in less than 4 seconds. This cart polling has proved more reliable across different store templates. 5. Integrating with other Shopify apps I mentioned that early-adopter stores tend to have lots of other apps: and those apps have loyal customers who push to make Littledata's app to work their chosen app (not just vanilla Shopify). The challenge is that most of these app development companies run a very Agile process, constantly changing how their app works (hopefully to improve the experience for store owners). An integration that worked a few months ago may no longer work. We've found the best solution to be open developer-to-developer communications, via a Slack guest channel. Having the developers implementing the features on each side talk to each other really cuts down the delays caused by a well-meaning project manager slightly misinterpreting the requirement. 6. Handling ongoing updates As tested improved client-side tracking scripts, we needed to update the script in the store theme (see point 2 above). This creates a small risk for the store, as there is no UAT or test environment for most stores to check before going live with the new script. The store theme may also get edited, creating new layout templates where the Littledata snippet is not loaded. In the first version of our app we tried to update and re-insert the latest Littledata snippet automatically on a weekly cycle. However, once we reached hundreds of active installs this became unmanageable and also opaque for the store admins. In the latest version we now allow store admins to UPGRADE to the latest script, and then we check all the correct Google Analytics events are being fired afterwards. Giving the end user control of updates seems a better way of maintaining trust in our brand and also removing risk: if the update goes wrong, it’s quicker for us to alert the store owner on how to fix. Conclusion I’m still sure we made the right choice with Shopify as a platform, as their APIs, partner support and commercial traction are all number one in the ecommerce world. But I hope that by sharing some of the hidden challenges in developing Shopify integrations, we can all build better apps for the community. Have you built something for the Shopify app store? Are there development problems you’ve encountered which I haven’t shared here? PS. Are you a developer interested in joining an innovative analytics company? We're hiring in multiple locations!

When the GDPR regulation comes into effect later this month, it will impact all websites trading with EU citizens. That means any ecommerce site with customers in Europe! Is your Shopify store ready to comply? We recently updated our Shopify app (since release 7.8) to help Shopify stores which use Google Analytics comply with GDPR. In addition to automatic fixes to help your store comply, we include recommendations for how to update your site content (such as Terms and Conditions), and how to deal with the new 'two year rule'. If you're running a Shopify store, the time to act is now. Automatic fixes with our Shopify app The first two steps are done automatically when you install our GDPR-ready Shopify app. If you're already using Littledata's Shopify app, these two fixes can be applied when you upgrade to our latest tracking script (version 3.2). Here's what they address. 1. Anonymise customer IP addresses The IP address of your website visitor is considered personal information under GDPR, and to remove any risk that this is sent to Google’s servers in the USA, our script scrambles the last few digits of the IP address. Google already promises not to store the IP address, so this step is an extra level of safety. This slightly reduces the accuracy of tracking which city your visitor came from -- but we believe that this is a small price to pay for ensuring anonymity. 2. Filter personal emails and ZIP/postcodes from pageviews Many sites accidentally send personal data in the page URLs or titles tracked by Google Analytics. For example, apps with their own checkout often send the user email as a URL parameter like ‘/url?email=myname@gmail.com’. Our script now filters that personal data out at source, so the page path you’ll see in Google Analytics is ‘/url?email=REMOVED’. Additional manual steps There are two additional manual steps to ensure that Google Analytics for your Shopify store is GDPR-compliant. 3. Update your terms and conditions You need to update your website T&Cs to ensure users are aware of the Google Analytics Advertising Features that our Shopify app activates and Google uses to identify user demographics, such as gender and interests. We are not lawyers, but we suggest using something similar to these sentences to describe what data is collected, how you (and we) use the data, and how how users can opt out: Our site uses Google Analytics Advertising Features to deduce your gender, age group and interests based on other types of websites you have visited. We use this in aggregate to understand which demographics engage with areas of our website. You can opt out with Google's browser add-on. 4. Remove user-specific information after 2 years You should also change the data retention period for your Google Analytics web property, so that Google removes all user-specific information from their database after 2 years. To make this change, logging to your GA account and go to the Settings cog, and then Property > Tracking info > Data Retention. Use the 'data retention' drop-down menu to select to keep user data for 26 months, and mark 'reset on new activity' to ON. This means that after 26 months, if the user has not come back to your website, any user cookie will be deleted. We think this sensible to comply with the Right to Erasure without making any practical limits to your analysis. Right to Erasure feature coming soon! We're also working on a feature to help websites comply with the Right to Erasure or Right to be Forgotten. Here's a summary of that aspect of the regulation, from the summary of key changes at EUGDPR.org. Right to be Forgotten Also known as Data Erasure, the right to be forgotten entitles the data subject to have the data controller erase his/her personal data, cease further dissemination of the data, and potentially have third parties halt processing of the data. The conditions for erasure, as outlined in article 17, include the data no longer being relevant to original purposes for processing, or a data subject's withdrawing consent. It should also be noted that this right requires controllers to compare the subjects' rights to "the public interest in the availability of the data" when considering such requests. Littledata's Right to Erasure feature will ensure that when you delete a customer from your Shopify admin interface, any references to that customer are deleted from Google Analytics. This won’t affect aggregate reporting, such as number of web sessions or transactions. When do GDPR regulations take effect? The official enforcement date for General Data Protection Regulation (GDPR) is 25 May 2018. At that time any organisations in non-compliance may face heavy fines. In short, we recommend implementing the fixes above ASAP for your Shopify store. All you need is Google Analytics account and our Shopify app. And do check our blog regularly for updates. This is the best place to hear about new Littledata features relating to GDPR, as well as news and analysis about how the regulations affect different types of online businesses, including ecommerce websites, subscription businesses, and membership-based sites such as large charities and nonprofits. Looking for additional support? Contact us about GDPR consulting for analytics setup.

Mobile as a marketing strategy isn’t a new idea to anyone, but the landscape is changing quickly. Back in 2015, Google told us it would be expanding its use of mobile-friendliness as a ranking signal. More recently, in early 2018, they stated that page speed will be a ranking factor for mobile searches middle of this year. As consumers change their behavior on mobile devices, this greatly impacts our strategy as marketers. We now need to be visible on all devices, all the time. What do all these changes mean for marketers? Whether you're a solo AdWords consultant or a member of a digital agency, it's essential to stay on top of consumer trends in a way that is measurable and repeatable. In this post I break down how to develop a data-driven mobile marketing strategy that can easily scale with your online business. Mobile search has changed As consumers, we are research-obsessed. We want to know everything we can about an ecommerce product or service so we can make informed decisions. And as more of us search for seemingly minor things and do so on a small device, advertisers have the opportunity to be present in those micro moments. With an increase of searches on mobile devices (and with mobile searches already having bypassed desktop searches several years ago) we need to be present across the entire consumer experience, making the customer experience a business priority regardless of our brand or business size by providing a seamless experience on every device. Analyzing data with a last-click attribution model misses some of these mobile moments. Assumptions have changed along with search behaviors. In September 2015, Google shared that “near me” or “nearby” searches on Google had grown 2X in the previous year, but the use of that phrase has since declined. People still want results that are near them, but the assumption of today’s searchers is that Google knows the location of the searchers and where to find what was searched because people are using their devices throughout the day. Increase of use for “open now” and “tonight" and “today” travel-related terms indicate people are seeking information on their device. What this means for brands Does your strategy consider these trends and adjust to changes in consumer behavior? A mobile experience leads to a brand impression. People expect a consistent experience every time they interact with a brand. If your site does not deliver and does not deliver quickly, they will quickly leave. Regardless of which channel they used to get to your site, the mobile experience must be as seamless as the desktop experience. What this means for Google AdWords As mobile use continues to increase and consumer behavior changes, we need to better align our PPC efforts and use an attribution model that addresses all steps of the journey. With AdWords, we can align our marketing strategy to mobile use with mobile search ads, mobile display ads and app ads on mobile devices. Each option offers slightly different features. Text ads can display on any device. The primary difference with ads on mobile vs desktop is more ads per page on a desktop and only a couple on a mobile device. Because the first couple ads take up most of the screen on a smartphone, advertisers need to be in the first or second position because that is all that will display. Impatient searchers will not scroll down on their device to your ad in position four. On the Display Network, you can be more creative with ads, adding images and videos to the mix. Although image sizes that work on desktop computers will also work on mobile devices, aim for a smaller size of 320 x 50 when possible, keeping the layout of smaller screen sizes in mind. The third option for mobile ads are appearing on mobile apps, which are part of the Display Network. App promotion ads have a goal of driving downloads. Campaigns with only app promotion ads are eligible for phones and tablets; they are not on desktop computers. Bid adjustments With your AdWords campaigns, set bids on mobile devices that are aligned with your goals. As mentioned above, many will not scroll down the search results page on a smartphone to view ads so may want to increase these bids. This is also important for branding goals; you need to be at the top to be seen. When determining mobile bids based on ROI, identify ROI for desktop versus tablets and devices. That way, your adjustment is based specifically on the mobile value of conversions. Keywords In any AdWords campaign, the key to success is selecting the correct keywords. But you can go a step further and use the keyword tool to also see mobile trends for your selected keyword over the previous year. Use these findings to inform your bidding strategy. A subjective approach is to view your keywords in the eyes of your users. Are the keywords in your campaigns ones that you would type into your mobile device? Although more people use voice recognition to search, there are still those who type in their request. Since typing on a small screen results in typos, you want broad match keywords in your campaign when targeting mobile users. Make sure these keywords include action-oriented terms. Some people may surf their device out of boredom while standing in line, but many search to find information to make a decision. You can capture these early clicks with an attribution model other than last-click. Mobile URLs Google provides an option of using mobile URLs in ads to customize the mobile experience, but if the mobile URL is the same as the Final URL in AdWords, adding it does not impact mobile performance. This is designed for people who have different pages for mobile users. AMP pages An open source initiative, Accelerated Mobile Pages (AMP) solve the issue around slow landing pages to make them faster for mobile. Business that have used them find a much quicker loading time and a more engaging experience. You can also use the AMP version of your website in this option for final URL Bid strategy Take advantage of machine learning with a Smart Bidding strategy in your AdWords campaigns. It considers the multiple signals around device type and browser for auction-time changes, offering more targeting than we could do manually as an AdWords account manager with simple bid adjustments. Monitor device performance with this strategy and prioritize mobile traffic if it does particularly well on devices. Attribution models In all AdWords campaigns, regardless of device, many advertisers use the last-click attribution model, which is not ideal for any campaign, including those targeting mobile. It gives all the credit for a conversion to the last touchpoint - the last click - which misses out on how other interactions influenced the decision to convert. If you have enough data in your account, utilize the Data-Driven Attribution Model. If it is not available to you, consider one of the other options besides last-click attribution. The right reporting for mobile marketing Before you target mobile users with advertising, check first that your site performs well on mobile devices if you do not plan to have a mobile specific URL. Start with a quick test for mobile speed to see if you are at risk of losing traffic. Next do a quick SEO check of your site which is based on Google’s guidelines, which is also relevant to paid traffic. For all your campaigns, not just AdWords, you need to consider metrics such as sessions by device type for general site behavior and conversions once a campaign is running for a while. To minimize manual work for reporting and analysis, use a Littledata report pack which pulls in data from Google Analytics to offer automated reporting on customer touch points, providing data you need without the manual labor. And remember your mobile users are on the go, so any advertising needs to cater to them in the moment!   Want to know more? Get in touch with Tina's agency, 360 Internet Strategy, and follow her on LinkedIn.

Ecommerce blogs were once full of the stories of retailers who had built a thriving ecommerce business sitting on a beach in Thailand while doing as little work as possible. Their business model wasn’t complex: they bought cheap goods from suppliers in developing nations, dropshipped them to US and European consumers with a substantial markup, and lived off the profit. If you’re unusually smart and lucky, it’s still possible to find success walking this path, and you will have little trouble finding ecommerce bloggers happy to sell you the secret to their success (and a large dose of snake oil to wash it down with). But for today’s hopeful new ecommerce merchant, that path doesn’t lead anywhere worth going. As the ecommerce market matured, the low-hanging fruit was picked. In 2017, the most successful small ecommerce retailers are focused on niches they understand well and can build a rapport with. The suppliers relied on by the dropshippers of old got wise. They don’t need small ecommerce merchants to act as the middle-man when it’s just as easy to sell online themselves. There are suppliers who don’t want to be involved in the retail end of the business, but those are generally wholesalers who only sell in quantities that smaller retailers can’t afford. As Commerce Notebook’s Brian Krogsgard puts it: Yesterday’s dropshipping gold rush is today’s dropshipping myth factory. You should be prepared for the realities of dropshipping today in a highly competitive environment, and know that it’s not as easy as some of the stories you’ve heard. Plus, if all your store does is attempt to replicate a tiny subset of Amazon, you’re onto a losing proposition. You can’t beat Amazon at its own game. And yet, small ecommerce merchants continue to thrive. How? By doing what the Everything Store cannot: providing excellent service to a niche market whose needs they understand. I’ve seen dozens of smaller ecommerce businesses flourish by focusing with single-minded determination on a niche audience. Why niche ecommerce works Niche ecommerce works because it’s all-encompassing. Every aspect of these sites fits their particular specialism, including the passions of the target audience. When building user personas for your site, the better you know your audience, the more effective those personas will be when running PPC campaigns, improving SEO and optimising product listings! Branding, communication, product, design, service: everything is calculated to appeal to a specific and clearly identified group of people. Groups that are large and diverse enough to be worth selling to while possessing a sliver of a common identity. One of my favorite examples of this phenomenon is Dolls Kill, a fashion retailer that sidesteps the norms of the fashion industry to appeal to a clearly articulated individualism. The online store calls for shoppers to ‘navigate through the site and unleash your inner riot girl’, and they even have a brick-and-mortar pop-up shop in San Francisco right now. Towards the more mainstream end of the spectrum, Grovemade manufactures and sells wooden furniture and other products. Its branding focuses on design, craftsmanship, and the quality of its materials, with content that tells the story of each product’s genesis, from concept, to design, to manufacture. Although different in tone, audience, and product, these retailers are similar in one way: each understands the values, lifestyles, and needs of a niche market. They unapologetically sell products and build a brand that appeals to that audience. Their customers get the products they desire, but more than that, they buy from a retailer that projects an authentic image in-line with their ideal identity. What’s next for niche ecommerce? The future of ecommerce might be in a combination of these worlds, the old and the new, the big and the small. On one hand we have niche sites that combine next-gen dropshipping with the power of a platform like Shopify, WooCommerce or Magento that make it easy to scale -- as long as you choose the best reporting tools to understand revenue and customers. Littledata’s ecommerce analytics app is particularly useful for Shopify and Magento stores that want to find the right buyer personas to sell to, and to connect that marketing directly to revenue. On the other we have larger stores like MADE.com and Figleaves in the UK. These online stores are now household names, but they became that way by building best-in-class customer support teams and online customer communities with specialised, personalised tools. Two standout examples are MADE’s Unboxed customer community, where shoppers share design pics, and Figleaves’ My Perfect Fit tool, where shoppers can find their perfect lingerie fit. MADE’s story is especially worth noting because they created a niche based on the story of how their business operates, cutting out the middleman and selling directly from designers to consumers. Once they found this niche, they scaled using data-driven decisions that lead to radical increases in yearly revenue. That’s the deal with niche selling: no two stores are ever the same, but your chances for success increase many fold when you use proven tools for hosting, design and tracking -- and create ways for your customer community to share inspiration while at the same time discovering new products and trends. Niche ecommerce is a powerful force, and anyone entering the ecommerce market in 2018 should pay heed to that power.   About the author: Graeme Caldwell works as an inbound marketer for Nexcess, a leading provider of Magento and WordPress hosting. Follow Nexcess on Twitter at @nexcess, Like them on Facebook and check out their tech/hosting blog!

Have you ever been browsing the Shopify app store and wished that you could hear directly from founders and app developers about how their products work? Our new free webinar lets you do exactly that! We're dedicated to providing free learning tools for Shopify stores. In the webinar recording below, you'll hear directly from our CEO and Product Director about how the Littledata reporting app works for Shopify sites on the growth path. Interested in automating your Google Analytics reporting? Great. Confused about how to connect your marketing campaigns to checkout steps and buying behaviour? No problem - we've got you covered. Problems are our business :) Google Analytics made easy for Shopify stores Join Edward Upton to get the lowdown on optimising Google Analytics for Shopify. Put on your thinking caps and get ready for Shopify Reporting 101. In the recorded webinar, Ed gives a product overview and covers a range of FAQs: Common issues with Shopify's native reporting How to get accurate data across the customer life cycle with Google Analytics Who uses Littledata How our automated reporting works The connection between marketing and revenue Our live webinars are designed for ecommerce sites, marketing agencies and everyone in between. We adapt the content based on questions from participants, so please don't hesitate to reach out with questions and suggestions. Ready for smarter growth? Sign up for a free trial of our Shopify reporting app today! The trials extend to all plans, so you can fix your analytics and fully test our feature set. PS. If you're looking for info on our Shopify app integration partners, check out these posts on ReCharge and Refersion.

Facebook isn't just a social platform anymore. Even though the vast majority of users come to Facebook to keep up to date with news from friends, advertisers are finding in Facebook a real revenue stream and a platform to mine for more accurate data about their ideal customers. Around this time last year, I was struggling to use Google Analytics APIs and Google Sheets to identify user profiles for one of my top clients. This process was both tedious and time-consuming, but there was no alternative to doing it manually. I was basically making user personas by hand, and once I had established this user profile service, other customers began requesting it. By presenting it to them in my portfolio I found out just how little most companies actually knew about their user profiles and the invaluable data they provide. From a marketing perspective, most companies can’t afford not to know this information. These personas can dramatically improve ad performance because they’re based on accurate, useful consumer data. Littledata is committed to automating the most time-consuming parts of your day, so we started work on a Buyer Personas algorithm. The resulting Buyer Personas feature shows you which type of customer, on which type of marketing channel, is most likely to convert -- so you can spend smarter, not just more, on Facebook ad campaigns. Here's how to use those personas to get higher ROI on Facebook. Why it can be difficult to improve Facebook ad performance The first question you ask yourself when setting up a new ad campaign is: Who is the target audience? It seems simple, but companies often struggle to come up with an answer. I faced the same problem when I was working with Pufushop and was asked to help them set up a new Facebook ad campaign. I've set up many campaigns on Facebook, but usually the website has had a target audience in mind or the site had installed a Facebook Pixel so long ago that I could have found this out from Facebook Analytics. But for this particular project I needed to find the target audience based only on Google Analytics data. If you've read any of my blog posts you know that "feeling" is not a metric for me. We all know that Facebook and Google Analytics have different ways to define demographics and interests. And that’s okay, sometimes it’s even beneficial. On one side we have Facebook's audience definition, which is sourced from how users self-identify in their profiles and also what content they interact with. On the other hand, we have the Google Analytics audience definition, which is based on presumptions about user behaviour and less rooted in user-generated data. I created the Buyer Personas profile below directly in the Littledata app. Our algorithms generate accurate personas based on your conversion goals and ecommerce setup, broken down by specific marketing channel (in this case, Facebook ads). Using our Buyer Personas feature I was able to find out the demographics and interests of Pufushop buyers -- in under 3 minutes. That persona is the result of tens of automated permutations. Note that this sample website has relatively low volumes, so four user characteristics stand out. For higher-volume sites, more categories appear automatically. Creating effective Facebook Ads from Buyer Personas Once I had the required data, I was ready to start my campaign. Here is a step-by-step guide on how you can set up a Facebook ad campaign based on your Buyer Personas. Go to your Ads Manager in Facebook and click on "Create" to start a new campaign In my case, I used a catalog sale because the campaign was promoting some items that were sold out and all of my products were part of a Collection and had the same target audience. Once I've chosen the catalog for the products and added the campaign name, I can click "Continue" and move on to the next step. Define the Ad set and the audience I found out using Littledata's Buyer Personas that my highest conversion rate is with users from Oradea, who are bargain-hunting females aged 21 to 30, have their browser set up in Romanian, and like to shop on Monday evenings. So I will set up that exact same audience for this ad set. Using all this insight as well as my specific need to present a 5-day sale with a minimal budget, I've successfully set up an audience that should convert at a higher rate. I click ‘Continue’ and on the next screen I add the creatives for the advertisement (image and text) and then, just like that, I’m done. To top it all off, this discovery and set up was done in less than an hour! The many uses of Buyer Personas As you get to know Buyer Personas, you can also use them to: Create new campaigns when you're running on a low budget Narrow down your audience based on specific factors Reduce the frequency of your ads by choosing the best hour to deliver them Create a better re-marketing strategy by knowing when your abandoned carts are more likely to be converted into purchases Run territorial marketing campaigns, taking into consideration the interest and potential of each area Plus many more insights and discoveries to dramatically improve your conversion rate (doing something unique? Let us know!) At first glance a buyer persona like the sample above may seem to be only "four lines in a table," but if you look beyond the text you’ll start to really understand how users from a specific category interact with your website. And once you use your Buyer Personas to adjust and customize your Facebook ads, you'll come to the same conclusion I did: "This is so obvious, how did I miss it?" Facebook campaign reporting in Littledata If you're advertising on Facebook and want to see how your Facebook efforts are paying out, check out Littledata's Social traffic pack. The pack pulls from your Google Analytics data to create automated reports on social traffic and top-performing campaigns. Included in the pack are reports that will show you landing pages for untagged traffic from social networks, an overview of traffic from social media sources, and top campaigns from social networks that help you monitor your campaigns, enabling you to track how your traffic is being split between social channels. We've also recently launched a Facebook cost import feature (more details coming soon). The feature links your Facebook data with Google Analytics so that you can ensure accurate tracking of your Facebook Ads spend -- yet another way that Littledata helps you make informed, data-driven decisions. How are you using Buyer Personas and Facebook Ads? Leave a comment below! The buyer personas data in this blog post has been modified for illustrative purposes.

Today I'm excited to be participating in the Innovation Meets Fashion event in Lugano, Switzerland. As an increasing amount of luxury and fashion retail moves online, high-end brands are finding it complicated to track the complete customer journey. In many cases, difficulties in tracking customers through to eventual purchase are holding back investment in the digital experience and online marketing. But it doesn't have to be this way. We've found a straightforward correlation in ecommerce between the average ticket price of the item being purchased and the number of web pages or sessions before that purchase is made. Simply put, customers spend longer considering big ticket items than they do with smaller ticket items and impulse purchases. Luxury retail involves many touch points with the brand across your websites, social sites and physical stores. The problem is that the longer than online customer journey, the harder it is to get consistent data on which top-of-funnel experiences are leading to purchasing. So first the bad news: since many potential customers browse anonymously, perfect ecommerce tracking across a long online and offline journey is not possible. Tracking browsers based on first-party cookies (such as Google Analytics) will fail when customers use multiple devices, clear their cookies or browse in-app (such as from Facebook). Yet there are three ways we have seen retailers selling high value items increase the reliability of their online behavioural data. 1. Track online shopping behaviour in detail Understanding whether customers browse certain products, view the detail of product variants and even add-to-cart is a good proxy for seeing which campaigns eventually convert. Does your brand have a good understanding of how each marketing channel influences browsing behaviour, after the landing page but before the checkout? 2. Offer a good reason to get customers to login before buying VIP offers, registering for events and discounts all offer a good way of getting customers to login from different devices. With the correct analytics setup, this login information can be used (without infringing the users’ privacy) to link together different interactions they make across multiple devices 3. Make the most of your email list Even without having a login before purchase, customers clicking through links in a marketing email can allow the same stitching together of sessions. This means that if a customer visits a link from their mobile device, and on another week from their home laptop, these two devices can be linked as belonging to the same email – and therefore the same person. Luxury online retail involves a complex journey. Littledata is here to make your tracking and reporting both easy and accurate. Sign up today to get started with our complete analytics suite, and feel free to reach out to our Google Analytics consultants with questions about best practices for luxury ecommerce. Your success is our success!

Team invites are here! It's now easier than ever to collaborate with team members in your Littledata account. In the new digital landscape, collaboration is the mother of invention. Our new Team feature lets you easily manage additional users for your Littledata account, so that everybody on your home team - or on a particular marketing or ecommerce project - can view smart metrics and reports for your site. What's new All Littledata accounts now include team functionality. You can invite and manage team members from your Littledata admin. Here's what you can do with Team members in Littledata: Invite new team members Manage current members Respond to requests to join your team From simply sharing reports to collaborating on complex analytics projects, team invites are a straightforward way to share information and hone down on accurate data, whether you're currently in the data setup phase or focusing on making and understanding business decisions based on that data stream. Adding team members to your account helps to ensure that your colleagues can take advantage of the automated reporting you set up in Littledata to get a clear view of your online business performance. And it doesn't stop there. Team members have access to all of the features in your Littledata plan, so you can collaborate on projects such as setting up accurate tracking, benchmarking your site, and running data-driven campaigns based on buyer personas. Note that while you can have multiple team members, there can only be one account owner for each Littledata subscription -- and only the owner can use the app to make changes in GA. Team members can view audits and reports but cannot make changes to the connected Google Analytics property using the Littledata app. We automatically limit permissions in this way to ensure that the account owner has oversight on any changes to tracking and reporting. Benefits for users, partners and agencies Team invites aren't just for your core ecommerce team. They can be used to enhance collaboration and ensure accurate reporting on any number of projects. The benefits extend to every type of Littledata user: General users can collaborate with both internal teams and external consultants such as PPC agencies Agencies can manage customer accounts internally (as an owner) or externally (as a team member) Partners can access client website data in one streamlined tool, including benchmarks, and find ways to optimise custom report packs based on client needs Team owners can always remove member permissions at a later date, so the Team feature is ideal for growing ecommerce sites that want to control who has access to their Google Analytics data when they change agencies or move on to a different project. Your Littledata team might be composed of members from a variety of teams in your office, and that's okay. In fact, it's encouraged. Sometimes your marketing department needs a good way to collaborate with your data team, your online merchandising department or your ecommerce site developers. As Littledata offers ways to both fix your tracking and get more relevant reporting, our app often brings new teams together to make smarter decisions. Early adopters of our Team functionality have found it particularly useful for expanding the range of reports they use in Littledata. In addition to finding ways to further enhance custom dashboards and reports, sometimes a team member will notice a particularly relevant report pack that had previously been overlooked, and the metrics in that pack will end up making the biggest difference to your online revenue. How to invite new team members and manage invitations To manage team members, login to your Littledata account and go to Settings > Members. You can access the Settings menu by clicking on the gear icon on the upper right, and you'll find Members in menu bar on the left. From the Members page, you can send new invitations, manage sent invitations, and respond to requests to join your team. In addition to invites, users can request to join an existing team. When new users sign up for Littledata or current users add a new site/view to their account, they can search for your site and request to join your team. When someone requests to join your team, you'll receive a notification at your registered email. You can either accept or remove their request. Wondering how to join a current Littledata team? You can request to join an existing team when you sign up using your Google account or a supported social login (currently Facebook and Twitter). Scalability Team member functionality is the logical next step in helping to support sustainable business growth for our customers. Last year we switched to transaction-based pricing because we are dedicated to providing apps and managed services that easily scale with any online business, whether you're doing $5,000 or $250,000 per month in sales when you first get going with Littledata. Our pricing is per web property (you need a separate account for each particular Google Analytics view or data source), not per user. Standard and higher plans include unlimited team members, but if you need a unique team setup or multi-site dashboard, let us know. We hope you love the new Team feature as much as our team does here at Littledata!

Buyer personas. User personas. PPC personas. Are these just marketing buzzwords? Do they mean months of planning before you can even begin your PPC campaigns? The answer to both questions is a straightforward no. 'User personas' don't require months of extra work to build, and they aren't just another marketing buzzword. If you follow my suggestions below, you can quickly create personas to help target and optimise your next PPC campaign. Start with brainstorming Brainstorming should come at the very beginning of your process. What do you already know about your audience? This can be old-school brainstorming with a pen and paper, or a more business-like approach with a whiteboard in your conference room. If you do this with a team, hand out some Post-it notes for jotting down ideas. The Post-it notes approach makes it very easy to move your notes around and begin grouping by identified themes. Quickly create simple personas The key here is simplicity.  There is great content out there on creating more complex personas, by using a resource such as Hubspot’s 100 Questions. For the simple approach, I look at three areas to kick things off. Describe the audience by their demographics: gender, location, age, parental status, income, etc.. Identify the biggest problems they want to solve. If you are unsure how to define this one, start with 'I want' or 'I need' to put yourself in the position of your audience. For example, as a marketer, my ongoing problems include automating mundane tasks and creating simple personas. Ask how your offering specifically solves the identified problems. When it comes to creating personas, Littledata can help by automatically building personas with existing Google Analytics data. With this information, create a very short narrative with the key descriptors and needs of each identified persona. Find the perfect image Do this after you finish the above steps. You do not want to start with image and then create a persona to look like that person. (There’s some great discussion on that on UX Mastery). One step I often recommend is to look at images of people in existing marketing materials to see if they represent the personas created from this exercise. Digital tools to help you create user personas After you do some brainstorming and jot down initial notes about personas, you can next turn to digital tools to help you. MakeMyPersona.com is aptly named because it helps you do just that.  It is a way to organize some of the thoughts that came up in the earlier steps. Those in the B2B market can try Up Close & Persona. It meets my criteria of simple and takes you through questions that help you think of appropriate messaging for your audience. However, some of the questions have only a few preset answers so I would not start this tool. It could box you into narrow thinking. Littledata’s buyer personas feature helps you identify the website visitors that are most likely to convert.  We know that Google Analytics does not do all the work for us, but there is a lot of data available for analysis. Compare these findings to what was uncovered during brainstorming. Develop your PPC campaign around the user persona Take your 'I want' and 'I need' statements and pull out some of those phrases as keywords. When it comes to choosing PPC keywords, stay away from your corporate lingo, and instead think about how your prospects talk about you. These keywords will help you match your message to each persona. Is your persona trendy with a sense of humor? Maybe you will get a little snarky with your messaging.  Is the need something serious, such as a health issue? Stay away from the snark and instead be really clear about your benefits. Create an offer that matches the persona. An intellectual, highly educated executive may take the time to download and read your white paper. A busy single parent with four young kids wants a solution. And wants it quickly. Segment personas by channel. I like Littledata's buyer personas because they let you see how to adjust your ad spend based on specific marketing channels beyond Paid Search. PPC is not the only place to reach your audience. You will - hopefully - have a multi-channel approach and need to understand Organic Search, Email, Referral, and Social in addition to PPC. Unless you have an unlimited marketing budget, you may not be able to reach every persona and on every channel. One consideration for your PPC spend is to focus on the longer tail or brand name keywords. This is definitely a smaller audience, but it will capture people further down the funnel who are more likely to buy. What to do next I hope that you find this simplified approach to developing personas useful in kicking of the next stage of your digital marketing! My goal is to provide steps for you to take action and not get bogged down by the prospect of developing personas before kicking off a campaign. You may want to refine this approach over time, but the important thing is to get started now. Even with the best planning, you may find some surprises in your campaigns after you get started which is why I always watch new campaigns closely, especially in those first few days. Monitor your performance by channels in Google Analytics and be prepared to adjust your ad spend. Your ROI will vary by offer and user persona, so focus on actionable analytics from this wealth of data to make the right decisions for your particular business.   Want to know more? Get in touch with Tina's agency, 360 Internet Strategy, and follow her on LinkedIn.

For most Shopify stores, the Littledata - Google Analytics reporting app automatically adds our tracking script to your shop's template. However, if your store has a custom template/layout, there will be some cases where our app isn't able to do this automatically. Luckily it's super-easy to resolve this issue by adding a code snippet yourself. Once you add the code, your store will automatically call our tracking script at just the right time. That way we can help you get accurate data across the customer life cycle. In this quick how-to guide I'll show you how to add the code snippet. How to add the snippet to your shop's code 1. Edit the code in your Shopify admin Go to your Shopify Admin > Online Store > Themes > Actions > Edit code. 2. Copy the snippet Copy the following snippet. (Even though our script has already been added to your store, it still needs to be called for each Layout.) [code language="javascript"] <!-- Start of Littledata - Fix Google Analytics Script--> {% include 'LittledataLayer' %} <!-- End of Littledata - Fix Google Analytics Script --> [/code] 3. Paste the snippet Now paste the snippet in every one of your store's layouts, just under the <body> tag. In the example below, we'll paste the snippet in row 77. 4. Save and repeat After you paste the code, click Save and repeat the steps above for each layout. Note that you will need to make this change for each layout when you are installing our app, but also when you create another layout for a new campaign. Anytime you create a new layout, just follow the steps above to add the right code snippet. That's it! You're now all set to get a consistent stream of accurate data and intelligent insights for your Shopify store. Remember that it takes about a week for the new analytics setup to start producing useful reports. If you've followed these steps but still have questions, please don't hesitate to get in touch with our team. We <3 code. And we're here to deal with it so you don't have to :)

We often receive questions about what customers get when they upgrade from the free version of Google Analytics to Google Analytics 360. The quick answer is that you get a lot - the possibilities are literally endless - as long as you're a big, data-driven company willing to put energy into customer engagement and marketing. Google emphasises that their enterprise analytics are designed to help large companies, like major ecommerce sites, create better customer experiences. But what does that mean in practice? There are a lot of details to understand if you're thinking of transitioning to the big paid version of Google Analytics. The main differences lie in how each product deals with the volume of data and integrations that they have available by default. I've broken those differences down into three categories: Data Collection, Data Sampling and Data Sources. Data collection In short, Google Analytics 360 allows for a faster, smarter, larger data collection. With unlimited hits per month and up to 200 custom dimensions per web property. Features Google Analytics (free) 360 Suite (paid) Hits per Month up to 10M unlimited Custom Dimensions/Metrics 20 Per Property 200 Per Property Calculated Metrics 5 Per View 50 Per View Properties per Account 50 50+ Views per Property 25 25+ Roll-Up Properties No Yes Data Freshness 24 – 48 hours 4 Hours   Data sampling and limits As your web traffic grows, Analytics 360 lets you get more out of both sampled and unsampled data sets. Compared with the standard version of GA, you get better reporting on large amounts of data. Understanding how data is sampled in Google Analytics will help you scale the smart way. Features Google Analytics (free) 360 Suite (paid) Report Row Limit per Day Yes Yes Standard Reports Pre-Aggregated 50K 75K Sampling in Ad-Hoc Reports 500K Sessions per Property 100M Sessions per Property Custom Tables No 100 Custom Table Report Row Limit per Day No 1M Rows Unsampled Reports No Yes Unsampled Report Row Limit No 3M (for download) Data sources The 360 Suite makes it especially easy to pull in data from a wide range of advertising platforms and sources, including non-Google products like Salesforce. For some of our enterprise customers, especially large ecommerce sites with a focus on PPC lead gen and retargeting, the ability to seamlessly integrate with DoubleClick is itself enough to make their 360-buy worthwhile! Features Google Analytics (free) 360 Suite (paid) AdWords Yes Yes AdSense Yes Yes DoubleClick Campaign Manager No Yes DoubleClick Bid Manager No Yes DoubleClick For Publishers No Yes Custom Data Sources Yes Yes Query-Time Data Import No Yes Salesforce No Yes BigQuery No Yes   Additional perks (GTM 360, beta testing) In addition to the above benefits, being able to connect Google Analytics to other Google 360 Solutions like Google Optimize 360 and Google Tag Manager 360 is a big plus. As an added perk, Analytics 360 clients often get early access to beta programs for testing and product feedback -- getting directly involved with product development to suit their needs -- plus first-hand support from Google. Google 360 can be purchased directly from Google or through a sales partner. We don't currently sell the 360 Suite ourselves, but we’ve been a certified Google Analytics Service Partner since 2015, including Google Tag Manager and Google Optimize certification, and have extensive experience with custom tagging and reporting. Plus, we built the Littledata app around those analytics best-practices. Our larger consulting clients get the most benefits out of our enterprise plans, which include automated analytics audits, unlimited access to app features, custom setup and reporting, and a dedicated account manager to help ensure deep, accurate tracking. Whether or not you've already upgraded to Google Analytics 360, we highly recommend getting in touch to make sure you're able to use this powerful tool to its full potential!

The whole purpose of having Google Analytics tracking on your site is to find out how your website is performing and to use this data to improve your digital efforts. Yet many businesses miss the mark when it comes to taking action at the level of product listings, despite the fact that this can lead to huge revenue gains! Why do they miss the mark? Two reasons: inaccurate tracking and unclear reporting. The Littledata app helps to fix these issues automatically, providing users with a reliable data stream and automated reporting based on Google Analytics data, but it's still useful to drill down into Google Analytics itself to understand all of the details. In this post I break down how to use Google Analytics to refine merchandising, product promotions and product listings in a way that can have a direct effect on both short-term and long-term revenue for your ecommerce site. For this to work, you'll need to have Enhanced Ecommerce set up on your website. You'll also need some spreadsheet software (Excel, Google Sheets, etc.) so we can play with extracted data and drill down deep. Banners and creatives: getting users to see what we want them to see A full enhanced ecommerce setup will enable you the power to see how much money each of the creatives on your site is bringing you. If your website is like most ecommerce sites, you have several creatives displayed, such as: Homepage carousel Homepage pods Category main banner Choosing which creative should get on your homepage might feel like just a preference, but it doesn't have to be that way. You can use the 'Internal Promotion' menu in Google Analytics (Marketing > Internal Promotions) to make data-driven decisions about your homepage creatives. Imagine an online store that sells scooters and accessories: We have banners for categories like Helmets, Accessories, Mini Micro and Maxi Micro (different sizes of scooters). We have 2 banners on the homepage with these two creatives: Safety (the first one) and Built for Adults (the second one). We want to change one of the creatives on the carousel. Let's analyze what is the best strategy here. The first banner on the carousel was seen 24,404 times. It has a 5.01% click thru rate (CTR) and a £3.90 value per click. The second banner on the carousel was seen 17,109 times. It has a 5.52% CTR a £2.02 value per click. Now we can make a decision. What to discard and what to keep Even though we have a higher CTR on the second banner and this is an indicator that the message is more appealing, the reality is that the revenue that comes with that click is not even half of the revenue we get from a click on the first banner. If you want to make a 100% correct decision here you can analyze the margins on the product promoted by each of the banners. If you have double the margin for the products in the second banner you can get rid of the Safety banner and make the second banner primary. If your margin is the same for both categories then the best decision here is to replace the second banner with the first one. How to populate the carousel We already decided to keep the first banner, but now we need a replacement for the second one. So we need to find a creative in the website that had performed at least the same as the second banner. Based on the example above if we search by CTR higher than 5.52% we can see that we have a banner for Maxi Micro with 20% CTR and a value per click of £5.32. The action here is to replace the second slot of the carousel with this creative. After 1-2 weeks we can retake this process all over again and we may decide to reverse the creatives (Banner 1 will be Banner 2 and Banner 2 will be Banner 1 in the carousel). This is not a one-time job. The analysis should be made every time you add a new creative or make a new promotion.--or even as a weekly task. Many Littledata clients run this type of analysis on a regular basis, whether or not they've launched a new promotion, to make sure they are optimizing sales and conversions. You should pay attention to the average click thru rate (CTR) based on creatives category, and also you should know what is your standard deviation for each category so that you can quickly spot which are over- or under-performing. Based on the example above, the average CTR for a carousel banner on the site is 5.26% and the standard deviation is 0.25%. So I know that if I see a banner that has a CTR less than 5.01%, there is room to improve. As per above for the category pages, we have an average of 10.92% CTR with a standard deviation of 6.28. This means that everything under 4.63% should be replaced ASAP and everything above 17.20% should be promoted. List views: how to arrange products for ultimate engagement One of the best Enhanced Ecommerce features in Google Analytics is the Product List Performance Report (Conversions > Ecommerce > Product List Performance). This report shows you how many views each list gets. Why does this matter? Because if you have a high margin on some products from a specific category, you should find out if that list (category) is being sufficiently promoted on your site. From these reports, we can find out things like: Most viewed categories (sort by Product List Views) The category that has the biggest engagement (sort by Product List CTR) The list that is bringing you the most money per view (Product Revenue divided by Product List Views) Which categories are performing best -- and which are most profitable? Let's say I have three categories in my store: categories 1, 2 and 3. And my margin for products in category 3 is three times the margin for those in category 1. In the report above, we see that we don't have a click thru for Category 2. This could mean: The tracking is not working on that page Users have issues clicking on the products There is no call to action (CTA) on that page So we can assume that Category 2 is not working. Moving forward we should analyze the performance of Category 1 vs Category 3. Views Clicks CTR Revenue Revenue / click Margin at each $1 sold Margin at 1000 clicks Category 1 1,701,660 57,038 3.35% $329,799.67 $5.78 0.23 $1,329.88 Category 3 46,895 3,175 6.77% $23,881.37 $7.52 0.69 $5,189.97 We can see that even though we have a fraction of the views for Category 3, this category is for us almost 3 times more profitable per 1000 clicks. At this point, we should investigate how much marketing we're doing around Category 3 to see if there are options to push harder on this highly profitable category, alongside whatever's already working for promoting Category 1. Order matters The Product List Performance Report can also help us find out how customers progress from viewing a product in a list to clicking through for more information. Let's analyze the data in the above report. The table is sorted by Product List Views for Mobile devices. We know that the alignment for this website is one product under the other and for a product view to be sent the user needs to see it for at least one second. So we can draw these conclusions: Position 2 and 3 are normally visually scanned by users. The fourth product in a list is seen in more detail but has a lower CTR than the second or third product in the list. We know that each page has 10 products so the average Product List CTR rate for page 1 is 1.36% and the standard deviation is 0.42. From this, we can see that position 2 has a good CTR and we need to change the photo and text of the listing to attract more attention -- products placed in the second position in a product listing on this site tend to convert well. Position 4 gets attention but has low performance so we could try changing the photo and title of products in this position in order to increase the CTR. If we are looking at this report as aggregate data then we can conclude that if we want to make a push for particular products, we should place them in position 1 or 4 for maximum visibility, or position 1 or 2 for maximum CTR. How to monetize product list positions We can take this analysis further by examining how list slots relate to product revenue, whether on your site or via affiliate programs. Looking at the report in aggregate and extracting the data, we can give a monetary value to each slot in the product listings. Product List Position Product List Views Product Revenue Revenue/view per slot 1 2,290,505 £183,207.00 £0.08 4 2,279,917 £99,830.00 £0.04 3 2,246,164 £117,096.00 £0.05 2 2,239,943 £157,605.00 £0.07 6 2,062,271 £73,183.00 £0.04 5 2,053,534 £94,889.00 £0.05 8 1,788,080 £58,585.00 £0.03 7 1,775,762 £60,603.00 £0.03 9 1,750,248 £52,366.00 £0.03 10 1,606,599 £50,913.00 £0.03 From the above example, we can see that each of the slots in the listing has a value per view. And the value is decreasing with the position. Using the known margin for a specific product in a list, you can improve your ROI just by positioning it in a slot with a higher CTR based on the model above. Which photos should you show first in a listing? If you offer a product in multiple colors, you should use an image and a default (primary) product selection in the most popular color. But how do you figure that out? Product variants are too often left behind in analysis. The Product Variant field captures the specific variation of a product, e.g., XS, S, M, L for size; or Red, Blue, Green, Black for color. It is an Enhanced Ecommerce feature that can give you powerful insights into your users' searches, interests and preferences. Paying attention to variant performance can have a big effect on shopping behavior and sales. In the example above, we're looking closely at the Product Variant dimension to figure out which color is most popular. We have a product with 4 colors: Black, Grey, Midnight Black and Persian Grey. There isn't enough transaction data to make a decision based on purchases, but we can calculate the most popular variant (in this case, the most popular color) based on how often users have added items in each color to their shopping carts (Adds To Cart). For Black, we have a View to Add To Cart rate of 0.6% and for Grey 0.8%. So in this case we should use the main Grey color for advertisements and main photos in listings pages. We might also try using the Persian Grey variant. Note that in this example we can calculate for each product view because we've listed each color as a different product. If you're listing only one product and you show variants on the product page, then you'll need to divide the Adds To Cart for each variant by the total Product List Views. What to do next If you need help with Enhanced Ecommerce reporting, our analysts are ready to come to the rescue. You can either request a consultation or just sign up for a free Google Analytics audit and contact us directly from the app. How are you using Enhanced Ecommerce reports in Google Analytics? Drop us a note below.

https://www.youtube.com/watch?v=SGY013J9QGg So you've got your new sales plan in action and you've set up unique goals in Google Analytics. Are they tracking what you think they're tracking? Are you sure they're giving you reliable data? If you've audited your analytics setup, you might have noticed any number of incorrect audit checks about how you've set up custom events for your Google Analytics (GA) goals. Goals are used to make important business decisions, such as where to focus your design or advertising spend, so it's essential to get accurate data about them. In this quick video we cover common issues with setting up Google Analytics goals, including: Tracking pageviews rather than completed actions Selecting the wrong match type Inconsistent naming when tagging marketing campaigns Filters in your GA view rewriting URLs (so what you see in the browser is different from what you see in GA) Issues with cross-domain tracking In GA, a goal is any type of completed activity on your site or app. GA is a remarkably flexible platform, so you can use it to measure many different types of user behaviour. This could be visitors clicking a subscribe button, completing a purchase, signing up for membership -- known as 'conversion goals' -- or other types of goals such as 'destination goals', when a specific page loads, and 'duration goals', when a user spends over a particular amount of time on a page or set of pages. That all sounds well and good, but trouble comes if you simply set up goals and then trust the data they give you in GA, without double-checking to make sure that data's consistent and reliable. We hope you find the video useful. And don't despair -- even a little extra time spent on your GA setup can yield awesome results. Sign up for the Littledata app to audit your site for free, and let us know if you've experienced other common issues with setting up goals in GA.

Ecommerce companies typically store lots of personally identifiable information (PII), so how can you make compliance easier without compromising analysis? With the deadline for GDPR compliance looming, I wanted to expand on my previous article on GDPR and Google Analytics to focus on ecommerce. Firstly, who does this apply to? GDPR is European Union legislation that applies to any company trading in Europe: so if you sell online and deliver to European Union member countries, the regulations apply to you. It's essential that you understand how your online business is collecting and storing PII. Splitting PII from anonymous data points Your goal should be to maintain two separate data stores: one that contains customer details, from where you can look up what a specific customer bought, and one that contains anonymous data points, from where you can see performance and trends. The data store for the customer details will typically be your ecommerce back-end and/or CRM (see below). This will include name, email, address, purchase history, etc. It will link those with a customer number and orders numbers. If a customer wants the right of access all the relevant details should be in this store. We use Google Analytics as the anonymous data store (although you may have a different ecommerce analytics platform). There you can store data which only refers to the customer record. These are called pseudo-anonymous data points under GDPR: they are only identifiable to a customer if you can link the customer number or order number back to your ecommerce back-end. Pseudo-anonymous data points you can safely send to Google Analytics include: Order number / transaction ID Order value / transaction amount Tax & shipping Product names and quantities Customer number Hashed email address (possibly a more flexible to link back to the customer record) If a customer exercises their right to removal, removing them from the ecommerce back-end will be sufficient. You do not also have to remove them from your Google Analytics, since the order number and customer number now have nothing to refer to. You do still need due process to ensure access to Google Analytics is limited, as in extreme circumstances a combination of dimensions such as products, country / city and browser, could identify the customer. Isn’t it simpler to just have one store? Every extra data store you maintain increases the risk of data breaches and complexity of compliance – so why not just analyse a single customer data store? I can think of three reasons not to do so: Marketing agencies (and other third parties) need access to the ecommerce conversion data, but not the underlying customer data Removing a customer’s order history on request would impact your historic revenue and purchase volumes – not desirable Your CRM / ecommerce platform is not built for large scale analysis: it may lack the tools, speed and integrations needed to get meaningful insights Beware of accidental transfers There are a few danger areas where you may inadvertently be sending PII data to Google Analytics: Customer emails captured in a signup event A customised product name – e.g. ‘engraving for Edward Upton’ Address or name captured in a custom dimension Our PII audit check is a quick, free way to make sure that’s not happening. Multiple stores of customer details GDPR compliance becomes difficult when your customer record is fragmented across multiple data stores. For example, you may have product and order information in your ecommerce database, with further customer contact details in a CRM. The simplest advice is to set up automatic two-way integrations between the data stores, so updating the CRM updates the ecommerce platform and visa-versa. Removing customer records from one system should remove them from the other. If that’s not possible, then you need clear processes to update both systems when customer details change, so you can comply with the right to rectification. Conclusion GDPR compliance need not require changing analytics tools or databases, just a clear process for separating out personally identifiable information – and training for the staff involved in handing that data. I hope this brief overview has been helpful. For further advice on how your ecommerce systems comply, please contact us for a free consultation. Littledata has experience with every major analytics platform and a wide range of custom setups. However, as a number of global companies are concurrently prepping for compliance, we highly recommend that you get in touch sooner rather than later!

Are you following a strategy to increase ecommerce site traffic, or are you shooting in the dark? In this guest post, Courtney McGhee outlines proven ways to get more web visitors. So you’ve created your ecommerce site and you’ve set up your social media profiles. Why isn’t your audience flocking to your site, cash in hand? The truth is, creating your website and social presence is only the first step toward generating traffic. Your strategies on these platforms will ultimately determine the amount of traffic that lands on your pages. You need to invest time, create relationships and sometimes even invest some money if you want to boost your numbers. In this guide, I'll show you proven ways to drive ecommerce site traffic. Step 1: Decide how many daily visitors you need Setting a clear, attainable goal should be the first step if you want to increase your traffic. Marketing strategies can be overwhelming if you don’t first determine what your goal should be. First, decide how much annual revenue you are looking to earn. Let’s look at the example of $350,000. Next, divide your total annual sales by the value of your average order. Let’s say your average order costs $50. This calculation gives you the number of annual orders you will need to reach your sales goal. For our example, that number would be 7000, or about 19 orders each day. Let’s realistically assume that 19 orders per day come from a conversion rate of 2%. That means you will need around 960 daily visitors if you are going to have 19 orders each day. These numbers will show you how much time you need to spend on generating traffic and can help you set attainable and measurable goals. Once you've decided on the amount of traffic you're shooting for, make sure your Google Analytics setup is giving you accurate data about all of your websites (including microsites) and isn't duplicating visitors. You'll also want to set up goals for specific events, such as when a customer adds items to their cart, signs up for your email list or completes a checkout. It's better to set up this tracking early before launching your new strategy--otherwise you won't know whether or not your new strategy worked! Step 2: Start your search engine optimization (SEO) Search engines are (or should be) one of the biggest sources of your traffic. Now, it’s time to milk them for all they’re worth. Search Engine Optimization (SEO) should be a main focus to drive organic traffic to your site. Whether or not you have just launched your ecommerce store, you should make a habit of reviewing each page and product on your site. To do this, you need to start an SEO audit. Enter your URL on an SEO tool like WooRank, and start an Advanced Review. You can add up to three competitors here to take your SEO up a notch. Add keywords you want to track in the Keyword Tool, and choose the location where you want to focus on. In the keyword tool, you will be able to see the volume and rank for each keyword and how you are doing against your competition. There are plenty of free keyword research tools available if you aren’t sure which ones you should be targeting. Now that you have chosen your keywords to use for optimization efforts, you should make sure you are using them in a consistent and natural way. Using them in your title tags, meta descriptions and body content will help you become more visible to your target audience. To really optimize your keyword strategy, I recommend setting up site-search tracking to see what visitors are searching for on your site and also monitoring how keywords convert on your site by adding Search Console to your Google Analytics account before moving onto the next step. Step 3: Craft your content...carefully Even for an ecommerce site, it is essential to have useful, relevant and authoritative content. Of course, it is critical to have product images, but product descriptions will really help you boost your traffic. With product descriptions, you can weave in the keywords you can easily rank for that can also drive conversions. It’s actually easier to rank higher for long tail, localized keywords that will align with your visitors’ search queries. If you are selling garden supplies and you can rank highly for “planter for tomatoes”, the produce descriptions should use “planter for tomatoes”. Include that phrase in the title, as well. The product images need to be clear and representative of the actual product you are selling. Don’t forget to include the alt text with every image you use. This should go without saying, but don’t use images you downloaded from the internet that aren’t pictures of what you are actually selling. Also, you can create content like product reviews or comparisons of different brands and models that are optimized for “planter for tomatoes”. You can experiment with other types of content on social media, like videos, that can help you rank highly on search results. Videos related to the product that can also be embedded on your site is another easy way to incorporate your keywords in your content. Step 4: Tap into social media influencers In terms of brand engagement, Instagram is one of the best platforms. There is a whopping 25% more engagement on Instagram compared to other social media platforms. Also, studies show that nearly 25% of online shoppers are influenced by social media recommendations. In order to tap into the influencer market, you need to find the people who are willing to feature your products to their many followers. Finding those people, though, is easier said than done. A tool like WEBSTA can help you find the most popular Instagram hashtags and accounts. Once you find the influencer with a substantial amount of followers that aligns with your general category, you can contact him or her and ask for your product to be featured. Step 5: Entice visitors with contests Let’s be honest: everyone loves a good freebie. Does your site have a gift that your customers will find worthwhile? Use your social media profiles, your website and your influencers to get the word out that you are having a contest for free goodies. If your potential customers think your gift is valuable, they will share it with their friends and families. The only con to this strategy is attracting people who are only interested in free stuff. These users will likely never convert to customers, so use this option only when it makes sense for your brand. Step 6: Publish user reviews Search Engine Land noted that 88% of shoppers trust reviews they read online. You can encourage your users to leave reviews on your website and social media accounts. Reviews will help you rank higher in search results, and users are more likely to click on your site/social media pages. User reviews ensure fresh, relevant content - a big plus in Google’s eyes. Here are some more stats from Econsultancy on why user reviews are so valuable: Bad reviews improve conversions by 67% 63% of customers are more likely to make a purchase from a website with user reviews Reviews generate an average boost in sales of 18% Step 7: Pay-Per-Click (PPC) advertising At least 43% of ecommerce traffic, on average, comes from Google search (organic). But, more than a quarter of traffic is coming from Google AdWords, according to Wolfgang Digital. So, it’s important to have both your SEO and PPC set up correctly. As mentioned above, during your keyword research find the keyword your audience uses most, like “tomato planters”. This includes the long tail keywords, too, like “best planters for tomatoes”. Now, run a PPC campaign including both keywords. Primary keywords will generate more traffic, while long tail keywords will drive less traffic but higher conversion rates. To increase conversions even more, you can link your AdWords account to your Analytics account, then use Buyer Personas for specific marketing channels to target those users that are more likely to spend money on your site. So, are you ready for real growth? Bringing traffic to your ecommerce sites all starts with setting a clearly-defined goal. You need to know where your existing traffic is coming from, and optimize all of your platforms for your visitors and search engine bots. Incorporating other strategies, when done correctly, will help you bring more eyes to your site. Contests and PPC advertising are great ways to get your product in front of your target audience. I hope this guide helps take your online store to the next level! Courtney McGhee is on the Marketing Team at WooRank, an SEO audit tool that has helped millions of websites with their SEO efforts. A former journalist in North Carolina, Courtney shifted gears and entered the digital marketing world in Brussels, Belgium.

In the ecommerce world, one of the smartest ways to improve ROI for marketing campaigns is to retarget customers who visited your website in the first place. These visitors are already in the market for the types of products that you sell, but how do you pull them back if they've dropped out of the checkout process? The most effective way to grab these customers is to target them based on where they dropped off. Luckily, Google lets you do exactly that: with the right analytics, you can set up retargeting campaigns based on checkout behaviour. At Littledata we've helped online stores in over 50 countries to improve marketing ROI using ecommerce tracking. In this post I share three simple steps you can take to improve your AdWords retargeting based on ecommerce checkout behaviour. 1. Set up accurate product tracking for your store Enhance Ecommerce tracking has been available from Google Analytics for a couple of years now. If you're already using this Google Analytics feature, good for you! Having product data means you can take advantage of this and create Audiences that then can be shared with AdWords (and other platforms). In order to improve AdWords retargeting using checkout steps, you must have checkout tracking and Enhanced Ecommerce enabled in Google Analytics. Then you can follow this checklist to set up accurate product tracking that can be used for Audiences in AdWords. Check out this resource (or share it with your lead developer): Google's Guide to Measuring a Checkout Repeat after me: "The fields must by dynamically populated! This is important!" Clarify where the checkout process starts and ends on your website (and again, if your developer is handling the setup make sure they're clear about each stage in your checkout funnel, including where  the process starts and stops) Set up checkout tracking based on that process Once this data is successfully coming into Google Analytics, you're ready to create Audiences and share them with AdWords At this point, it's important to mention that there are a lot of elements to Enhanced Ecommerce tracking and each part needs to be set up separately. For example, you will not automatically be tracking product categories, listings and details. If you're not sure how to implement the full extent of Enhanced Ecommerce, we're here to help. If you're using the Shopify platform, you're in luck, as our Shopify reporting app's audit feature checks for accurate product and checkout-step tracking, and automatically assists with setting these up for you. The app works directly with the Google Analytics setup for your Shopify store, so you don't have to deal with Shopify's native reporting, which doesn't let you see how users are progressing through the checkout process. 2. Analyse customer behaviour, including checkout steps Shopping cart abandonment is the most frequent complaint we hear from ecommerce marketers. Why does someone add products to their shopping cart and then just abandon it completely? This isn't common in brick-and-mortar stores, so why does it happen so often online? Remember that online shoppers don't want to leave those things behind. They were attracted to those products and have expressed the desire to buy. But with a bad checkout flow, too much information or too little, they'll fly away and leave behind only unloved products with high shipping costs or under-promoted benefits. One of the best Enhanced Ecommerce use cases is the Checkout Behaviour report. This is essentially a Shopping Cart Abandonment report, showing weaknesses in your checkout process and where to invest your time and money to convince users that have added-to-cart to go ahead and complete a purchase. Why is this important and relevant to AdWords? Well, everything in marketing is about perspective. The above report doesn't only show you where you could improve your checkout flow, but also where you've lost customers. 'Lost' is the key word here. If you're losing a significant percentage of customers at the shipping stage of your checkout process, this is an opportunity to improve - and to market those improvements using AdWords. For example, you might look at that report and ask yourself: Are you charging customers too much for shipping? You can't really change that cost for all carts (we know that shipping costs are significant) but you could, for example, offer free shipping to shoppers with items in their cart over some profitability margin. Retargeting those users in Google AdWords is an effective way to show them that you're ready to reward them for making large purchases from your online store. Are you limiting yourself to too few territories? Put your analysts to work to find out where customers that leave the purchase flow want their goods to be delivered. Can you extend your logistical capabilities, or do you have a brick-and-mortar store nearby where you can direct these shoppers? Use AdWords retargeting to let them know. Of course, Google Analytics' native reports aren't for everyone. If you find them confusing or haven't worked extensively with enhanced ecommerce data, check out Littledata's report packs. These automated reports are an easy but comprehensive way to read and interpret ecommerce data without any hassle. For the purposes of tracking checkout steps to improve retargeting, I'd recommend our Ecommerce behaviour pack, which includes reports on shopping behaviour by marketing channel and checkout steps. 3. Set up retargeting campaigns based on that data How do you retarget users in AdWords based on Google Analytics data? Fear not, my brave colleagues! If you've made it to this step, you shouldn't have any trouble creating powerful retargeting campaigns. First you'll need to create a new Audience. In your Google Analytics Admin, find Audience Definitions in the middle of the screen near the bottom. Click on New Audience. Click on Create New and on this screen go to Conditions and Filter Users to Include the steps you want to target with this Audience. Set the Shopping Stage to contain (equal) 'Checkout_Abandonment' or 'Checkout_1', 'Checkout_2', etc. - wherever your customers have been falling off and leaving a basket full of goodies without completing the purchase. (Note that this field is auto-completed, so give GA a second after you start typing to show the options here.) You'll then need to set a time period. Think about your specific business and how far back you want to go with the search. Once you're happy with your selection, pick which Google AdWords account you'll want to link to this new Audience. That's it! You're now ready to run PPC promotions to a buy-ready audience that would otherwise have disappeared. I hope you've enjoyed this quick guide. Please drop me a line below and let me know how you use checkout steps in relation to AdWords. I always love to hear how other specialists in the field combine platforms to create perfect marketing. PRO TIP: If you're in a country with Google Merchant available, you can benefit from dynamic remarketing. This does take some extra setup on the product level, so let us know if you have specific questions. (And stay tuned - we're planning some Google Merchant Center-related posts for the near future.)

These days, you can sell just about anything online. From subscription boxes to charities, everyone is using websites and mobile apps to enhance the customer journey. But even if you advertise on the right channels, how do you know if your marketing is working? And how do you connect that traffic to revenue? Watch this quick video to see how the right analytics setup will help you avoid getting shipwrecked on the seas of ecommerce, whatever you might be 'selling' online. https://www.youtube.com/watch?v=hE4nzZycVLE Google Analytics can take you much deeper than Shopify’s native reporting, but setting it up correctly is difficult without the right tools. Littledata gives growing Shopify stores a clear map of shopper behaviour, from marketing campaigns -- how people find you -- to the intricacies of buying behaviour: what customers buy, how they buy it, and who will want to buy more. Our Shopify reporting app automatically audits your Google Analytics setup to make sure you’re tracking everything you should be, and tracking it correctly. We give you accurate data and smart reports on everything from marketing channels like Google AdWords, Facebook and Twitter, to product performance and shopping cart activity, including details like checkout steps and voucher codes. The app makes it easy to tie every aspect of your store back to revenue, so you can make decisions like a captain instead of drifting along in the back of the boat and drawing the map as you float along. And we integrate seamlessly with other popular Shopify apps, including ReCharge and Refersion, so your analytics will always match every touch point in the customer journey. Sign up for free today and we’ll start building a personal treasure map for your Shopify store. Pricing is based on transaction volumes (but you're free to upgrade to a higher plan at any time), and all plans include a free 14-day trial!

How do you choose between Shopify and Magento? Hostinger's Laura Ramonaitytė breaks down the differences between these popular ecommerce platforms. Taking your offline business online, or starting a new online business from scratch, can be overwhelming. However, if you take time to do research and choose the right ecommerce platform for your particular business, you'll alleviate stress and have a much greater chance of success. With so many options in the market, it can be difficult to know that you're making the right decision. Nevertheless, your first preference should be choosing a platform that can fulfil not just current but also future requirements of your online store, at least as much as you can estimate those future needs. To help you make this difficult decision, we've compared the two most popular ecommerce platforms: Shopify and Magento. We look at a number of different categories and performance areas, so make sure to read through the entire post to help you make the best decision for your business. Core differences Before starting the detailed comparison, let’s take a look at some core differences between Shopify and Magento. Shopify is a complete ecommerce platform, while Magento is free and open-source software. For Shopify, secure web hosting is included in all main subscription plans, whereas for Magento you need to set up your own hosting. Both platforms have technology ecosystems with apps and themes to help you customise your site and track online sales and marketing, but Shopify's app store is much more robust and developed, with over 2,000 apps available since they opened to third-party developers in 2009! Let's dive deeper into differences between the platforms. Pricing These platforms handle setup and operating costs differently. Shopify provides a 14-day free trial. After that, users need to purchase a monthly subscription (you can start the trial and then decide on a plan, which is a nice touch). Users can choose from 3 main subscription plans, currently ranging from $29-299 per month, plus lite (for basic selling via Facebook and  'buy' buttons) and enterprise (Shopify Plus) options. Shopify is a fully hosted platform, which means you pay a flat fee per month for a plan that includes hosting. It's worth mentioning that credit card charges and transaction fees can be extra. On the other hand, Magento offers two pricing options: Magento CE and Magento EE. Magento CE (Community Edition) is free for download and use, and you are not required to buy any monthly subscription. It can be a perfect option for small and mid-sized businesses. Magento EE (Enterprise Edition) is another option, ideal for larger online stores and established businesses. The price depends on the size of your business. You can find the exact pricing by contacting Magento specialists and requesting a quote. Startups.co.uk estimates that the costs for setting up and maintaining a Magento EE site are a good fit only for larger ecommerce sites and enterprises: To give some indication, a very basic Magento shop selling less than 6,000 products, that uses pre-made Magento themes, will cost you in the region of £20,000 to £40,000. On the other hand, if you have cheap web hosting, a Magento CE site using a free theme could be quite affordable, as long as you have the expertise to maintain it. Conclusion: Shopify has fixed pricing while the cost of Magento depends on different factors such as the costs of hosting plans, technical support and plugins. If you're an experience ecommerce developer, Magento probably gives the best cost-benefit. Otherwise, Shopify is a better deal. Templates and Designs Elegant templates and designs are a crucial part of any online store. The template which looks and feels good can attract more people and eventually earn more revenue. Screenshots from the Seaside style of the Providence theme for Shopify Shopify has it own theme store, where users can look for beautifully designed, highly-responsive templates and themes. However, since Shopify is a hosted shopping cart, users get limited options for customizations. That said, Shopify's themes are awesome for plug-and-play. The themes are organized by industry, such as Furniture or Clothing, and also by type of store, such as themes optimised for stores with very small (or very large) inventories. Shopify themes generally cost over $100 but include useful features like Instagram product feeds. Screenshots from the free Absolute Theme for Magento Since Magento is open source and has been supported by a large developer community from the start, it has a range of template options. There are free and paid themes available in the Magento Marketplace, and most are mobile responsive, but there is also a huge variety of free and paid themes available from independent front end developers around the world. It's worth noting that some  Magento stores with solid coding experience do create custom themes on their own as well. Here's a guide to theme development if you're running Magento 2. Conclusion If you're looking for more theme options and customization, Magento is the winner. On the other hand, why start from scratch? Whatever you're looking for, it probably already exists in a Shopify theme! SEO Optimization If you are starting your online store from the ground up, it is necessary for you to pick the ecommerce platform that has SEO capabilities as well. Nowadays, more than half of all online purchases begin with an online search in search engines like Google and Bing. Therefore, it is crucial that ecommerce platform you have chosen supports various search optimization techniques. In our analysis, the overall SEO score for Magento is 95 out of 100 whereas Shopify's SEO score is 98 out of 100. Shopify is a highly SEO-optimized platform that has all the basic and advanced SEO features in all its plans. You can easily edit your title tags, meta description, page URLs, according to your requirement. Besides this, you can also customize your image file name and also edit alt tags as per SEO requirements. Like Shopify, Magento is also a fully SEO-optimized ecommerce platform that supports extensive SEO functionality. Along with basic SEO settings, it also provides some advanced SEO options, including canonical tags for separate categories and products, robot.txt files, image optimization, meta tags for products and home page. Conclusion Both platforms seem equally competent in terms of SEO optimization. As long as you have an organized content strategy, you can take advantage of the SEO capabilities of either platform to get more traffic. Customer Support Reliable support is more important than anything else. As a newbie, you may need to access customer support many times in a day. Consequently, invest in the company that has better technical support and back up based on what your needs might be. Shopify provides 24/7 technical support, which means that you can access support day and night whenever needed. There are three ways you can access their customer support team: Email Support Phone Support Live Chat Magento’s customer support does not include any official service. However, you can look for answers to your queries in its extensive developer community, Magento Forums, and in their documentation. Almost all platform-related queries are already answered there. Conclusion: This is the category where Shopify is definitely the winner. Final Thoughts In conclusion, both Shopify and Magento have various stunning features and they can manage your online store efficiently and help to boost your revenue. Magento is an open source platform and is more flexible, but you need to have the staff and knowledge to develop it. Features, customer support and ease of use probably make Shopify a better ecommerce platform for a standard ecommerce business. I hope this post inspires you to dig deeper and make an informed choice before launching your online store, whichever platform you choose. There are other platforms available as well, such as WooCommerce (Shopify vs WooCommerce), so don't just pick one randomly! Hostinger is a leading worldwide cheap web hosting provider.

We're an ecommerce analytics company, so it's no surprise that Shopify and Google Analytics top the list of topics in our most-read and most-shared posts of 2017. But what continues to surprise us is how many online businesses know that their analytics setup needs to be fixed, but put off the decision to take action. Luckily tools like our Shopify reporting app are making it easier than ever to get accurate data and automated reporting that really drives revenue. If fixing your tracking and making decisions based on trustworthy data wasn't your main new year's resolution for 2018, it should be! Here are the top 5 posts from our analytics blog in 2017. They should provide some inspiration. 1. Is Google Analytics compliant with GDPR? From May 2018 the new General Data Protection Regulations (GDPR) will come into force in the European Union, causing all marketers and data engineers to re-consider how they store, transmit and manage data – including Google Analytics. This popular post looks at basic and full compliance. The rights enshrined by GDPR relate to any data your company holds which is personally identifiable: that is, can be tied back to a customer who contacts you. 2. Shopify Marketing Events vs Google Analytics The ability for other Shopify apps to plug their campaign cost and attribution data into Shopify (via the new marketing events API) is a logical step to building Shopify’s own analytics capability, but is it really a viable substitute for Google Analytics? Google already has a team of hundreds working on Google Analytics, and it seems unlikely that Shopify will be able to dedicate resources to keep up with the functionality that power users need. 3. Is Google Analytics accurate? 6 common issues and how to resolve them How do you know if your Google Analytics setup is giving you reliable data? In this much-linked blog post we look at common problems and explain what can be done to make your tracking more accurate. If the journey of visitors on your site proceeds via another payment processor or gateway, you could be losing the link between the sale (or goal conversion) and the original marketing campaigns. 4. How to increase revenue with Refersion and affiliate marketing Affiliate marketing consistently outperforms other channels for ecommerce businesses. In this special guest post, our integration partner Refersion shares essential tips about how Littledata customers can get a piece of the action. When customers come through affiliate channels, their average customer revenue is 58% higher than other channels. 5. What you can track with our Shopify app Here at Littledata we believe that everyone should have access to professional-level analytics tools for tracking, reporting, and improving sales and engagement. That’s why we built the ultimate Shopify reporting app. This much-shared post outlines 'Shopify’s Standard Tracking vs Littledata for Shopify'. It's a match we're betting on! Shopify is one of the best ecommerce platforms on the planet, but their standard analytics are extremely limited.

It's been a busy and exciting 2017 here at Littledata. Our Shopify reporting app really took off this year, and with a bunch of new features and report packs in the works for 2018 we don't plan on slowing down any time soon. Data never sleeps. If you work in ecommerce, analytics or -- as we happen to do here at Littledata -- ecommerce analytics, the holiday shopping period can be sleepless for the humans in charge of that data, too. So we wanted to take a moment to pause and give thanks. We couldn't have made it this far without you. From our team to yours, happy holidays! May the coming year bring you peace and success.    

I’m exasperated reading dodgy logic justifying the heady ascent of Bitcoin. What are the worst 5 arguments I’ve heard? Full disclosure: I don’t own any Bitcoin, or have any bets on its rise or otherwise. 1. Bitcoin is an insurance against the collapse of capitalism The booster The rise of artificial intelligence and mass joblessness will sweep away much of the old order of nation states and their currencies. Bitcoin is independent of government and will survive the coming storm. A grain of truth I believe big change in the relative value of labour and capital, and how they contribute to the tax base, is coming faster than politicians expect. And the reactionary backlash in affected countries, such as those voting for Donald Trump, won’t stop this trend. The sceptic Bitcoin relies on a chain of other technologies which may well get disrupted with the collapse of capitalism: cheap power supply, a global internet and secure online vaults to hold the private keys and transact the Bitcoin. If you’re betting on the end of the world as we know it, hunting and farming skills are going to be more useful!   2. Bitcoin’s limited supply makes it deflationary by default The booster Unlike fiat money (e.g. the US dollar) which can be printed at will by central banks, the total number of Bitcoin is mathematically limited to 21 million. That means, as other currencies inflate, Bitcoin will hold its value – i.e. it’s digital gold A grain of truth As developed countries around the world are forced to borrow themselves out of the hole of shrinking tax bases and increasing healthcare costs, they may try to inflate their currencies to erode the debt. The sceptic Central banks have a positive inflation target for a reason: in a deflationary currency, no-one wants to spend the currency and so there’s no circulation of wealth. If one Bitcoin could have bought me a coffee in 2016, but at the time of writing could have bought a car, why would I ever spend it? And if no one spends the currency then it has no tangible value.   3. Bitcoin is the leader of the blockchain revolution The booster Blockchain is one of the few game-changing technologies to be invented the last two decades. It will revolutionise the world of finance, and you need to own Bitcoin to be part of that. A grain of truth The blockchain ledger, keeping a public record of all transactions, and reducing the possibility for fraud or interception, will certainly change many aspects of finance. There are many projects underway in financial trading and government. The sceptic Just because Bitcoin was the first use-case of the technology, does not make it essential to newer blockchains. Equally, its first-mover advantage may not even make it the winning cryptocurrency. That said, I wouldn’t go out buying a basket of other cryptocurrencies just yet – they are all overinflated by Bitcoin’s rise.   4. The increasing mining cost of Bitcoin underpins its value The booster New bitcoin gets exponentially harder to mine, so since the cost of electricity for the miner’s servers won’t fall, the cost per bitcoin mine is rising all the time. And if you can’t mine them, you’ll have to buy them. The sceptic Yes.. but what if no one needs Bitcoins at all? Mining gold is subject to the same economic forces, but if the gold goes out of fashion as a value store (as it did an the turn of the Millennium) it still had industrial value for conducting electricity and aesthetic value for jewellery. Bitcoin has neither of those.   5. The rise of bitcoin is 2017 shows it has won out as the cryptocurrency of choice The argument Bitcoin is now the established alternative store of value, which is why it has risen so fast in 2017. And what if all the pension funds and institutional investors now buy up a slice to ensure an allocation of this new asset class? A grain of truth There’s no rational way to value Bitcoin: it does not pay dividends or have intrinsic worth (see point 4). So it could be worth anything .. or nothing. The sceptic Every decade a new mania comes along for investors to follow. The vast chatter on LinkedIn, Facebook and other forums only heightens the mania by allowing unchecked falsehoods to flourish. You only have to look at the South Sea Bubble and Tulip mania to see there is nothing new under the sun. Enjoy the roller-coaster ride up .. because everything that goes up, must come down.      

https://www.youtube.com/embed/PAeCubNxoKI Could you be missing out on your best customers - those that are more likely to convert, and more likely to make big purchases when they do? Watch this quick video to find out how to to set up demographics tracking in Google Analytics. Demographics and interests data provides information about the types of customers that are using your site, along with the interests they express through their online travel and purchasing activities. Once you set up this tracking, you'll be able to see your customer base broken down by age group, gender and interests. This data isn't just nice to have; it helps you market to the biggest potential spenders by discovering who's most interested in your products or services. Analytics and AdWords use the same age, gender, and interests categories, so this is particularly useful for improving your targeting on the Google Display Network. That said, connecting demographics data with shopping activity and revenue is a complicated art. Our popular Buyer Personas feature automates reporting and shows you how to improve that spend. And we don't just stop with paid ads. We include personas for every significant channel, including email marketing, organic search, affiliates/referrals and social media campaigns. Wherever you want to use demographics targeting to increase revenue, we've got you covered.

The results are in, and this year's Black Friday sales prove that things are continuing to look up for ecommerce. Across 570 online stores, the average store did 2.4 times their normal sales in Black Friday week 2017, compared with only 2.2 times in 2016 – and a greater proportion of stores participated in the sales. Following our post on pre-Black Friday trends, Littledata looked again at what happened from Thanksgiving Thursday 2017 through to the following Wednesday (the week including Black Friday and Cyber Monday) – versus a control period of November & December in 2016. Compared with 2016, we found a bigger number of stores participating in Black Friday sales this year: 53% of stores were trading more than 1.5 times their normal volumes, compared with only 49% in the equivalent week in 2016. For those stores which promoted heavily in 2016, the median boost was 2.5 times normal. And those in the bottom quartile of sales in 2016 still traded 108% their normal volumes. How did Black Friday promotions work for your store? Use our industry benchmarks to find out how your online store is performing against the competition.

I knew Black Friday had reached ‘late adopter’ stage this week when a company I’d bought fencing panels from - fencing panels – emailed me their holiday season promotions. But the real question is whether all these promotions serve to drive customer loyalty or just attract bargain hunters? At Littledata we looked at aggregate data from 143 retailers who participated most in 2016 Black Friday, versus 143 retailers who did not. For the first 23 days of November 2017 – before Black Friday – the median year-on-year increase in sales was 13% for those pushing discounts the previous year, versus only 1% growth for those avoiding Black Friday discounting *. Our conclusion is that retailers who discounted most heavily on Black Friday 2016 saw a lasting benefit in extra sales a year after the sales period. However, we don’t know whether these extra sales were profitable enough to pay for the seasonal promotions. Another possible explanation is that higher-growth retailers are more active in marketing Black Friday, but in either event the discount season has done them no harm over the following year. In a follow up post next week we’ll compare the peak discount trading – and see if on average these same stores increased their participation this year or reigned it back. Looking at 2016, it seems Black Friday was bigger than the year before for our cohort of 270 UK retailers – but at the expense of sales later in the season. Yet in the UK we are not close to US-levels of hysteria yet, where a much greater proportion of the last quarter’s sales are done on that weekend. The other interesting question is what sectors does Black Friday affect? Reflecting back on my 2016 post, it may be a surprise that the biggest boost of over 100% average increase in sales comes for Health & Beauty stores; whereas technology and computer stores on average saw a boost of 40% for the week. (The graph shows the difference with the average sales volumes in November & December, by sector, for 3 selected weeks.) And perhaps I shouldn’t have been surprised by those fencing panels: business and industrial sites saw a big boost too! Interested in tracking online sales activity for your own site this holiday shopping season? Littledata's ecommerce analytics software provides accurate data and automated reporting to help you track promotions and drive conversions and customer loyalty. * The statistical detail I took a group of 573 retailers we have tracked for at least 2 years, and looked at the ratio of Black Friday weekend sales (Friday, Saturday, Sunday, Monday) to the 2 month average for November and December. Those in the top quartile (trading 2.6 times above average during the Black Friday season) were deemed to have participated; those in the bottom quartile, showing a dip in trading over that weekend were deemed not to have participated. I then looked at the year-on-year growth in revenue between November 2016 (first 23 days) and the same period in November 2017, for the discount versus non-discount group. A t-test between the groups found a 18% probability that the two groups had the same mean, not allowing us to dismiss the null hypothesis.  

Understanding how your website performs versus similar sites is the best way to prioritise what to improve. In this post we take a look at 6 top benchmarks for optimising Shopify store performance. Accurate benchmark data is especially useful to the increasing number of ecommerce companies using web performance benchmarks, such as bounce rates and home page reliance, as core elements of their sales and marketing KPIs. Understanding benchmarks is a key to success. To put together this new benchmarking report, we analysed current data from 470 Shopify retailers. If you're wondering how you compare, check out our Shopify analytics app. Average order value Average order value (AOV) or Average revenue per paying user (ARPU) is the total monthly revenue divided by the number of users which transacted that month. It is a measure of how well you are up-selling and cross-selling your products, depending on your product mix. What is a good average order value for Shopify stores? The benchmark is $69. The average is slightly lower ($63.50) if you are a smaller Shopify store. More than $120 AOV would put you in the top quartile, and one of our top-performing stores in the luxury ecommerce sector is averaging $2,080 per order! If your Shopify store has a lower AOV than the benchmark, you might try increasing your average checkout value by cross-selling other products, offering free shipping above a minimum threshold or increasing pricing on selected products. Ecommerce conversion rate Ecommerce conversion is the number of purchases divided by the total number of sessions. Most visitors will take more than one session to decide to purchase, but this is the standard measure of conversion rate. It is a measure of how good a fit your traffic is for your products, and how well your site converts this traffic into customers. What is a good ecommerce conversion rate for Shopify stores? The benchmark is 1.75%. Larger stores have pushed this to 1.85%, and if you are more than 2.8% you are in the top quartile. The highest conversion rate we’ve seen on Shopify is 8%. Can you increase the conversion rate with more attractive product displays, or improving the checkout process? Enhanced ecommerce tracking will help you identify exactly where the blockers lie. Bounce rate from mobile search Since more than 60% of Google searches are now done on mobile, ensuring your site design works on a small screen is important for branding and sales. Bounce rate is the percent of visits of only one page – and will be high if your landing pages do not engage. Google will even adjust your mobile ranking for a given keyword depending on what proportion of visitors stick on your page - a good indication that your link was useful. What is a good bounce rate from mobile search for Shopify stores? The benchmark is 47.5%. The biggest Shopify stores have got this below 40%, and overall large retailers have 38% mobile bounce rate. So it’s not a problem with the Shopify platform, so much as a problem with the store theme – or how the options and products are displayed on a smaller screen. Can you improve the first impressions of the landing pages, put key content higher up the page, or decrease the page load speed to reduce that bounce rate? Delay before page content appears The delay between a page request by the user and them being to read or click on that page. This is more important than full page load speed for AJAX / lazy loading sites (also called the ‘DOM Interactive Time’). What is a good delay time before page content appears? The benchmark for Shopify stores is 2.75 seconds. Even larger retailers have this down to 2.8 seconds, so Shopify sites do well on this score. Anything less than 3 seconds is generally acceptable. Internet users are increasingly intolerant of slow sites. Your developers could look at Google PageSpeed Insights for more details. Often the delay will be down to extra scripts which could be delayed or removed. Server response time This is the part of the page load speed which is entirely outside of your control – and due to the speed of the servers your site runs on. What is a good server response time for Shopify stores? The benchmark is 322ms. The average for larger ecommerce is 542ms – so Shopify’s server infrastructure is serving you well here. Reliance on the homepage This is the percent of visitors who land on your homepage. If this is below 40% you rely heavily on your homepage to capture brand or paid search traffic. Google increasingly rewards sites with a greater volume of landing pages targeting more specific keyword phrases. What is a good reliance on homepage percentage for Shopify stores? The benchmark is 32%. Larger Shopify stores, with many more landing pages, have reduced this to 7.3% of traffic landing on the homepage on average. Can you build out product landing pages and inbound links to copy their advantage? Ready to benchmark your own website, stop playing guessing games and start scaling your ecommerce business? Our Shopify reporting app is the easiest way to get accurate benchmarking. Install Littledata today and you'll get instant access to up to 20 relevant industry benchmarks for ecommerce sites, plus the tools you need to fix your analytics for accurate tracking, so you'll always know for sure where your website stands. It's all about smart data that helps you focus on making changes that drive revenue and increase conversions. We're here to help you grow!

Affiliate marketing consistently outperforms other channels for ecommerce businesses. In this special guest post, Refersion's Robert Woo shares essential tips about how Littledata customers can get a piece of the action. Affiliate marketing is a powerful channel to drive sales, but is surprisingly overlooked by many small and medium-sized businesses. In a 2016 report by Heinz Marketing, referrals made the most positive impact on revenue for businesses, by far. As business owners know, the easiest sales come from customer recommendations to their friends and family. Especially for SMBs, word-of-mouth is often the backbone of how they acquire new customers. Now here’s another statistic: when customers come through affiliate channels, their average customer revenue is 58% higher than other channels. In other words, not only is it easier to get more customers via word-of-mouth, if they are referrals, but those customers also spend more. As you can see, getting into affiliate marketing is a double win for your business. But it can seem tricky to get started. The traditional way of doing affiliate marketing Online affiliate, or referral, marketing is as old as the internet. Here’s how it traditionally works: Research various affiliate networks that are accepting new merchants (that’s you). Pay a fee to join one (as high as $5000). Use this network to find affiliate partners to market your product/service. Pay out a commission to these partners. Pay out a monthly fee, and a portion of these commissions (15 to 25%) to the affiliate network. In this traditional way, you can see a clear trade-off for the benefit of joining an existing network. While you’ll have immediate access to many publishers waiting to market your product, there are a lot of fees for this privilege. So much so that for smaller businesses often find it hard to make a good profit from this model. On the other hand, you could start your own program up from scratch. But while you’d save a fortune in fees, the big trade off is your time investment. It takes time to put an affiliate marketing program in place. From creating a portal for your affiliates to use, to finding these influencers in the first place, to getting the hang of the metrics you need to monitor; it can all be a lot, especially for SMBs with a small team devoted to marketing. The better way, for Littledata customers Luckily, we here at Refersion have made it easy and affordable to forego joining an existing affiliate network and start your own. What we do is help businesses take a 'hybrid approach', taking the best of both worlds, making running a program cheap and simple. The best part? We’ve now integrated with Littledata to make data analysis even more insightful, so your business can easily maximize the ROI of your in-house affiliate marketing program. Used together, Littledata and Refersion are a supercharged toolbox for ecommerce entrepreneurs who have always wanted to launch a referral program, but was afraid to commit the time and energy. With Refersion, you can set up your business to start taking advantage of affiliate marketing in less than ten minutes. Connect your online shopping cart, create custom affiliate emails and coupon codes, and quickly find the right publishers to work with in the Refersion Marketplace. And if you’re already a Littledata customer, you’ll know that you can get all your affiliate marketing metrics and analysis in your dashboard and reporting. Don’t leave money on the table With the rise of ad blockers, many types of online marketing have taken big hits. But affiliate marketing isn’t subject to this limitation. Don’t ignore one of the best channels of getting new customers and higher sales! If you want to learn more about Refersion, watch this short intro video on how it all works. Ready to take the plunge? Here’s a special signup page for Littledata customers. Get a 14 day free trial today! Robert Woo is a Marketing Manager at Refersion.

https://www.youtube.com/watch?v=YVxi0sQmro0&t=5s Google Analytics is only as smart as your tagging. To lower average CPA and increase conversions in a sustainable way, you need an in-depth view of customer acquisition channels. Accurate campaign tagging makes it possible to get the data needed to understand acquisition costs based on particular source and medium. If you want to improve marketing ROI, it's essential to get campaign tagging right in Google Analytics. But how does it all work? Follow the simple rules in this quick how-to video to make sure you're getting accurate data about where your traffic is coming from. Questions addressed in the setup video: What is a campaign in Google Analytics (GA)? What is UTM Parameter and how do I use it? Is it possible that a large volume of my 'Direct' traffic in GA is actually coming from sources such as email or social, but just wasn't tagged correctly? How do I know? I want to see all email marketing campaign traffic as one line item in my GA reports. Do spellings matter? Are UTM parameters case-sensitive? What are the best practices for GTM tagging using the Google Analytics Link Builder? For more info on custom campaign tracking, check out this detailed post about campaign parameters and how to use them. Remember that when you set up new campaigns or marketing channels, things can change or get lost in the mix. It's important to keep an eye on your analytics setup. Even once you've successfully set up campaign tagging in GA, we recommend auditing your analytics on a regular basis. And don't stop there. Once you've established data accuracy, follow in the footsteps of the most successful ecommerce sites and use Buyer Personas to get a clear view of which types of customers are more likely to convert in each channel. Now that's smart growth, driven by data!

From May 2018 the new General Data Protection Regulations (GDPR) will come into force in the European Union, causing all marketers and data engineers to re-consider how they store, transmit and manage data – including Google Analytics. If your company uses Google Analytics, and you have customers in Europe, then this guide will help you check compliance. The rights enshrined by GDPR relate to any data your company holds which is personally identifiable: that is, can be tied back to a customer who contacts you. The simplest form of compliance, and what Google requires in the GA Terms of Use, is that you do not store any personally identifiable information. Imagine a customer calls your company and using the right of access asks what web analytics you hold on them. If it is impossible for anyone at your company (or from your agencies) to identify that customer in GA, then the other right of rectification and right of erasure cannot apply. Since it is not possible to selectively delete data in GA (without deleting the entire web property history) this is also the only practical way to comply. The tasks needed to meet depends on your meaning of ‘impossible to identify’! Basic Compliance Any customer data sent ‘in the clear’ to GA is a clear break of their terms, and can result in Google deleting all your analytics for that period. This would include: User names sent in page URLs Phone numbers captured during form completion events Email addresses used as customer identifiers in custom dimensions If you’re not sure, our analytics audit tool includes a check for all these types of personally identifiable information. You need to filter out the names and emails on the affected pages, in the browser; applying a filter within GA itself is not sufficient. But I prefer a belt-and-braces approach to compliance, so you should also look at who has access to the Google Analytics account, and ensure that all those with access are aware of the need not to capture personal data and GDPR more generally. You should check your company actually owns the Google Analytics account (not an agency), and if not transfer it back. At the web property level, you should check only a limited number of admins have permission to add and remove users, and that all the users only have permission to the websites they are directly involved in. Or you could talk to us about integrations with your internal systems to automatically add and remove users to GA based on roles in the company. Full Compliance Other areas which could possibly be personally identifiable and you may need to discuss are: IP addresses Postcodes/ZIP codes Long URLs with lots of user-specific attributes The customer’s IP address is not stored by Google in a database, or accessible to any client company, but it could potentially be accessed by a Google employee. If you’re concerned there is a plug-in to anonymise the last part of the IP address, which still allows Google to detect the user’s rough location. ZIP codes are unlikely to be linked to a user, but in the UK some postcodes could be linked to an individual household – and to a person, in combination with the web pages they visited. As with IPs, the best solution is to only send the first few digits (the ‘outcode’) to GA, which still allows segmenting by location. Long URLs are problematic in reporting (since GA does not allow more than 50,000 different URL variants in a report) but also because, as with postcodes, a combination of lots of marginally personal information could lead to a person. For example, if the URL was mysite.com/form?gender=female&birthdate=31-12-1980&companyName=Facebook&homeCity=Winchester This could allow anyone viewing those page paths in GA to identify the person. The solution is to replace long URLs with a shortened version like mysite.com/form And for bonus points... All European websites are required to get visitors to opt in to a cookie policy, which covers the use of the GA tracker cookie. But does your site log whether that cookie policy was accepted, by using a custom event? Doing so would protect you from a web-savvy user in the future who wanted to know what information has been stored against the client ID used in his Google cookie. I feel this client ID is outside the scope of GDPR, but guaranteeing that the user on GA can be linked to opt-in consent of the cookie will help protect against any future data litigation. The final area of contention is hashing emails. This is the process used to convert a plain email like ‘me@gmail.com’ into a unique string like ‘uDpWb89gxRkWmZLgD’. The theory is that hashing is a one-way process, so I can’t regenerate the original personal email from the hash, rendering it not personal. The problem is that some common hashing algorithms can be cracked, so actually the original email can be deduced from a seemingly-random string. The result is that under GDPR, such email hashes are considered 'pseudonymized' - the resulting data can be more widely shared for analysis, but still needs to be handled with care. For extra security, you could add a ‘salt’ to the hashing, but this might negate the whole reason why you want to store a user email in the first place – to link together different actions or campaigns from the same user, without actually naming the user. There are ways around that strike a compromise. Contact Littledata for a free initial consultation or a GDPR compliance audit.

I was proud to be invited by Microsoft to speak at their Codess event in Bucharest last week to encourage women in software. We talked about how Littledata uses Meteor, Node and MongoDB to run scalable web applications; slightly controversial because none of these are Microsoft technologies! The event was well run and well attended, so I hope it inspires some of the attendees to start their own projects...or to join Littledata (we're hiring).

There's never been a better time to grow a subscription-based business. But the landscape is also more competitive than ever. How do you rise above the noise and obtain devoted subscribers? With our new ReCharge report pack, any recurring-product business can get advanced analytics to help obtain a devoted subscriber base. It's the latest addition to our automated packages of analytics reports. The new pack includes a curated selection of reports proven to help subscription-based ecommerce sites get more traffic and increase recurring revenue. Each report automatically pulls relevant data from your Google Analytics account and turns it into actionable reports, with essential tables and smart visualisations. Growth of subscription-based businesses From vitamin supplements to hacker boxes, product subscription companies are on the rise. Getting products in the mail every month is a huge chunk of the future of ecommerce. According to the Subscription Trade Association (SUBTA), the subscription box industry alone is on track to generate more than $90 billion in annual revenues in the coming decade. SUBTA itself was only formed a little over a year ago, coalescing around this exciting new ecommerce community, and their first events have all sold out. Entrepreneurs who want a piece of subscription industry growth need to optimise every part of the customer life cycle. You don't just need more traffic, you need better-quality traffic. And you don't just need to improve the user experience (UX) on your site, you need to create an engaging customer experience (CX) that drives conversions, brand devotion and upsells. Sounds easy, right? Think again. Luckily there are solutions like ReCharge and Littledata that work out of the box to help you run and optimise a subscription business. What's in the new report pack Our popular ReCharge integration was built to give subscription-based companies accurate marketing attribution for signups and sales in their Shopify stores, but it's quickly grown to be even more detailed, offering deep analytics across the subscription customer life cycle. Automatically connecting marketing campaigns to recurring payments is just the beginning. The first ReCharge report pack makes it easy to keep tabs on where your customers are coming from, the balance between new signups and recurring payments, and how different subscription plans are contributing to revenue. The pack contains a general overview widget plus four key reports for digging deeper into recurring revenue. Which marketing campaigns are driving the most first-time purchases? Is organic search outperforming your PPC campaigns? Is revenue per recurring purchase growing at a steady rate? Those are questions with answers. The ReCharge report pack will help you: Get a concise overview of weekly performance Increase marketing ROI with a clear understanding of how different channels and campaigns are contributing to customer growth Build a sustainable subscription business by optimising revenue segments and payment solutions The Reports tab in your Littledata dashboard automatically shows all relevant report packs, so check them out today and reach out if you have any questions. The ReCharge pack pairs well with our Basics pack, which includes essential reports on site performance and user behaviour. PS: Still waiting to try our Shopify reporting app? Don't delay! We have a plan for every sized business, and ReCharge integration is free!

Search traffic is essential for ecommerce growth, and it takes time to build. In this guest post, SEO expert Bill Widmer highlights 5 easy steps to rise to the top. There are over 1 billion websites on the internet today, with almost 2.4 million websites created every day. Of those sites, only 10 make it to the front page of Google. And the top result gets 30% or more of all the search traffic. Where does that leave you? If you don’t take SEO seriously, there’s no way your ecommerce site will beat the competition. If you want to make tens of thousands of extra sales every year, without spending a dime on marketing, listen up. It’s time to boost your ecommerce search traffic. Step 1: Start a blog and produce high-quality content Don’t think you can get away with slapping together a few paragraphs about your latest collection and calling it a blog article. The content gods are watching! In all seriousness, quality content is crucial to ranking on the first page of Google. It’s one of their top 2 ranking factors to determine what to show (the other is backlinks). But what exactly does quality content entail? Let’s hear it from the horse’s mouth: Google's basic principles for high-quality content Make pages primarily for users, not for search engines. Don't deceive your users. Avoid tricks intended to improve search engine rankings. A good rule of thumb is whether you'd feel comfortable explaining what you've done to a website that competes with you, or to a Google employee. Another useful test is to ask, 'Does this help my users? Would I do this if search engines didn't exist?' Think about what makes your website unique, valuable, or engaging. Make your website stand out from others in your field. In a nutshell, Google wants you to focus on providing value to your readers with every blog article. Producing high-quality, long-form content (at least 1,500 words) is the key to ecommerce content marketing and pleasing the search gods. Pro Tip: Not sure what kind of blog articles to produce? As a general rule of thumb, steer clear from anything that’s too obvious and salesy (eg. 5 Shoes From Our Latest Collection That You’ll Love). Instead of this, try to produce content that’s useful to your customers (eg. How To Maintain Leather Shoes: A Comprehensive Guide). With these less salesy articles, you can still include links and call to actions for readers to shop your products after they’re done reading the article. As an added bonus, these articles can help you rank for keywords which your product and category pages can’t (such as 'how to maintain leather shoes'). Step 2: Fix your on-page SEO On-page SEO refers to elements which you can optimise within your website (off-page SEO, on the other hand, deals with external links and other factors). Image from FlightMedia.co With on-page SEO, the first thing you need to do is select the keywords you want to target. Once you’ve got your keywords in mind, optimize your title, header tags, content, image alt texts, and metadata for each page and post on your website. If this sounds like Greek to you, don’t stress. Here’s a step by step guide which will take you through the entire process. Pro Tip: Only target one keyword per page to increase your chances. However, it’s always a good idea to include LSI keywords! Step 3: Add internal links to your most important pages By adding internal links (links from one page on your site to another page on your site), you’re helping Google to understand the relationship between the different pages and posts on your ecommerce site. The more internal links a specific page or post on your website has, the more 'important' it is deemed by Google. Think of your website as a pyramid, with the most important content - your 'cornerstone' content - at the top. You should be linking from your cornerstone content to other related pages in order to pass on link value to them. At the same time, link to these cornerstone pages from other pages in order to bolster their standing. Want to learn more about internal links? Check out this article. Step 4: Build external links Once your internal links are done, it’s time to move on to building external links. You might need to invest some budget into this, but since Google has confirmed that external links are amongst the top 3 ranking factors, I’d say it’s definitely worth your while. First, look for influencers in your industry and reach out to them to enquire if they’d be willing to link to your website in exchange for a small fee OR for a partnership. You can use platforms such as Mailshake and VoilaNorbert to speed up the communication process. Another way of getting backlinks is to guest-post on other websites. Whilst this typically takes longer to execute, it’s a great way of building your brand and establishing thought leadership whilst getting more backlinks. Step 5: Consider paid traffic Assuming you’ve completed all the above steps (and you reallllly should!), this doesn’t mean you’ll see results overnight. It’ll take some time (a few months, or even a year) for you to experience a boost in your organic traffic. In the meantime, you can consider 'supplementing' with paid traffic. Image from ThinkDigi.org The two most commonly used channels are Facebook Ads and Google Ads - and there are tons of useful resources online that will teach you all the basics (read this guide for Facebook ads or this guide for Adwords). Alternatively, if you don’t want to handle your ads yourself, you can always outsource them to an expert. Once those ads are running, a full-cycle analytics platform like Littledata is essential to help you optimise your ad spend and connect it to revenue. After all, the idea isn't just to get more traffic, but to get the best kind of traffic and sell to your best type of customer - the kind that's more likely to convert. The truth about ecommerce growth A few parting words. A lot of ecommerce store owners think that as they become more established, they’ll automatically have more people visiting their website. The truth is, word of mouth can only get you so far - and if you’re serious about growing your ecommerce store and increasing your profits, you’ll need to boost your search traffic through SEO and the other methods discussed above. And you'll want to optimise that search traffic by paying attention to specific metrics such as bounce rates from mobile Google search. Do you want to see a nice exponential curve in your search traffic analytics, or are you content to have your traffic flatlining? The sooner you get started, the sooner you’ll be able to snag that highly coveted spot in the first page of Google. I’m rooting for you! Bill Widmer is a content marketing and SEO expert who has worked with many well-known brands like Content Marketing Institute, Social Media Examiner, and SEMrush.

We're excited to announce that the first automated report packs are live in the app! Each pack contains a curated set of reports proven to help ecommerce businesses scale faster and smarter. Looking for next-gen analytics reporting that doesn't break the bank? We developed report packs to make advanced analytics accessible to every customer - in just the right combination. You can subscribe to an entire pack for one low monthly price. Why we built report packs Call us crazy, but we believe that every ecommerce business should have the tools to automatically transform their Google Analytics data into actionable insights. Otherwise, what's the point of all that tracking? Unlike the reporting features in some other analytics apps, Littledata's reports never sacrifice accuracy for usability, nor the other way around. Put simply: we have no time for fluff. We believe that the most useful analytics can - and must - be both clean and accurate, and we've built the app's reporting functionality around the actual reporting needs of successful ecommerce businesses, based on our experience with enterprise customers, Shopify stores, and some of the biggest charities in the world. Our analysts considered the many setups we’d built for customers on top of the core Littledata app, and the idea for report packs grew out of this work. We found that growth-oriented ecommerce businesses weren't just looking for clutter-free analytics, but the right combinations of reports to guide ad spend, marketing channel priorities, ecommerce site design and customer journeys. As a result, report packs are next-gen reporting with just enough algo-awesomeness to keep the data geeks happy while letting your marketing team focus on actionable insights to increase engagement at every stage of the shopper journey, from first views and clicks to repeat buying behaviour. The first three packs We've launched three report packs to start: a Basics pack, an Ecommerce Performance pack, and a Shopify marketing pack. Basics pack Overview of site performance Sessions and bounce rate by city Sessions by device type Pages where users enter and exit The Basics pack includes four essential reports on site performance and user behaviour. It's a must-have for any ecommerce site with active users, whether you have a ton of conversions or are still growing your shopper base. Ecommerce Performance pack Overview of ecommerce stats Product category performance Number of sessions to make a transaction Number of days until a purchase is made Many Littledata customers use an enhanced ecommerce setup in Google Analytics. With four essential reports on shopping behaviour and store performance, the Ecommerce Performance pack will help you get the most out of that setup and make data-driven decisions for rapid growth. Shopify pack Conversion rate by marketing campaign Conversion rate by marketing channel When users are most likely to buy Shopping behaviour by channel The Shopify pack includes four reports that connect marketing channels with shopping behaviour. Built to give our Shopify app users a pro reporting experience, the pack contains essential analytics for growing a Shopify store through intelligent targeting. Anticipated addition to our reporting feature set Report packs offer high value at a lower price point by automating data collection and presentation based on proven ways to use and interpret Google Analytics data. Even though they're newly launched, they've already become a much-used feature alongside our popular custom reports, which agencies and large ecommerce stores use to dig deeper into marketing channels and user behaviour specific to their site design and business models. We recommend starting with one report pack and then adding more packs and custom reports to fit your needs. Subscribe to a report pack today to lock in an early-bird discount and start making better-informed marketing and product decisions. New to Littledata? Sign up for a free analytics account. PS. Our developers are hard at work on a number of new report packs, including packs for enhanced ecommerce, ReCharge subscription businesses, email marketing, Facebook ad performance, and more. Subscribe to this blog for the latest updates.

[embed]https://www.youtube.com/watch?v=YVGAdHTkw3s[/embed] Product performance can seem confusing, but it doesn't have to be. In this quick video, we show you how to use Google Analytics to see shopping behaviour related to each product you're selling. All you'll need to see this report is a site connected to Google Analytics with the Enhanced Ecommerce plugin setup. Using the Shopping Behavior report in Google Analytics Whether your ecommerce site is large or small, the Shopping Behavior report makes it easy to drill deep into user behaviour to understand why some products are converting better than others. If a particular product isn't selling well, the Shopping Behavior report will help you figure out why. It shows how far shoppers engage with your products, from initial list views through to shopping cart activities. Reasons a product might not be selling well It isn't at an optimal place in a product list or display The product details, such as images and description, aren't sending the right message Customers are abandoning their shopping carts completely, or removing that particular product (or group of products, such as multiple pairs of jeans) after adding it Who knows? You haven't audited your Google Analytics setup lately so your customer behaviour data can't be trusted to help you improve Each of those issues requires different actions, sometimes by entirely different departments (ie. marketing, pricing, ux)! That's what makes the Shopping Behavior report so important for improving ecommerce sales and conversions. We hope you enjoyed this latest video in our series of Google Analytics how-to guides. Need help setting up Enhanced Ecommerce in Google Analytics, or ensuring that your data is accurate? Contact a Littledata consultant today.

Does this sound familiar? 'We know our data's bad, but we don't have the time or resources to fix it'. Or, even worse: 'I checked a bunch of other metrics and they didn't justify our current ad spend, so I think I'll just present that same old report at the meeting today...again. Luckily we haven't fixed our Google Analytics setup to track too much relevant data about other marketing channels, or to connect those channels directly to revenue, because then we might need to change our whole strategy!' There's still a lot of confusion out there about the role and scope of an analytics audit. With a free audit tool directly in the  app, Littledata is on a mission to change this. Here are some (slightly exaggerated) versions of common objections to doing an analytics audit, and how to overcome them. 1. You don't know what a Google Analytics audit is Okay, not to start this somewhat ironic post with an entirely un-ironic objection, but not understanding the process is probably the only good reason not to audit your analytics setup. Luckily an analytics audit is actually very straightforward: it's simply a check of your analytics configuration and implementation. Some consultants and last-gen apps can make the audit process seem confusing and disorienting. If that's been your experience, we're here to help. Our free Google Analytics audit tool explains the process in real time. Not only that, but many tracking and reporting issues can be fixed automatically by the app (hello, intelligent algorithm!). 2. You don't believe in marketing ROI There are a lot of fluffy tools out there. Google Analytics isn't one of them. It's not that all digital marketers take action based on analytics, but a majority of the top ones do. That's what makes them the best. If you need convincing that accurate data is the secret sauce behind higher marketing ROI (return on investment), check out the recent Google Analytics research with Econsultancy, where they found that '60% of leading marketers routinely take action based on analytics, and are also 48% more likely than mainstream marketers to say their strategy is strongly data-driven'. 3. You trust everything you read online Failing to audit your analytics setup is basically the same as believing that everything you read online is true, no matter the source. Why? Because bad data produces bad reports. This is true no matter how fancy your reporting templates might be, or how much time you've spent making spreadsheets of Google Analytics data look accessible. Unless you regularly audit your analytics setup, how do you know if you're tracking the right things in the right manner? This is especially true if you're using an otherwise awesome ecommerce platform like Shopify, which has notoriously questionable tracking that also happens to be easy to fix with the right analytics app. 4. You think that the customer is always wrong Customer happiness isn't just a buzzword, it's increasingly what's driving the growth and expansion of online businesses, especially in the ecommerce space. Big players like Amazon learned this early on, and they built an effective - and addictive - customer experience around heaps of data on everything from affiliate ads to repeat buying activity. Think you don't have access to those same tools? Think again. If you want to build a better customer experience, it's essential to start with the correct Google Analytics setup and end the guessing games about where your leads and customers come from, and how they act. That's where the audit comes in. 5. You're betting on failure Are you betting that your own company will fail? Unless you secretly run an ecommerce hedge fund and have shorted your own startup, this is probably a bad idea. Auditing your data tracking across the customer life cycle is a sure way to see what's working, what's not, and what can be improved. Otherwise you're stuck with bad data and revenue tracking that might not have much to do with the reality - or the future - of your online business. Is there a better way? Look, we get it. Change can be scary, but choosing to stay stuck in the same data rut isn't the way forward. We've helped over a thousand online businesses fix their Google Analytics setup to capture accurate, relevant data. Littledata's industry-leading automated audit tool is free to run as often as you'd like. Sign up today and start trusting your data.

https://www.youtube.com/watch?v=OlsMBWFt5aQ What are visitors searching for on your website? Watch this quick video to learn how to set up Site Search tracking in Google Analytics. Site Search makes it easy to track search activity on your site. In the video we show you how to: Set up Site Search for a web property connected to your Google Analytics account Understand which query parameters you're using, and apply them to your Site Search setup View the resulting search metrics, including visits with search, total unique searches, specific search terms (what web visitors are searching for), and search depth Tracking on-site search terms is surprisingly easy! All you'll need to get started is a Google Analytics account and a search box on your site. What are visitors searching for on your site? On-site search is one of the things we scan for with our free Google Analytics audit tool. Many online businesses forget to add this to their Google Analytics setup, focusing instead on external search data such as that from Google AdWords (or ignoring search activity altogether!), but this is a mistake. Capturing on-site search terms is essential for any online business that that is serious about growth. Understanding what web visitors are searching for - and how that leads to deep engagement with your site or app - can help you improve site UX (user experience), develop product offerings which your customers are already hungry for, and get a higher ROI from product marketing campaigns and ad spend. For more details on the Site Search feature and how to identify search query parameters, check out the Google Analytics help guide. Still have questions? The Littledata team is always here to help. You can contact us directly in the app, or feel free to connect with our Google Analytics consultants for larger projects. Hint: Use search-related benchmarks to find out how your on-site search traffic compares with other sites in your industry and location. The Littledata app includes analytics benchmarks to make this as easy as possible. For example, you can compare usage of internal search on your website against internal search usage on all websites. Once you've set up Site Search, you will automatically be able to see relevant search-related benchmarks in your Littledata dashboard.  

For two decades the ecommerce customer journey has stayed roughly the same. Customers browse, add to cart, checkout, and then see a page confirming their purchase: the 'thank you' page. That last step is changing, and this is no small change as it threatens to break how many sites measure purchases. Ecommerce stores that stop using a final 'thank you' page without adjusting their analytics setup accordingly are in danger of getting inaccurate purchase data, or even losing track of shoppers altogether. In order to help our customers get ahead of the curve, we've gone through a number of test cases to find short and long term fixes to this issue. But first, a little history. In the old days... In the early days of ecommerce the biggest barrier during checkout was trust. Retailers paid to be certified as ‘hack-proof’ and customers wanted to make quite sure when and how their money was taken. Fast forward twenty years to today, and in the developed world most consumers have transacted online hundreds of times. They are familiar with the process, expect a seamless user experience, and confident that when they click 'buy' their payment will be taken and the products delivered. Online shoppers are so confident, in fact, that an increasing number we observe don’t even bother waiting for that ‘thank you for your order’ page. That page is becoming redundant for three reasons: Almost every checkout process captures an email address to send an order receipt to, and the email acts as a better type of confirmation: one that can be searched and referenced. Seriously, when was the last time you opted to ‘print the confirmation page’ for your records? Many retailers are forced to compete with the superb customer support offered by Amazon. This includes refunds for products that were ordered in error, and quick handling of failed payments. So from a customer's perspective there’s little point in waiting for the confirmation page when any issues will be flagged up later. Which leads to the third reason: as retailers improve the speed of checkout, the payment confirmation step is often the slowest, and so the one where customers are most likely to drop out on a slow mobile connection. This is no small issue, as mobile revenues are expected to overtake desktop revenues for ecommerce businesses globally this year. What does this mean for ecommerce sites? The issue is that for many sites the linking of sales to marketing campaigns is measured by views of that ‘thank you' page. In the marketing analysis, a ‘purchase’ is really a view of that 'thank you' page - or an event recorded on the customer’s browser with the sale. If customers don’t view the page, then no sale is recorded. If you have ever been frustrated by the lack of consistency between Google Analytics and your own payment/back-end records, this is the most likely issue. A dependency on viewing the 'thank you' page brings other problems too: a buggy script, perhaps from another marketing tag, will block the recording of sales. This is another source of the type of analytics inaccuracy which the Littledata app combats automatically. How to adjust your ecommerce tracking The short-term fix is to tweak the firing order of marketing tags on the 'thank you' page, so that even customers who see the page for fractions of a second will be recorded. Sites with a large number of marketing tags will have the greatest room for improvement. But in the long term, as this trend continues, the analytics solution is to link the marketing campaigns to the actual payments taken. This removes the need for the customer to see any type of 'thank you' or confirmation page, and also removes discrepancies between what your marketing platform tells you was purchased and what actually got bought. This is known as server-side tracking. The good news for those of you on the Shopify platform is that our Shopify reporting app does this already - and solves a lot of other analytics problems in one install. For those on other stores, please do contact us for advice. The Littledata team has worked with ecommerce businesses to set up integrations with Magento, DemandWare and numerous custom platforms. Not only can we help fix your analytics setup for accurate tracking, but our app then automates the audit and reporting process for all of your sites going forward.

Are you a digital marketing agency looking for new reporting solutions? As our agency partnerships continue to grow, we thought it would be useful to outline how Littledata's custom reporting helps forward-thinking agencies cut down on reporting time, visualise data and improve performance for their clients. The marketing landscape is complex, but your reporting doesn't have to be overly complicated. With such a wide range of channels and sites to track, many agencies struggle to find the best analytics tools. To you we say: Welcome, you've finally found a solution that both simplifies and enhances the reporting process. Smarter reporting and accurate analytics Do you produce regular campaign performance reports in Excel or Google Sheets for your clients? Have you rejected other reporting solutions as being too rigid or complex for your needs? Then Littledata’s custom reports could work well for you and your clients. We automate the data fetching and calculations you currently run manually, and display the results to clients in a streamlined web app. We'll even show you the most important metrics, and report on key changes - automatically. One key advantage over tools such as Tableau, Data Studio or Chartio is that you can define a template report and then roll it out for many different web properties (or segments of websites) with the click of a button. Compared with other solutions you may have considered we also offer: Full support in data setup, report design and client onboarding Branded report packs for your clients and customers Complete life cycle data on your clients' customers, from marketing attribution to repeat purchases (including for subscription-based businesses) 1st line support to end users Flexibility to calculate any metrics (using Google Sheets in our processing pipeline) Comparison to industry benchmarks for sales, marketing and web performance - or create private benchmarks amongst your own client base Actionable insights for any online business to improve marketing ROI and increase conversions, whether one large ecommerce site or a series of micro-sites Integration of Google Analytics with Google Search Console data for powerful SEO reports We’re also open to discussions about white-labelling the Littledata app. This type of partnership works best for agencies with at least 20 clients ready to take advantage of our intelligent analytics tools. Please contact us if you’d like a demo, to see how this has worked for existing customers, or to discuss a particular client’s needs. Get ready to love your analytics :)

If you're tracking multiple sites or apps in Google Analytics, you can connect all of these views to your Littledata account and easily switch between them. Watch this quick video to learn how to add or remove a Google Analytics data source in the Littledata app. FAQs - Working with multiple Google Analytics views How do Littledata reports link to Google Analytics views? When you click to set up another site you will see a list of all the Google Analytics properties and views linked to your Google account. Typically you will only be interested in one of the views, which contains data for the site or app you are working on. When you select a view, Littledata fetches the data it needs to enable core features such as our intelligent Google Analytics audit and industry benchmarking. Note that this doesn't commit you to purchase anything. The underlying data in your Google Analytics account is not affected unless you opt-in to our automated fixes, which let you automatically fix particular aspects of your Google Analytics setup. How many websites or apps can I track? You can set up standard reporting for as many websites as you like. However, if you're using Littledata's Pro services for advanced custom reporting, this is priced per view or data source. You can switch between these sites using the drop-down menu in the top bar. Does your reporting work with mobile app properties? Right now, some of the features will work - such as dashboards, alerts and buyer personas - but audit and benchmarking are specifically for websites. How do I add or remove a site? Once you've connected multiple web properties to your Littledata account, you can manage them using the My Sites page under the profile photo drop-down menu in the upper right. Can Littledata handle micro-sites? Yes. If each micro-site have it's own Google Analytics view, then go ahead and connect them all to your Littledata account. If the micro-sites are all under one web view, then ask the Littledata team about custom solutions to create a multi-site dashboard that lets you visualise Google Analytics data from many micro-sites and benchmark against each other. We have done this for a range of customers and are happy to discuss the details of what is involved in reporting on multiple micro-sites, whether just a few or several hundred!

Here at Littledata we believe that everyone should have access to professional-level analytics tools for tracking, reporting, and improving sales and engagement. That's why we built the ultimate Shopify reporting app. Shopify is one of the best ecommerce platforms on the planet, but their standard analytics are extremely limited. Even if you have a Shopify Plus plan with Acquisition and Behaviour reports, this default reporting misses out on essential metrics for understanding how to improve sales and conversions on your site. How can you expect to improve marketing ROI without marketing-channel attribution for every type of sale in your store? How can you expect to increase sales without a clear picture of shopping cart behaviour? And how can you grow a business unless you understand what share of your sales comes from repeat buying versus new customers? Here's a table detailing what you can track with the Littledata Shopify app: Shopify's Standard Tracking vs Littledata for Shopify Standard Tracking in Shopify The Littledata Shopify App  Essentials Transaction volumes in Shopify match volumes in Google Analytics  ✓ Sales attribution to the source of the visit (marketing channels and other sources)  ✓ Track what pages users see  ✓  ✓ Demographics tracking (age group, interests, etc.)  ✓  Ecommerce behaviour Track what lists are viewed divided by category  ✓ Track the product position in a list  ✓ Track the clicks on products in a list  ✓ Track the product page views  ✓  ✓ Track what products are added to cart  ✓  ✓ Track what products are viewed in the cart  ✓ Analyse the data by product variants (colour, size, etc.) ✓ Track checkout steps (cart, billing, shipping, payment)  ✓ Analyse what order coupons / discount codes perform best  ✓  ✓  Recurring payments Track ReCharge renewals  ✓ Differentiate ReCharge sales from normal sales  ✓  Extra accuracy Deduct returns from total transactions  ✓ Track in Google Analytics by User ID from Shopify  ✓ Exclude traffic from payment gateways like paypal.com  ✓ Exclude spam traffic from Google Analytics data set  ✓ Capture on-site search terms  ✓ Store currency matches Google Analytics currency  ✓ Store timezone matches Google Analytics timezone  ✓ The Littledata app makes all of this remarkably easy. It guides you through the correct Google Analytics setup for your Shopify store, then provides curated reports and analytics to help you make sense of your new stream of reliable data. You don't have to be a Google Analytics expert to use Littledata's Shopify app. In fact, the app works best for product and marketing teams that are eager to learn about the big power of little data. We simplify the setup process and streamline the reporting process. It's that simple. Try it today for free in the reporting section of the Shopify App Store and see for yourself!  

Last night we gave a live demo of the Littledata app at TechHub London's Tuesday demo night. It's always exciting to share Littledata with other entrepreneurs and business owners, and to get their feedback about Google Analytics issues (everybody has some!). But in this post I'm putting our app aside for a moment in order to share some thoughts on the other company demos from the event. After all, isn't sharing feedback and ideas what the TechHub community is all about? My Film Buzz MyFilmBuzz is an early stage mobile app – launched eight weeks ago with 150 users. The user interface is really intuitive; making use of great visuals from movies and Tinder-style swiping to rate movies. The commercial problem is competing with established players like Rotten Tomatoes with big established audiences. Can a better interface tempt film viewers away? HeathClub TV HeathClub TV offers personalised training videos and exercises, selling via personal trainers who create their own profile and packages. A bit like Udemy for personal training courses, the trainers take a cut of the course fees. Again personal fitness is a very competitive market – the founder said one competitor spent £1.5m on their first version mobile app. I’ve personally enjoyed the 8-fit mobile app, with a similar mix of video exercises but without the marketplace for trainers to produce content. It will be interesting to see if the user generated content model wins out in this market. Trevor.io Trevor helps companies visualise data sources from their own business, such as SQL databases. The user interface makes a good job of simplifying a complex task, switching between table and graph views. As a data geek, I love it! We thought about a similar product in the early stages of Littledata, so my big question is: how many users have the analytical knowledge to create the data integrations, but aren’t comfortable using SQL or similar. At Littledata, most of our analysts progress to coding, because it makes them quicker to do the analysis – but then we are an unusually techy company. Grocemania Grocemania allows customers to place orders from local retailers, charging a small delivery fee (£2.50) and small minimum order (£10) subsidised by 15% commission from the retailers. They have launched a pilot in Surrey with nine retailers. The strategy seems to be to undercut other delivery companies, with lower delivery costs from freelancers and passing stock control onto the retailers. The presenters got a groan for highlighting how they reduce employment costs, but my real concern is how they can profitably undercut companies like Amazon who are ruthless pros at retail and delivery. Worksheet Systems Similar to Trevor, Worksheet Systems aims to solve the problem of storing lots of data in interconnected spreadsheets. Their idea is to split the user interface and database inherent in a complex spreadsheet, and present as a kind of Google Sheet – rather than the customer building an actual database. It looks really powerful, but I wasn't clear what it can do that Google Sheets doesn’t; we use Sheets for lots of smaller ‘databases’ in Littledata, and it’s both simple and powerful. Crowd.Science Crowdfunding for scientific projects, helping scientists raise money from individual donations, business sponsorship and charitable trusts. They take 5 – 10% commission of the money raised. It seems like a great model: crowdfunding is well proven in other areas, and some scientific projects have real public benefit. As the trustee of a grant-giving trust, I know the way we find projects is fairly inefficient, so this platform would be a great benefit as it takes off. Realisable Realisable is an Extract, Transform and Load (ETL) tool, with a visual business rules editor to transform a data source. Their live demo uses a job to transform unshipped orders from Shopify into a format that can be exporting to an accounting package, adding a customer ID to the transactions. I investigated this market in 2016, and there are some very big companies in the ETL market. Many of their products suck - a great opportunity - but there are ones with better user interfaces like Stitch Data. Talking to the founders afterwards, their strategy is to dominate a channel (in their case, Sage consultants); I know this has really worked for another ETL tool, Matillion for Amazon RedShift. Conclusion What’s my favourite idea (outside of Littledata)? Crowd.Science has the biggest potential commercially I think, but I do love Trevor’s product.

This week we're excited to introduce Buyer Personas, a game-changing new feature for marketers and ecommerce teams that are serious about hacking growth at a major scale. Do you know which types of customers are most likely to convert? Gathering customer data is one thing, but turning it into actionable insights is another. We've found that Littledata users are often struggling to find the exact differences between web visitors that buy and those that don't buy, especially when it comes to particular marketing channels. Littledata's new Buyer Personas feature automatically generates user personas based on your particular Google Analytics ecommerce setup or conversion goals, making it easier than ever to target your marketing and on-site content at those shoppers most likely to engage, convert, and grow with your online business in the long term. For example, if you know that users who arrive on your site on the weekend, in the afternoon are more likely to buy, then you should allocate more of your budget to those times. Or if users on tablets are most likely to convert, then target campaigns and ad formats most relevant for that screen size. Accurate Data If you have a decent Google Analytics setup it is possible to look at how different attributes of the user (age, browsing device, time of visit, etc.) affect their likelihood of converting. The better the data setup for your 'people analytics', the more detailed the report can be – when's the last time you audited your website's Google Analytics setup? Buyers or Users? We’re calling the new feature Buyer Personas since this is often requested by retail customers, but it is equally relevant if you have another conversion goal (eg. registrations, event bookings). In all of these cases, your customers are essentially 'buying in' to your product or service. You can switch the conversion metric at the bottom of the Buyer Personas page in the app. Marketing Channels Buyer personas give you actionable insights on particular channels, such as paid search, while also improving your overall understanding of your ideal customer base. The feedback is split out by channel so you can action it more easily: how you would re-organise your paid search marketing is very different to how you re-target your email marketing, but both are needed. The reality is that most smaller websites won’t have any of the ideal people of their site. We are not saying that only that exact profile will convert but that, by targeting the marketing on those who convert most easily, you can improve your return on investment. Pick the category with the biggest potential audience first. The first iteration of the new feature is live in the app this week. We look forward to hearing your feedback! Note that to generate Buyer Personas, you will need an active conversion goal or ecommerce tracking setup, and a minimum of 50 conversions in the previous month. Don't have a Littledata account yet? Sign up today to fix your Google Analytics setup for free and start generating buyer personas.

[embed]https://www.youtube.com/watch?v=I3c8OuqDj_8[/embed] Watch this quick video to learn how to install our Google Analytics Shopify app. The popular reporting app makes it easy to get better Google Analytics data about your Shopify store. To install Littledata's Shopify app and start trusting your data, follow the easy steps in the video: Get the app Authorise Google Analytics (GA) access Pick the existing GA data for your site Our app runs the migration process on your store Swap in Littledata's tracker (in your Shopify store admin) Confirm and go live! This video covers the basic setup process for fixing your data collection and setting up accurate tracking. But that's only the beginning of what the app can do for you. Once you've successfully installed the app and fixed your analytics setup, we recommend making daily use of your new analytics dashboard, setting up custom reports and alerts, and checking out relevant ecommerce benchmarks. Shopify stores love how the app automatically shows you the most important metrics for your sales and marketing. With a clear view of the complete user lifecycle -- from marketing channel engagement, to shopping cart activity, to repeat buying -- the sky's the limit!

Our customers come from a range of industries, but when they first come to the Littledata app for help with fixing their analytics, they share a lot of common questions. First of all, is Google Analytics accurate? How do you know if your Google Analytics setup is giving you reliable data? In this blog post we look at common problems and explain what can be done to make your tracking more accurate. Google Analytics is used by tens of millions of websites and apps around the world to measure web visitor engagement. It won’t measure 100% of visitors – due to some users opting out of being tracked, or blocking cookies – but set up correctly, it should be measuring over 95% of genuine visitors (as opposed to web scrapers and bots). What are the common things that go wrong? The six most common issues with Google Analytics -- and how to resolve them 1. Your tracking script is wrongly implemented There are two common issues with the actual tracking script setup: 1) when it is implemented twice on some pages, and 2) when it is missing completely from some pages. The effect of duplicating the script is that you’ll see an artificially low bounce rate (usually below 5%), since every page view is sending twice to Google Analytics. The effect of the tracking script missing from pages is that you’ll see self-referrals from your own website. Our recommendation is to use Google Tag Manager across the whole site to ensure the tracking script is loaded with the right web property identifier, at the right time during the page load. 2. Your account has lots of spam When it comes to web traffic and analytics setup, spam is a serious issue. Spammers send 'ghost' referrals to get your attention as a website owner. This means that the traffic you see in Google Analytics may not come from real people, even if you have selected to exclude bots. Littledata’s app filters out all future spammers and Pro Reporting users benefit from having those filters updated weekly. 3. Your own company traffic is not excluded Your web developers, content writers and marketers will be heavy users of your own site, and you need to filter this traffic from your Google Analytics to get a view of genuine customers or prospects. You can do this based on location (e.g. IP address) or pages they visit (e.g. admin pages). 4. One person shows up as two or more users Fight Club aside (spoiler alert), when the same person re-visits our site we expect them to look the same each time. Web analytics is more complicated. What Google Analytics is tracking when it talks of ‘users’ is a visit from a particular device or browser instance. So if I have a smartphone and a laptop computer and visit your site from both devices (without cross-device linking) I’ll appear as two users. Even more confusingly, if I visit your site from the Facebook app on my phone and then from the Twitter app, I’ll appear as two users – because those two apps use two different internet browser instances. There's not a lot which can be done to fix that right now, although Google is looking at ways to use it's accounts system (Gmail, Chrome etc) to track across many devices. 5. Marketing campaigns are not attributed to revenue or conversions If the journey of visitors on your site proceeds via another payment processor or gateway, you could be losing the link between the sale (or goal conversion) and the original marketing campaigns. You will see sales attributed to Direct or Referral traffic, when they actually came from somewhere else. This is a remarkably common issue with Shopify stores, and that’s why we built a popular Shopify reporting app that solves the issue automatically. For other kinds of sites, the issue can often be resolved by setting up cross-domain tracking. 6. You aren't capturing key events (like purchases or button clicks) Google Analytics only tracks views of a page by default, which may not be meaningful if you have a highly interactive website or app. Sending custom events is the key to ensuring that your tracking is both accurate and relevant. Doing so is made easier with Google Tag Manager makes this easier than it would be otherwise, but you may need to speak to a qualified analytics consultant to decide what to track. If you want more certainty that your analytics is fully accurate, try Littledata's free Google Analytics audit or get in touch for a quick consultation. We <3 analytics and we're always here to help.

This is a guest post by Patrick Rauland, co-founder of the Lift Off Summit, a free virtual conference for growing ecommerce businesses. When someone starts an online store they usually look at their bank account and if they have money they go with ads. And if they don't they go with free marketing channels. And while this makes sense it isn't the best way to think about marketing and getting traction for your store. In this post, I break down the real differences between paid marketing channels and free marketing channels to help you figure out the best route to help your growing online business reach the next level of success. The Free Channels There are a lot of free channels you can use. Just to name a few there are: Search Engine Optimization (SEO) Content Marketing Facebook pages Twitter Instagram Pinterest Video marketing (YouTube) And all of these can drive traffic to your store. But you have to start building an audience on these channels first and figure that out before you start driving serious traffic to your store. This can be especially hard on some platforms like Facebook that suppress organic page posts and instead display ads. Another problem is that these strategies usually take a lot of time. One of the most effective channels for my personal blog is SEO. But it took years to get enough organic traffic. The Paid Channels There are just as many--if not more--paid channels. Here are a few: Facebook Ads Instagram Ads Twitter Ads Pinterest Ads Google AdWords Affiliate Marketing Influencer Marketing What all of these have in common is that they can help you speed up the growth of your brand & store. Speed Up Growth Building something from scratch is hard. It's hard and it's slow. Even if you have a compelling message you might only get that message in front of a few new people each day. And only a fraction of those are ready to buy your product today. Ads let you target the perfect audience. Facebook especially has robust targeting let you target interest, ages, genders, and locations. And you can target users at any point along the customer journey. Whether they've seen your site, visited a specific page, joined the newsletter, or added something to the cart. When you can target the perfect audience you're much more likely to make the sale. If you need 100 visitors to your website to make a sale. You might only need 50, 25, or maybe if you're really good just 5 visitors to make a sale with ads. With ads you don't just pay for leads. You pay for hot leads. What About Costs? The cost of running ads can actually be quite low. I interviewed Facebook marketing expert Megan Adams for Lift Off Summit, she made a really good point about starting small and testing the results: “In the beginning…start with $5 a day and see where that takes you. Or $100 a campaign.” Amber Turril, Chief Funnel Operations Strategist at White Coat Digital said: “You can start a $5/day campaign on Facebook and see where that goes. Or $10/day on Adwords.” For $5 a day. That's $125 a month. A very reasonable amount. Even if every single click-through fails you still learn something. You can tell which ads had the most compelling message based on their click through rates. You can try different copy & different images to learn what call to actions are the best for your audience. And then apply that to your eCommerce site improving the conversion rate site-wide. Break Even First All of the platforms can show you the ROI on each of the ads. And with your first ad you're likely to have a negative ROI - meaning you lost money on that ad. And that's okay. You're going to have ads that under perform. It may take you a few weeks or maybe a month to get to the break even stage. And breaking even is the goal for someone just getting into ads. Turrill continued: “Will that one dollar turn into two dollars? It will. But first go for break even. And then go for that positive return on investment.” Paying on the Backend I've mostly been talking about ads so far - partly because they're what everyone thinks of when they think of paid marketing channels. But also because they amplify what you're already doing. There is another strategy though. You can leverage someone else's audience entirely and after each sale you can pay a commission. That means there are no upfront costs. I'm talking about affiliate marketing & influencer marketing. If you have a product that people are willing to promote (and if you don't you should evaluate what you're selling) then reach out to influencers in your space. Who is in your industry that knows your potential customers. They should know their wants, needs, and desires. And they should already have an audience. If they understand your industry and they have an audience give them an affiliate code. And you can give them a commission on any sales made with their affiliate code. I interviewed eCommerce entrepreneur Pippin Williamson for Lift Off Summit and he said: "At it's core it's really other people saying good things about you." And I think that's why this channel works so well. It's a natural extension of word of mouth. The Three Ways to Grow In eCommerce there are three ways to grow: Get more customers Get your customers to purchase more (higher average order value) Get your customers to purchase more often And when you're a brand new store it's basically just one: get more customers. That's why I'm such a big fan of the paid channels. They obviously have a cost to run. And you should always work on organic methods like SEO & content marketing. But while you're gearing those up start playing with ads. You'll usually see immediate results and can continue to grow & tweak. Patrick Rauland is a public speaker, author, and blogger. He creates eCommerce content for LinkedIn Learning/Lynda.com. He loves helping people start their own businesses and take control of their own financial future.

Connecting marketing data with sales data is an age-old problem, and the crowded digital landscape has made this even more complicated. Google Analytics is supposed to give you the power to attribute sales (or purchase transactions) back to marketing campaigns, but this doesn't happen automatically. The good news is that it's entirely possible to get the right marketing channel attribution for sales activities. Accurate marketing attribution starts with the right Google Analytics (GA) setup. Start by asking yourself the following troubleshooting questions. These steps will help you figure out if your GA setup is correct, and how to use GA to get a complete view of user behaviour. Trustworthy GA setup takes a bit of work, but with a smart analytics dashboard like Littledata, much of that work can be automated. In fact, steps 1 through 4 can be checked automatically with our free Google Analytics audit tool. First of all, are you checking the right report? The best way to see the attribution is in the 'Channels' report in Google Analytics, under the 'Acquisition' section: 1. Have you got a large enough sample to compare? Firstly, can you be sure the sales are representative? If you only have two sales, and both are ‘Direct’, that could be a fluke. We recommend selecting a long enough time period to look at more than 50 transactions before judging, as with this example:   2. Is the tracking script on your purchase confirmation page setup? It you are getting some transactions recorded, but not 100%, then it may be possible to optimise the actual tracking script setup. See our technical guide to ecommerce tracking. This can be a particular problem if many of your sales are on mobile, since slower page load speeds on mobile may be blocking the tracking script more often.   3. Have you got a cross-domain problem? If you see many of your sales under Referral, and when you click through the list of referrers it includes payment gateways (e.g. mybank.com or shopify.com), that is a tell-tale sign you have a cross-domain problem. This means that when the buyer is referred back from the payment domain (e.g. paypal.com), their payment is not linked with the original session. This is almost always a problem for Shopify stores, which is why our Shopify app is essential for accurate tracking.   4. Is your marketing campaign tagging complete? For many types of campaign (Facebook, email etc), unless you tag the link with correct ‘UTM’ parameters, the source of the purchaser will not be tracked. So if a user clicks on an untagged Facebook Ad link on their Facebook mobile app (which is where 80 – 90% of Facebook users engage) then the source of their visit will be ‘Direct’ (not Social). Untagged email campaigns are a particular issue if you run abandoned cart / basket emails, as these untagged links will be 'stealing' the sales which should be attributed to whatever got the buyer to add to cart. Tagging is a real problem for Instagram, since currently the profile link is shown in full - and looks really messy if you include all the UTM parameters. We recommend using a service like Bitly to redirect to your homepage (or an Instagram landing page). i.e. The link redirects to yoursite.com?utm_medium=social&utm_source=instragram&utm_campaign=profile_link.  Read Caitlin Brehm's guide to Instagram links.   5. (only for subscription businesses using Littledata) Are you looking at only the first time payments? Tracking the source of recurring payments is impossible, if the tracking setup was incorrect at the time of the first payment. You can’t change Google Analytics retrospectively I’m afraid. So if you are using our ReCharge integration, and you want to track lifetime value, you will have to be patient for a few months as data from the correct tracking builds up.   6. Is a lot of your marketing via offline campaigns, word of mouth or mobile apps? It could be that your sales really are ‘direct’: If a buyer types in the URL from a business card or flyer, that is ‘Direct’. The only way to change this is to use a link shortener to redirect to a tagged-up link (see point 4 above). If a user pastes a link to your product in WhatsApp, that is ‘Direct’. If a user sees your product on Instagram and clicks on the profile link, that is ‘Direct’. Please let us know if there are any further issues you've seen which cause the marketing attribution to be incorrect.

We're excited to announce that Littledata's Shopify app now integrates seamlessly with ReCharge! The integration makes it easy to get an accurate data stream about your ReCharge subscriptions in Google Analytics. What is ReCharge? ReCharge is the most popular recurring billing solution for Shopify stores. It lets you easily sell subscriptions on a Shopify store. ReCharge has a robust feature set for stores selling physical products on subscription, allowing for single product, mixed cart & entire cart subscriptions. The app powers thousands of stores processing tens of thousands of orders daily, including Littledata customers like Tiege Hanley skin care and BIOHM probiotics. Until we built this new integration, ReCharge customers didn't have a way to get a complete data collection in Google Analytics without hiring expensive GA consultants. How the integration works Integrating Littledata with ReCharge lets you capture data about the entire subscriber journey, from marketing campaigns to first-time payments and recurring revenue. The integration uses Littledata's magic sauce to connect Shopify and ReCharge data to Google Analytics. The reporting includes essential information for understanding business performance: End-to-end Google Analytics tracking for the subscriber journey Marketing attribution for subscription revenue, including first-time payments and recurring charges Segmentation by payment source, subscription plan type and product category With this integration plus the power of Littledata's analytics audit tool, you ensure accurate tracking of everything in your ecommerce funnel. You can then take advantage of automated reporting to help you increase revenue, including report packs built specifically for subscription analytics. Littledata's revenue optimisation tools pull directly from your GA data. Advanced users can can also use that data directly in GA - and connect it to dashboard tools like Data Studio and Supermetrics. And the price is right! Littledata provides Google Analytics for ReCharge stores at no extra cost. It's a free integration for any Shopify store using both apps! Setup guide For the Littledata - ReCharge integration to work, you need to install both apps for your Shopify store, then connect them by activating the integration. Install ReCharge Install Littledata’s Shopify app Follow these steps to activate the integration Note that you will activate ReCharge’s basic Google Analytics integration as part of the setup process, but you need to complete the Littledata integration to get full marketing attribution and to track recurring subscriptions (not just first-time payments). For more information about how our ReCharge integration works, check out our knowledge base. If you’re looking for custom setup or help with reporting, consider one of Littledata’s enterprise plans. Higher-tier plans include a dedicated account manager and support from analytics experts. We have many happy ReCharge customers, so please get in touch if you have any special requests!   This post was updated in June 2018

So you’ve got a brand new tool in your web performance kit – Google Optimize – and now you want to put it to good use. What can you test with Optimize and how does it work? Firstly, what are the different options for setting up an experiment? AB Test Using the in-page editor you can create an altered version of the page you wish to test. This could be a change of text copy, different styling, or swapping in a different image. You can also add new scripts or HTML if you’re familiar with coding. The way this works is Optimize adds a script after the page loads to manipulate the page text, images or styles. I recommend not switching header elements or large images using this method as, depending on your website setup, there may be a noticeable flicker– try a redirection test below. You can create many versions with subtly different changes (C, D and E versions if you want) – but remember you’ll need a large volume of traffic to spot significant differences between lots of variations. You can also limit the test to a certain segment of users – maybe only first time visitors, or those on mobile devices. Multivariate Test Similar to an AB test, a multivariate test is used when you have a few different aspects of the page to change (e.g. image and headline text) and you want to see which combination is most engaging. To get a significant result, you'll need a large volume of traffic - even more than testing many options in AB tests.   Redirection Test This is where you have two different versions of a page – or a different flow you want to start users on. Optimize will split your visitors, so some see the original page and some are redirected to the B version. A redirection test is best when the page content or functionality is very different – perhaps using a whole different layout. The disadvantage is you’ll need a developer to build the B version of the page, which may limit the speed of cycling tests.   Personalisation Personalisation is not officially supported by Optimize right now, but we’ve found it to be a useful tool. You can assign 99.9% of the visitors who match certain criteria to see the alternative version of the page. An example is where you have a special offer or local store in a particular city - see our step-by-step local personalisation example. You can ensure that all the visitors from that city see a different version of the page. Unfortunately on the free version of Google Optimize you are limited to 3 concurrent ‘experiments’ – so it won’t be a good solution if you want to run similar personalisation across lots of cities or groups of users. Next the question is where to start with tests...   Start with the landing pages Landing pages get the greater volume of traffic, and are where small visual changes (as opposed to new product features) make the biggest difference to user engagement. This greater volume allows you to get a significant result quicker, meaning you can move on to the next test quicker. And keep on improving!   So what exactly could you test using Google Optimize? Here are six ideas to get you going.   1. Could call-to-actions (CTA) be clearer? Changing the colour or contrast of a key button or link on the page (within your brand guidelines) usually results in more visitors clicking it. This might involve changing the style of the CTA itself, or removing elements close by on the page – to give the CTA more space to stand out.   2. Are you giving the user too many choices? In Steve Krug’s classic Don’t Make me Think he explains how any small confusion in the user’s mind can stop them making any choice. Every choice the user has to make is an opportunity for them to give up. Try hiding one of the options and seeing if more users overall choose any of the remaining options.   3. Is the mobile page too long? As many sites move to responsive designs that switch layout on smaller screens, this has led to mobile pages becoming very long. User may get ‘scroll fatigue’ before then get to critical elements on the page. Try cutting out non-essential sections for mobile users, or editing copy or images to make the page shorter. You could also try switching sections so that the call-to-action is higher up the page on mobile – although this is harder to achieve without a redirection test.   4. Is localisation important to your users? You may have discussed providing local language content for your users, and been unsure if it is worth the costs of translation and maintenance. Why not test the benefits for a single location? As with the personalisation tests, you can show a different local language (or local currency) version of the page to half the users in the single location (e.g. Spanish for visitors from Mexico) and see if they convert better.   5. Does the user need more reassurance before starting to buy? It easier to build experiments which remove elements to the page, but you should also consider adding extra explanation messages. A common problem on ecommerce stores is that visitors are unsure what the shipping charges or timing will be before adding to cart. Could you add a short sentence at the start of the journey (maybe on a product page) to give an outline of your shipping policy? Or maybe some logos of payment methods you accept?   6. Changing header navigation If your site has a complex mix of products that has evolved over time it may be time to try a radical new categorisation – maybe splitting products by gender or price point rather than by type. For this test, you’ll want to target only new visitors – so you don’t confuse regular visitors until you’re sure it’s permanent. You will also need to make the navigation changes on all pages across the site.   Good luck! Littledata also offering consulting and AB testing support, so please contact us for any further advice.

Every business, in order to grow, needs to set up a certain number of objectives and KPI’s. Once they are set, you can actually track the way your business evolves and see if they are met or you underperformed. This is where Goals come in: the actual definition that Google has on their support page: “A goal represents a completed activity, called a conversion, that contributes to the success of your business.” In this article, I will answer to the following questions: What are Goals in Google Analytics? When should you use the Goals and what for? What are Goals in Google Analytics?   Goals are specific user actions that you can then use in other reports (such as landing pages or channels) to see whether users engaged with your website. It is really important to remember that you have a maximum of 20 goals for each Google Analytics view. Also, once you set up a Goal, it will stay set up forever in the view. You can disable goals, but you will still have them there. You need to make sure that the objectives you set up are relevant to your business and they can be monitored by using the goals. What Goals should you track and why? The four big categories that in which you can track Goals in Analytics are: URLs Time Pages per visit Custom Events The most useful of these are custom events. Here are some of the areas you should definitely consider tracking with custom events: Leads – If your site has a sign-up or contact form for enquiries you'll want to track how many users successfully complete it - especially because you want to convert those leads. Newsletter sign-ups – Newsletters are really important for many businesses, to educate the people that are interested in your business. Tracking what drives users to sign up for these emails will help you do a better at content strategy. White paper and E-book downloads – Make sure your buyers' journey is set up properly and that you make this is a priority in your objectives. By tracking these two really specific actions, you will be able to up-sell your key product, software or service. Trial sign-ups – If you follow a freemium business model or if you use the trial period in order to engage your users, then tracking this area will definitely give you insights into who is your ideal persona. This article from The Digital Marketing Institute will also show you other metrics you should monitor.   Happy Reporting. Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Being able to edit the Google Analytics account is the 2nd highest permission level. You need this if you want to create a new web property in Google Analytics. To grant permissions to another user you will need the highest permission level yourself: being able to manage users on the account. Step 1: Go to account user settings page First click the admin cog in any view under the account in GA you want to change, and then in the left hand list go to User Settings   EITHER Select an existing user from the list and click the 'edit' checkbox OR Add a new user's email (must be a Google account) and check the 'edit' checkbox. Step 3: Check it's working Your colleague should now be able to see 'Create new property' under the list of properties in the middle of the Admin page.

At the Shopify Unite conference today I heard plenty of great ideas such as ShopifyPay but the most interesting for me as a data specialist was the marketing events API. Since we launched our Fix Google Analytics Shopify app earlier this year we’ve known that reporting was a weak spot in Shopify’s platform offering, and they admit that ‘understanding marketing campaign performance’ is one of the biggest challenges of Shopify merchants right now. The ability for other Shopify apps to plug their campaign cost and attribution data into Shopify (via the marketing events API) is a logical step to building Shopify’s own analytics capability, but I don’t believe it will be a substitute for Google Analytics (GA) anytime soon. Here’s why: 1. Google Analytics is the industry standard Every online marketer has used Google Analytics, and many have favourite reports they’ve learned to interpret. Moving them to use a whole new analysis platform will take time– and it’s taken GA 10 years to achieve that dominance. 2. GA provides platform-agnostic data collection For a store using Shopify as their only source of insights, moving away from Shopify would mean losing all the historic marketing performance data – so it would be very hard to make like-for-like comparisons between the old platform and the new. Many of our customers have used GA during and after a platform shift to get continuous historical data. Which ties into my first point that over 85% of businesses have a history of data in GA. 3. Incomplete marketing tagging will still cause issues Making valid analysis on multi-channel marketing performance relies on having ALL the campaigns captured - which is why our GA audit tool checks for completeness of campaign tagging. Shopify’s tracking relies on the same ‘utm_campaign’ parameters as GA, and campaigns that are not properly tagged at the time cannot be altered retrospectively. 4. Google is rapidly developing Google Analytics I’d like to see the Shopify marketing event collection evolve from its launch yesterday, but Google already has a team of hundreds working on Google Analytics, and it seems unlikely that Shopify will be able to dedicate resources to keep up with the functionality that power users need. 5. More integrations are needed for full campaign coverage Shopify’s marketing analysis will only be available for apps that upgrade to using the new API.  Marketing Events has launched with integrations for Mailchimp and Facebook (via Kit) but it won’t cover many of the major channels (other emails, AdWords, DoubleClick for Publishers) that stores use. Those integrations will get built in time, but until then any attribution will be skewed. 6. GA has many third-party integrations Our experience is that any store interested in their campaign attribution quickly wants more custom analysis or cuts of the data. Being able to export the data into Littledata’s custom reports (or Google Sheets or Excel) is a popular feature – and right now Shopify lacks a reporting API to provide the same customisations. You can only pull raw event data back out. That said, there are flaws with how GA attribution works. Importing campaign cost data is difficult and time consuming in GA – apart from the seamless integration with AdWords – and as a result hardly any of the stores we monitor do so. If Shopify can encourage those costs to be imported along with the campaign dates, then the return on investment calculations will be much easier for merchants. I also think Shopify has taken the right pragmatic approach to attribution windows. It counts a campaign as ‘assisting’ the sale if it happens within 30 days of the campaign, and also whether it was ‘last click’ or ‘first click’. I’ve never seen a good reason to get more complicated than that with multi-channel reports in GA, and it’s unlikely that many customers remember a campaign longer than 30 days ago. In conclusion, we love that Shopify is starting to take marketing attribution seriously, and we look forward to helping improve the marketing events feature from its launch yesterday, but we recommend anyone with a serious interest in their marketing performance sticks to Google Analytics in the meantime (and use our Shopify app to do so).

Smart goals measure the most engaged visits to your website and automatically turn those visits into Goals, even if you don't have conversion or ecommerce tracking. Then use those Goals to improve your AdWords bidding. This article will explain exactly what smart goals are and how to use this feature. I need to start by saying that if you want to use Smart Goals you need to have an Adwords account linked to your Google Analytics in order to enable this feature and you need Edit permission at the view level in order to get the setup done. Also, the linked AdWords account must have sent at least 500 clicks to the selected Analytics view over the past 30 days before you can set up Smart Goals. (If the linked account falls below 250 clicks over the past 30 days for the selected view, Smart Goals will be deactivated until the clicks rise again to 500 or more) Smart goals are recommended to be used when you aren't measuring conversions. Smart Goals is an easy way to use your best sessions as conversions. You can then use Smart Goals to optimize your AdWords performance based on the 'best sessions' pattern. Smart Goals are configured at the view level. Smart Goals feature from Google Analytics is the result of machine learning technologies. These algorithms will examine dozens of signals about your website sessions to determine which of those are most likely to result in a conversion. Each session is assigned a score, with the "best" sessions being translated into Smart Goals. Some examples of the signals included in the Smart Goals model are Session duration, Pages per session, Location, Device and Browser. (Remarketing Smart Lists use a similar machine learning model to identify your best users.) To determine the best sessions, Smart Goals establishes a threshold by selecting approximately the top 5% of the traffic to your site coming from AdWords. Once that threshold is set, Smart Goals applies it to all your website sessions, including traffic from channels other than AdWords. After enabling Smart Goals in Analytics, they can be imported into AdWords. Instructions for setting up Smart Goals If your view is eligible, you can enable Smart Goals by selecting the Smart Goal goal type when following the regular goal setup flow: Sign in to Google Analytics. Click Admin, and navigate to the desired view. In the VIEW column, click Goals. Click + NEW GOAL. Select Smart Goal (if available). Give your Smart Goal a name and click Save. No additional configuration or customization is required. (That's part of the reason why we call them "Smart Goals.") Instructions for importing Analytics smart goals into AdWords After you've activated Smart Goals in Analytics, sign in to your AdWords account, click the Tools tab, and select Conversions. Click Analytics in the left-hand menu. Check the boxes next to the goals or transactions you want to import. Click Continue. On the next page, you'll see settings that will apply to all of the goals or transactions you selected. Make your choices, then click Import goals. Click Close, or to import more goals, click Import more. AdWords will begin importing the data from your Analytics account. Historical data from before the import won't be included. The Smart Goals report To help you see how Smart Goals perform, use the Conversions > Goals > Smart Goals report. This report shows you how your Smart Goals traffic differs from other traffic. You can also include the Smart Goals Completed dimension in custom reports. The Smart Goals report shows you how Smart Goals would perform even before enabling them in your view (assuming you are eligible to use Smart Goals in the first place). This lets you determine if Smart Goals will be of benefit to you before going through all the steps above. Both the Smart Goals report and the Smart Goals Completed dimension are only available in views which are eligible for Smart Goals.   Interested in getting help with any of these features? Get in touch with our experts and we’d be happy to help!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

This is the third article in the Q&A series. I will be answering some of the most-asked questions about Google Analytics and how it works. If you’ve missed the previous articles, you can access Part 2 (What is the bounce rate in Google Analytics) and see what questions we answered there. In this article, I will give you an answer to the following questions: How Google Analytics works for mobile apps? What are the differences between Firebase Analytics and Google Analytics? How Google Analytics works for mobile apps? Instead of using JavaScript, for mobile apps, you will be using an SDK. That is a Software Development Kit and it’s what collects the data from your mobile application. As most smartphones are either Android and iOS based, you will have different SDK’s based on the operating system. The SDK works similarly as the JavaScript and collects data like the number of users and sessions, the session duration, the operating system, the device model and the location. All of that is packed in hits and sent to your Google Analytics account. Here is an overview from The Google Analytics Help Center. The main difference is that the data is not sent right away. Because a mobile device might not have a connection to the internet at some points in time, the data is stored on the device and is sent when it is eventually connected. The process is called dispatching and it’s done at different time intervals on Android and on iOS. On Android, the hits are dispatched every 30 minutes and on iOS, every 2 minutes. Those numbers can be customised though. Keep in mind that you can customise the code so that you can track different data in case you feel the base code is not sufficient for you. What are the differences between Firebase Analytics and Google Analytics? Firebase Analytics (FA) is another way to collect the event data. While Google Analytics is a general-purpose (and more web oriented) analytics tool, Firebase was built keeping mobile in mind. There are some things that were added in in the later and also things that are missing from GA. Here are some noteworthy points when considering Firebase Analytics: Real-time view is missing for Firebase Analytics (we mainly use this when testing the app for new events). Events are available after 4 to 6 hours in Firebase Analytics. The Behavior Flow is missing from Firebase Analytics (since there are no screen views logged). The Audiences feature is a big advantage that FA has. If you couple this with the Notifications it will allow you to engage with a specific group of users. If users experience a crash, then an audience group will be created automatically when using the Firebase Crash Reporting feature. Funnel analysis based on custom events is easier in FA. However, if you use Littledata, then this problem can be solved for Google Analytics with the custom reports that we can build. Some events are logged automatically in Firebase Analytics (for example the sessions based on the Activity life-cycle). Firebase has a relatively low methods footprint compared to the methods count that Google Analytics uses - making it less processor and network intensive. As a final point there are benefits for using both platforms to track your Analytics, but if you do focus your business on mobile applications, keep in mind that Firebase Analytics was created for mobile apps. Happy Reporting. Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If you got this email from Google recently, or seen the blue notification bar at the top of Google Analytics, here's what is changing and how it affects your website. The big problem in modern online marketing is that most users have multiple devices, and the device they interact with the advert on is not the same as the one they convert on: [Google’s] research shows that six in ten internet users start shopping on one device but continue or finish on a different one. Facebook has been helping advertisers track conversion across devices for a few years  - because most Facebook ads are served on their mobile app, when most conversion happens on larger screens. So Google has been forced to play catch-up. Here’s the message from the Google Analytics header: Starting May 15, 2017, all properties using Remarketing with Google Analytics will be enhanced to take advantage of new cross-device functionality. This is an important update to your remarketing settings, which may relate to your privacy policy. The change was announced last September but has only just rolled out. So you can remarket to users on a different device to the one on which they visited your site when: You build a retargeting audience in Google Analytics You have opted in to remarketing tracking in Google Analytics Users are logged into Google on more than one device Users have allowed Google to link their web and app browsing history with their Google account Users have allowed Google account to personalise ads they see across the web This may seem like a hard-to-reach audience, but Google has two secret weapons: Gmail (used by over 1 billion people and 75% of those on mobile) and Chrome (now the default web browser for desktop, and growing in mobile). So there are many cases where Google knows which devices are linked to a user. What is not changing is how Google counts users in Google Analytics. Unless you are tracking registered users, a ‘user’ in Google Analytics will still refer to one device (tablet, mobile or laptop / desktop computer).   Could Google use their account information to make Google Analytics cross-device user tracking better? Yes, they could; but Google has always been careful to keep their own data about users (the actions users take on Google.com) separate from the data individual websites capture in Google Analytics (the actions users take on mywebsite.com). The former is owned by Google, and protected by a privacy agreement that exists between Google and the user, and the latter is owned by the website adding the tracking code but stored and processed by Google Analytics. Blurring those two would create a legal minefield for Google, which is why they stress the word ‘temporary’ in their explanation of cross-device audiences: In order to support this feature, Google Analytics will collect these users’ Google-authenticated identifiers, which are Google’s personal data, and temporarily join them to your Google Analytics data in order to populate your audiences.   How can I make use of the new cross-device retargeting? The first step is to create a remarketing audience from a segment of your website visitors that are already engaged. This could be users who have viewed a product, users who have viewed the pricing page or users who have viewed more than a certain number of pages. For more help on setting up the right goals to power the remarketing audience, please contact us.

I’ve read many articles stating a link between faster page loading and better user engagement, but with limited evidence. So I looked at hard data from 1,840 websites and found that there’s really no correlation between page load speed and bounce rate in Google Analytics. Read on to find out why. The oft quoted statistic on page load speed is from Amazon, where each 100ms of extra loading delay supposed to cost Amazon $160m. Except that the research is from 2006, when Amazon’s pages were very static, and users had different expectations from pages – plus the conclusions may not apply to different kinds of site. More recently in 2013, Intuit presented results at the Velocity conference of how reducing page load speed from 15 seconds to 2 seconds had increased customer conversion by: +3% conversions for every second reduced from 15 seconds to 7 seconds +2% conversions for every second reduced from seconds 7 to 5 +1% conversions for every second reduced from seconds 4 to 2 So reducing load speed from 15 seconds to 7 seconds was worth an extra 24% conversion, but only another 8% to bring 7 seconds down to 2 seconds. Does page speed affect bounce rate? We collected data from 1,840 Google Analytics web properties, where both the full page load time (the delay between the first request and all the items on the page are loaded) and the bounce rate were within normal range. We then applied a Spearman’s Rank Correlation test, to see if being a higher ranked site for speed (lower page load time) you were likely to be a higher ranked site for bounce rate (lower bounce rate). What we found is almost no correlation (0.18) between page load speed and bounce rate. This same result was found if we looked at the correlation (0.22) between bounce rate and the delay before page content starts appearing (time to DOM ready) So what explains the lack of a link? I have three theories 1. Users care more about content than speed Many of the smaller websites we sampled for this research operate in niche industries or locations, where they may be the only source of information on a given topic. As a user, if I already know the target site is my best source for a topic, then I’ll be very patient while the content loads. One situation where users are not patient is when arriving from Google Search, and they know they can go and find a similar source of information in two clicks (one back to Google, and then out to another site). So we see a very high correlation between bounce rate and the volume of traffic from Google Search. This also means that what should concern you is speed relative to your search competitors, so you could be benchmarking your site speed against a group of similar websites, to measure whether you are above or below average.   2. Bounce rate is most affected by first impressions of the page As a user landing on your site I am going to make some critical decisions within the first 3 seconds: would I trust this site, is this the product or content I was expecting, and is it going to be easy to find what I need. If your page can address these questions quickly – by good design and fast loading of the title, main image etc – then you buy some more time before my attention wanders to the other content. In 2009, Google tried an experiment to show 30 search results to users instead of 10, but found the users clicking on the results dropped by 20%. They attributed this to the half a second extra it took to load the pages. But the precise issue was likely that it took half a second to load the first search result. Since users of Google mainly click on the first 3 results, the important metric is how long it took to load those - not the full page load.   3. Full page load speed is increasingly hard to measure Many websites already use lazy loading of images and other non-blocking loading techniques to make sure the bare bones of a page is fast to load, especially on a mobile device, before the chunkier content (like images and videos) are loaded. This means the time when a page is ready for the user to interact with is not a hard line. SpeedCurve, a tool focussed entirely on web page speed performance, has a more accurate way of tracking when the page is ‘visually complete’ based on actual filmstrips on the page loading. But in their demo of The Guardian page speed, the page is not visually complete until a video advert has rendered in the bottom right of the screen – and personally I’d be happy to use the page before then. What you can do with Google Analytics is send custom timing events, maybe after the key product image on a page has loaded, so you can measure speed as relevant to your own site.   But doesn’t speed still affect my Google rankings? A little bit yes, but when Google incorporated speed as a ranking signal in 2010, their head of SEO explained it was likely to penalise only 1% of websites which were really slow. And my guess is in 7 years Google has increase the sophistication with which it measures ‘speed’.   So overall you shouldn’t worry about page load times on their own. A big increase may still signal a problem, but you should be focussing on conversion rates or page engagement as a safer metric. If you do want to measure speed, try to define a custom speed measurement for the content of your site – and Littledata’s experts can work with you to set that custom reporting up.

The bounce rate is number of web sessions where the user left your site after viewing just one page. It is a key measure for landing page engagement. This is the second article in the Q&A series. As I previous mentioned, I am going to continue answering some of the most-asked questions about Google Analytics and how it works. If you want to get an idea of how this works, you can visit PART 1(Pros and cons of using Google Analytics) of the series and see what questions we answered there. Here are the questions we will be tackling in this second article of the series: 1) What is the bounce rate in Google Analytics? 2) How is the Bounce rate calculated? 3) What is an ideal bounce rate? 1) What is the bounce rate in Google Analytics? The definition of the Bounce Rate as shown in the Google Analytics Help Centre is “the percentage of single-page sessions. Those are sessions in which the person left your site from the entrance page without interacting with any other page”. Why is this metric important? A high bounce rate shows you may have some problems on your website. Remember that the bounce rate is correlated to the content of your website and should be considered in the context of the purpose of the website. If you have a content website, a services website or an ecommerce website you need to look at the bounce rate in the big picture and analyse it using Advanced Segments to look at a specific category of pages, and see how they’re performing vs other sections. Some reasons for a high bounce rate are: Single page website: where the user never leaves the first page through their whole visit. A high bounce rate, in this case, is actually irrelevant: you should focus on how many visitors. In order to find out how people interact with your website, you can track Custom Events on the page. To get an accurate bounce rate in this case you need to set up the events as "interaction hits". Incorrect implementation: for a multiple page website, in order to track all the pages, you need to add a specific tracking code on all of the pages for a correct read of the data. In case the bounce rate is high, that might show that the tracking code is not correctly applied to all pages of the website. User Behaviour: the people that arrived on your site and left without doing anything else, either because they found the information that they wanted on that page and there was no need to access other pages or they simply entered by accident and didn’t find what they needed. Also if a user has a page bookmarked, enters the page and then leaves, that’s also counted as a bounce. Site design: when the implementation is done properly then you really might have a problem with the way the content is displayed. In this case consider looking at the landing pages, as they might not do justice to the content. Also, the keywords or ads that you use, might not reflect the content of your website and because of that, you need to optimise either the content or the keywords and ads. 2) How is the Bounce rate calculated? In Google Analytics, there are two indicators for the Bounce Rate. There is the Bounce Rate of a Web Page and then there is the Bounce Rate of a Website. The Bounce Rate of a Website is the total number of bounces across all of the pages on the website over the total number of entrances across all the pages on the website (both over the same determined period of time). This is represented in Google Analytics as a percentage shown in the table of all the pages displayed. The Bounce Rate of a Web Page is the total number of bounces on a page over the total number of entrances on the page (Both over the same determined period of time). The image above shows the equation for calculating it. This is also represented as a percentage but it is shown in the table for each page separately. Here is an article from OptimizeSMART in which they show us how to improve our bounce rate. 3) What is an ideal bounce rate? As I previously explained, the bounce rate should be as low as possible. In one of his articles, Avinash Kaushik who is a guru of Analytics tells us what the ideal bounce rate should be: “As a benchmark from my own personal experience over the years, it is hard to get a bounce rate under 20%. Anything over 35% is a cause for concern and anything above 50% is worrying.” To recap, in this article we managed to see what the Bounce Rate is, how it’s calculated and what is the ideal bounce rate we should strive for with our website. Make sure to check part 3 out, in which we will answer more questions about Google Analytics. Happy Reporting. Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Fix Google Analytics is a Shopify app that gives you 100% accurate tracking and attribution for your Shopify sales. If you want to uninstall the app, you will no longer get the full Enhanced Ecommerce reporting, but you must take further steps to re-enable the original tracking. 1. In Shopify admin -> Apps -> click the Trash Can next to the app This first step will only stop the transactions from being sent to the Google Analytics property. This means that if you click the trash can, you will no longer receive any transaction information in your Google Analytics account (under Conversions -> Sales Performance), even though the sessions and page views are still working.   2. Remove the Littledata script from your page template (Only relevant if you installed the app after 26th of March 2017) Click Online Store ->Themes -> Edit HTML/CSS In this new window, under the Layout folder, for each 'theme' file you need to find this line of code: "{% include 'LittledataLayer' %}" and then delete it. This will stop Littledata sending page views to Google Analytics. 3. Add back in the standard Shopify tracking Go in Shopify Admin -> Preferences -> Google Analytics section and type or paste in the Google Analytics web property. Your original Google Analytics web property ID starts with UA- and can be found in Google Analytics first screen where you choose your account. 4. Remove the Littledata test Google Analytics property Only applies if you clicked 'FIX' after installing the app Go to you Google Analytics account, and click the Admin cog on the bottom left. Find the (Littledata) web property in the middle list. Then under Property settings -> Move to Trash Can is in the top right of the settings.   By completing these steps, you will have successfully uninstalled the app. Warning: If you are seeing double counting of pageviews in Google Analytics, or your bounce rate has dropped significantly, then that is a sign you have completed step 3 but not step 2. Regardless of the reason behind you uninstalling the app, we would love to hear about it. Just drop us a line at support@littledata.io.  This feedback helps us provide the best possible experience to other stores.

Recurring billing & subscriptions have proved to be, at least in the last few years, the most viable model of business. The return on investment, value per customer and frequency of buying are all higher for any business that adopted a recurring subscription model. This article is focused on Shopify stores that use apps like ReCharge solution and Fix Google Analytics - Littledata app. Nonetheless, everything in here can be applied to all recurring payments business models. Recharge is the most used Shopify recurring billing solution powering thousands of stores and processing tens of thousands of orders daily. Fix Google Analytics - Littledata app completes ReCharge app by providing accurate sales attribution through Google Analytics. If you don't know what the Fix Google Analytics - Littledata app does, here is a short description: We fix your data collection, offer marketing insights and suggest improvements all in one app. Say goodbye to inaccurate data and start getting the full Enhanced Ecommerce experience. Install this app to get: Proper marketing attribution in Google Analytics Product views and shopping behavior Checkout conversion funnels (including voucher usage) Understanding of repeat buyers The first steps to install the Google Analytics tracking for Shopify are illustrated here: How to install the “Fix Google Analytics” Shopify app. Besides this, if you want to go ahead and make an advanced analysis of your customers then you need to make the following setup also: Enable the feature in Google Analytics Firstly, go into Google Analytics (both your normal Google Analytics property and the property that has been created by Littledata) and enable the User-ID feature by going to Admin > Property > Tracking info > User-ID. Click On, next, On, next, give the new view a name and you're done. Attention: The new view will start to collect data from the point of creation so you will need to wait a bit to use this report. The sources of the purchases will be collected from the point of creation so most of the orders will be shown in the first month from direct / (none). Enable the Enhanced Ecommerce feature in Google Analytics Go in Google Analytics, Click Admin. In the right side under view choose the new Registered Users view, that you've created earlier and click Ecommerce Setings. Toggle to ON and then click Next step. Toggle ON for Enhanced Ecommerce, save and you're done. How to see what was the initial source for recurring subscriptions? Using the registered view go under ACQUISITION -> All traffic -> Source/Medium or Channels. This report will show both new customers and recurring ones. We need to apply a segment to this report in order to show only the recurring users. This is how you set up the segment to exclude first time buyers: Now, with the above segment applied, you can check what was the original source or the sale for all transactions from repeating buyers. The other cool and helpful report is the AUDIENCE->Cohort Analysis report. You can see what was the retention of these users in this report for each day, week or month. This report must be read from left to right for the bellow image: Users that bought in December continued to buy in January in a proportion of 38% and in February in a proportion of only 10%. Combining this report with an advanced segment that excludes the first-time buyers AND includes only buyers that had their first transaction in December will provide the number of users that started the subscription package in December and what was the retention of these people. We would love to hear how you use these reports and what you think of the new version of our Fix Google Analytics - Littledata app.

We've decided to start a series of content to answer basic questions you may have regarding Google Analytics. These are readily available but sometimes over complicated and we're experts at both analytics and making things simple. Hopefully, these blog posts will help clarify any questions you may have. In Part 1, we will be discussing: When to use Analytics? Pros and cons of using Google Analytics. 1. When to use Analytics? These days, everything on the internet is connected. Have you ever questioned how websites know your location and redirect you to the page of that specific location? Or have you ever seen those ads that appear all the time after you visit a specific website? That’s due to cookies, which are a set of parameters that get collected and interpreted. They are part of Digital Analytics or Google Analytics, which is a set of measurements that helps you in understanding which people you reach with your website and how your website performs. By performance, we refer to who is visiting your website, how someone interacts with your website, the decisions they take following those interactions and much more. Ultimately, you want to use Google Analytics whether you own a website, you're an online shop or if you are a marketer, in order to increase the marketing and sales efforts of the platforms you are using. If you are still not convinced that Analytics is a must have for an online property, check this article from AnalyticsNinja and you'll get an even deeper dive into why you should you use Analytics. 2. Pros and cons of using Google Analytics: Google Analytics is one of the most known and used tools to track Digital Analytics. There are definitely a lot of pros to using it but there are also some drawbacks. Pros: It’s free of charge so everyone can use it. You can use it on different digital environments such as websites, mobile applications, kiosks, or anything that has an internet connection There's a Google Analytics Academy, where you can get in-depth information and get educated about how to use it. You can connect your Google Analytics account with your AdWords account. You can also collect data from different platforms and sources. You can create custom goals and you can also track your ecommerce platform. You can create custom reports based on your needs. This way you can track specific information depending on your industry. The cons: In order to understand all the intricacies, you need to learn. The issue with that is that the information is sometimes hard to find, may be confusing, and overwhelming. The academy is also quite time-consuming so if you're on a time frame, it my not be feasible. The overall feel of the platform might also be a little bit overwhelming. There are too many dashboards and too many things to look at. The free version of Google Analytics suit almost anyone, but if your traffic is high and you'd like to upgrade to Premium, the price is $150,000. Another great article on this matter is written by the guys at Eethuu. Hopefully, this has helped give you more insights into Google Analytics! If you'd like more information or have any questions, get in touch. Check out Part 2(What is the bounce rate in Google Analytics) of the series!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

With the How to improve your landing pages using Google Analytics blog post, I wanted to help answer the question, why users are clicking a call-to-action but are not converting? Now I will give you some basic tips on how to improve your landing pages, overall. Do what you say and say what you do There is nothing more frustrating for a client than to hope for honey and receive salt. Donʼt promise one thing and then deliver something else .. or even worse nothing at all (a 404 page). For example, if you are giving away an ebook, and your CTA says “Get your free ebook”, donʼt provide a PayPal form on the next screen asking for $2.95 for the product you said would be free, or merely say “thanks for registering” without a link to the product you are offering. Yes, you will have gained a lead, but the customer is now worthless and will tell others about your unfair tactics. In order to get the answer to "Why don't they convert" check this checklist: Do you respect the above? If not this is your biggest business issue. Do you track how many clicks your call-to-action have? If not, see the previous blog post about tracking CTAs What is your conversion rate? Depending on your business model, a conversion rate of 5% to 20% is be normal. (Calculate users that finished the call-to-action divided by users that clicked the call-to-action button.) With these answers, you can figure out what your problem is. This will either be that the users are not clicking or the users are not converting. If the users are not converting you can: A/B test the layout of next page after they click the call-to-action button A/B test the text of the next page after they click the call-to-action button Provide online support on that page offering customers the option to ask direct questions Create a survey for the segment of users that clicked the call-to-action but didn't convert to find out why they didn't Have any questions? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Google Analytics is a free Web analytics service that provides statistics and basic analytical tools for search engine optimisation (SEO) and marketing purposes. The service is available to anyone with a Google account. As a person that’s at the beginning and trying to get familiar with the field of analytics and data, it’s definitely important to understand how Google Analytics works. There are four components that come together and make Google Analytics work: 1. Collection 2. Processing 3. Configuration 4. Reporting Collection: Data can be collected from different sources, such as a website, a mobile application or pretty much any device that has a connection to the internet. For a website, in order to collect the information, we need to include a Tracking code (JavaScript). This code should be included on every single page of the website in order for Google Analytics to capture the information properly. The JavaScript that we get from Google is okay, but don’t forget that it tracks a limited amount of information. If you are active in a niche field of work, you might want to take a look at adapting that code in order to track the correct data. For a mobile application, we need to use a specific software development kit (SDK), depending on the operating system. In this case, activities will be tracked instead of pageviews. Because we might not always have an internet connection available, the hits will be stored and sent to afterwards to Google’s collection centres. Processing + Configuration: The processing step is the one that takes the longest to finish. It can take anywhere up to 4 hours (24 hours in Google's T&Cs) to turn all the raw data into reports that you are able to interpret and monitor. This doesn’t happen easily, but the only way you can skip the queue is by paying for Google Analytics 360. In Google Analytics, the configuration part comes in and it applies certain filters to the data that is collected. While some of those filters (new or returning users, linking between pages and time spent on certain pages) are pre-configured, you also have the possibility to apply some filters of your own to this process. Remember that you will not be able to change that information once it is stored in the database. Reporting: The final step what the users get to see. By using Google Analytics' own interface, you have access to all the processed information and this is the place where you can manage it from. There is also the possibility of using different applications by creating a custom code in the reporting API. Here is a short list of benefits that you will gain after using Google Analytics: 1. Visitor Segmentation: New vs Returning users, Geographical location and referral source. 2. Page visits: Finding out which pages are the most visited. 3. Locating the website: Finding out how the users got to your website and tracking the keywords they used. 4. Website optimization If you'd like some more information, please get in touch or leave a comment below! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

In the previous blog post, how to improve your landing pages using Google Analytics, we started analysis what makes a good landing page. Some of the ideas were related to call to actions. Your landing page must have a call to action (CTA) correlated with the marketing campaign and the full content of the page. Clear and unambiguous CTA(s) If you are offering app access, go with "Get Started" or "Create account" and don't say “Get your free ebook” or “go” or “submit”. Say short and clear what you want them to do. Don't mislead the users and don't use fancy words. When you're choosing the CTA for your landing page you should consider these three: what you say how your customer will interact with it where to place it What to say is the wording. If you want the customer to subscribe to the newsletter say "subscribe to the newsletter", if you want them to buy say "buy", if you want them to call say "call". Keep it short and clear. If the customer needs to subscribe you need to provide them with the field were to add their email address; If you want them to call you then you should use a dial function for mobile users or show the number for the desktop users; If you want them to buy then the press of the button should redirect them to a page where they can choose the option for delivery and payment. Where to place the call to action in your landing page is simple - where the customers will see it first. I presume you already have event tracking, in place (if no, find out how to set up in this blog post: Set up event tracking in GTM ). Based on some numbers from Google Analytics, let's see how good and bad engagement looks like for a landing page. Find out the level of engagement with the page Bounce rate: This will show you the number of people that entered this page and left without taking any other action (like seeing the second page or clicking on the call to action). The bounce rate will tell you how your whole landing page is engaging with the audience. In the example above, the landing page, /find-more has a bounce rate of 98,8%. This is very bad! On the other side, we have the landing page apps.shopify.littledata with 0% bounce rate. This is the holy grail of landing pages. These means that from an engagement point of view your landing page is perfect. As a rule: You should aim for at least the same bounce rate as you have on the entire website as a medium. Find out if your call to action performed Method 1 - Deducting from landing page report Go into Google Analytics -> in the search bar search landing page -> Choose Site content - Landing pages. Click on your landing page name and now add a second dimension: Second page. Find the link where your call to action redirects and analyse all elements in this report. If you don't have events in place, you will still be able to see how your traffic is clicking through the links on your landing page. If your landing page has more than 1 action then you can add a second dimension on the landing page report and see what was the second page they visited. In the example above, the call-to-action redirected them to the apps.shopify.com/littledata. From the numbers of sessions, we can see that only 10% of the users clicked the call-to-action button. 89% of the people wanted to find more about the product before purchasing. This is the example of bad engagement. The fact that 89% of the people wanted to find more means that we need to provide more details on the landing page and maybe have a clearer call-to-action. Method 2 - Deducting from Top Events report For this, go to Google Analytics and search for Top Events and add a second dimension to the report "Page". You can also build a custom report so you see the number of people that saw the page and the number of people that took the call-to-action. Have any questions? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

After I concluded that freemium is not the best business model for all, the continued rise of ‘free’ software has led me to revisit the same question. In a fascinating piece of research by Price Intelligently, over 10,000 technology executives were surveyed over 5 years. Their willingness to pay for core features of B2B software has declined from 100% in 2013 to just over 50% today – as a whole wave of VC-funded SaaS companies has flooded the market with free product. For add-ons like analytics, this drops to less than 30% willing to pay. “The relative value of features is declining. All software is going to $0” – Patrick Campbell, Price Intelligently Patrick sees this as an extension of the trend in physical products, where offshoring, global scale and cheaper routes to market online have led to relentless price depreciation (in real terms). I’m not so sure. Software is not free to manufacture, although the marginal cost is close to zero – since cloud hosting costs are so cheap. The fixed cost is the people-time to design and build the components, and the opportunities for lowering that cost – through offshoring the work or more productive software frameworks - have already been exploited by most SaaS companies. To pile on the pain, a survey of software executives also found that the average number of competitors in any given niche has increased from 10 to 15 over those 3 years. Even if software build costs are falling, those costs are being spread over a small number of customers – making the chance of breaking even lower. And the other big cost – Customer Acquisition (CAC) – is actually rising with the volume of competition. To sum up the depressing news so far: 1. Buyers have been conditioned to expect free software, which means you’ll have to give major features away for free 2. But you’ll have to pay more to acquire these non-paying users 3. And next year another competitor will be offering even more for free What is the route of this economic hole? Focussing on monetising a few existing customers for one. Most SaaS executives were focussed on acquiring new customers (more logos), probably because with a free product they expected to sweep up the market and worry about monetization later. But this turns out to be the least effective route to building revenue. For every 1% increment, Price Intelligently calculated how much this would increase revenue. i.e. If I signed up 101 users over the year, rather than 100, that would increase revenue by 2.3%. Monetization – increasing the Average Revenue Per User (ARPU) – has by far the larger impact, mainly because many customers don’t pay anything currently. In contrast, the impact of customer acquisition has fallen over 3 years, since the average customer is less likely to pay. Monetization is not about increasing prices for everyone – or charging for previously free features – but rather finding the small number who are willing to pay, and charging them appropriately. My company, Littledata, has many parallels to Profit Well (launched by Price Intelligently). We both offer analytics and insights on top of existing customer data – Littledata for Google Analytics behavioural data, and Profit Well for recurring revenue data from billing systems. And we have both had similar customer feedback: that the perceived value of the reporting is low, but the perceived value of the changes which the reporting spurs (better customer acquisition, increased retention etc) is high. So the value of our software is that it creates a requirement – which can then be filled by consulting work or ‘actionable’ modules. For myself, I can say that while focusing on new customer acquisition has been depressing, we have grown revenues once a trusted relationship is in place – and the customer really believes in Littledata’s reporting. For Littledata, as with many B2B software companies, we are increasingly content that 80% of our revenue comes from a tiny handful of loyal and satisfied users. In conclusion, while the cover price of software subscriptions is going to zero, it is still possible to generate profits as a niche SaaS business – if you understand the necessity of charging more to a few customers if the many are unwilling to pay. Freemium may be here to stay, but if customers want the software companies they rely on to stay they need to pay for the benefits. Would you like to further discuss? Comment below or get in touch!

Landing page optimisation is one part of a broader digital marketing process called conversion optimisation, or conversion rate optimisation (CRO), with the goal of improving the percentage of visitors to a website that becomes sales leads/or customers. Let's see how to improve your landing page performance. There are some things to check when you want to improve the conversion rate of a particular page. In order to get the best data, we use Google Analytics and Hotjar. I will start with Hotjar because it is faster! With Hotjar you will understand what users want, care about and interact with on your site by visually representing their clicks, taps and scrolling behaviour. This is shown with nice videos of a user's journey leading to conversion. With Hotjar, you can see what confuses people, what is not clear and if for your customer point-of-view is clear on your landing page. And now the hard and exciting part: Analyse the data collected in Google Analytics. If you think that the home page is a landing page please read this before you go further: Website Homepage vs Landing page - what's the difference? and this: Don’t obsess over your homepage – its importance will decrease over time! When a visitor clicks on a Pay-Per-Click (PPC) ad, they're taken to a landing page — a web page whose sole purpose of existence is to entice people to take an action. If done well, it could be the most effective marketing weapon in your arsenal. The correct analysis of data can save you a lot of money or even your business. If your visitors donʼt know what to do when they land on your landing page, then you are throwing your advertising money out the window. Your call-to-action (CTA) is the primary conversion goal of a visitor to your landing page. Next, I give you some examples of common actions that you might want a customer to do on your landing page: purchasing a product subscribing to a newsletter calling you on the phone downloading an ebook or whitepaper watching a demo requesting information Let's find out, step-by-step if your landing page is a winner using this checklist. Click on them to find out how to analyse and interpret data CTA(s) clear and unambiguous Do what you say and say what you do Don't be like Trump. Leave the Amazing! Awesome! words elsewhere Less is more Keep it where it can be seen Know your clients Twice is better Design matters Choose what matters the most CTA(s) clear and unambiguous Google Analytics report: "Landing pages" with a second dimension added to the report: "Second page" If you are offering an app access go with "Get Started" or "Create account" and don't say “Get your free ebook” or “go” or “submit”. Do what you say and say what you do Google Analytics report: "Landing pages" with a second dimension added to the report: "Second page" analyses the bounce rate on the call-to-action link. Donʼt promise one thing and then deliver something else or even worse nothing at all (a 404 page). To follow the same example, if you have an app and say "30 days free trial" don't let people click 'try for 30 days' and on the next page provide a PayPal form to charge them for a month period. Don't be like Trump. Leave the Amazing! Awesome! words elsewhere Google Analytics report: "Pages" see how many FAQ and Terms pageview you have. Resist the temptation to include bloated adjectives. Such claims are likely to make people think you are overselling and trying too hard. Less is more Google Analytics report: "Top Events" with a second dimension added to the report: "Page" analyses the clicks on your call-to-action versus other clicks in page or scroll actions. Make space for your call-to-action. Let them breathe visually. Using more whitespace will allow your button or statement to stand out on the page. Colour choice is important here also; create a high contrast between the call-to-action and surrounding elements to assert it’s dominance. Keep it where it can be seen Google Analytics report: "Top Events" analyse the scroll tracking. See how far your visitors are scrolling down If you have a long page, donʼt put the call-to-action below the fold. Take into consideration, the different screen sizes and adapt your landing pages for the most common. Most of the users will not scroll far down the page so be sure to put your value proposition and your call-to-action as a first-seen element in the page. Know your clients Google Analytics report: "Demographics - Language" Speak your client's language. Provide different landing pages based on country. Advertise differently based on specific demographics. However good your product or service is, the simple truth is that no one will buy it if they don't want it or believe they don't need it. And you won't persuade anyone that they want or need to buy what you're offering unless you clearly understand what it is your customers really want. Twice is better Google Analytics report: Combine "Top Events" (for scroll tracking) and "All Pages" for the propotion of sessions with FAQ/Terms pageviews Not all customers are ready to engage right away and might need some supporting information to ease their worries or answer their questions. If you are asking someone to buy something, a sensible secondary call-to-action can be to download a product brochure. This keeps them in your realm of influence (as opposed to leaving to do research elsewhere) and builds confidence. Ensure that the safety net CTA doesnʼt compete in size and visual dominance – often a simple text link is adequate, beneath the main big action button. If you are asking someone to purchase online, offering a phone number for phone orders can make a potential customer more likely to convert if thatʼs their preferred contact method. Design matters Google Analytics report: "Source/medium" shows the bounce rate for each campaign Carry your primary call-to-action throughout the entire acquisition and conversion experience, from audience acquisition ads (PPC, email, banner, social media link) through your landing page and on to the final destination page. Choose what represents you the most (maybe some colours or even the call-to-action itself), you should be able to look at the page and have your eye immediately drawn to the action area. Be audience appropriate Google Analytics report: there is no report in Analytics for this. Just remember your experience when reading an email or a Facebook comment Previously, I said to speak the customers' language. Now I'm saying to take care what they can interpret. Reading a statement is different from hearing it. So don't be too pushy, don't use a lot of exclamation signs, don't use a lot of caps lock wording and be a friend when they say what they feel when they see the call-to-action. I recommend reading this blog post from January: How to improve your conversion rate optimisation and this one: Conversion friendly experiences: reducing landing page friction with psychology. These two are related and complementary to the actions you're trying to take. In the next couple of weeks I will go deeper in each section and show you how good and bad engagement looks like for a landing page. Have any questions? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If Facebook is a major channel for your marketing, whether sponsored posts or normal, then you’re underestimating the visits and sales it brings. The problem is that Facebook doesn’t play nicely with Google Analytics, so some of the traffic from Facebook mobile app comes as a DIRECT visit. That’s right – if a Facebook user clicks on your post on their native mobile app they won’t always appear as a Facebook social referral. This traffic is ‘dark Facebook’ traffic: it is from Facebook, but you just can’t see it. Since around 40% of Facebook activity is on a mobile app, that means the Facebook traffic you see could be up to 40% less than the total. Facebook hasn’t shown much interest in fixing the issue (Twitter fixed it, so it is possible), so you need to fix this in your own Google Analytics account. Here are three approaches: 1. Basic: use campaign tagging The simplest way to fix this, for your own posts or sponsored links on Facebook, is to attach UTM campaign tags to every link. Google provides a simple URL builder to help. The essential tags to add are “utm_source=facebook.com” and “utm_medium=referral”. This will override the ‘direct’ channel and put all clicks on that links into the Facebook referral bucket. Beyond that, you can add useful tags like “utm_campaign=events_page” so you can see how many click through from your Facebook events specifically. 2. Moderate: use a custom segment to see traffic What if much of your traffic is from enthusiastic brand advocates, sharing your pages or articles with their friends? You can’t expect them to all use an URL builder. But you can make a simple assumption that most users on a mobile device are not going to type in a long URL into their browser address bar. So if the user comes from a mobile device, and isn’t visiting your homepage (or a short URL you deliberately post), then they are probably coming from a mobile app. If your website is consumer facing, then the high probability is that that mobile app is Facebook. So we can create a custom segment in GA for traffic which (a) comes from a mobile device (b) does not have a referrer or campaign (i.e. direct) (c) does not land on the homepage To start you need to create a segment where source contains 'facebook'. Then add the 'Direct mobile, not to homepage' segment: Next, you can create a custom report to show sessions by hour: You should see a strong correlation, which on the two web properties I tested on resulted in doubling the traffic I had attributed to Facebook. 3. Advanced: attribute micro spikes to Facebook Caveat: you’ll need a large volume of traffic – in excess of 100 visits from Facebook a day – to try this at home The final trick has been proved to work at The Guardian newspaper for Facebook traffic to news articles. Most Facebook activity is very transitory – active users click on a trending newsfeed item, but it quickly fades in interest. So what you could do, using the Google Analytics API, is look for the ‘micro spikes’ in referrals that come from Facebook on a minute-by-minute basis, and then look at the direct mobile visits which came at the same time, and add these direct spikes to the total Facebook traffic. I've played around with this and it's difficult to get right, due to the sampling Google applies, but I did manage to spot spikes over around 5 minutes that had a strong correlation with the underlying direct mobile traffic. Could these approaches work for your site?  I'm interested to hear. (Chart: Dark Social Dominates Online Sharing | Statista)   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If you run Facebook Ads and want to see how they perform in Google Analytics, you may have noticed some big discrepancies between the data available in Facebook Ad Manager and GA. Both systems use different ways to track clicks and visitors, so let’s unpick where the differences are. There are two kinds of metrics you’ll be interested in: ‘website clicks’ = the number of Facebook users who clicked on an advert on your own site, and (if you do ecommerce) the transaction value which was attributed to that advert. Website Clicks vs Sessions from Facebook 1. GA isn’t picking up Facebook as the referrer If users click on a link in Facebook’s mobile app and your website opens in an in-app browser, the browser may not log that ‘facebook.com’ was the referrer. You can override this (and any other link) by setting the medium, source, campaign and content attributes in the link directly. e.g. www.mysite.com?utm_medium=social&utm_source=facebook.com&utm_campaign=ad Pro Tip: you can use GA’s URL builder to set the UTM tags on every Facebook campaign link for GA. In GA, under the Admin tag and then ‘Property settings’ you should also tick the box saying ‘Allow manual tagging (UTM values) to override auto-tagging (GCLID values)’ to make this work more reliably. 2. The user leaves the page before the GA tag fires There’s a time delay between a user clicking on the advert in Facebook and being directed to your site. On a mobile, this delay may be several seconds long, and during the delay, the user will think about going back to safety (Facebook’s app) or just closing the app entirely. This will happen more often if the visitor is not familiar with your brand, and also when the page contents are slow to load. By Facebook’s estimation the GA tracking won’t fire anywhere between 10% and 80% of clicks on a mobile, but fewer than 5% of clicks on a desktop. It depends on what stage in the page load the GA pixel is requested. If you use a tag manager, you can control this firing order – so try firing the tag as a top priority and when the tag container is first loaded. Pro Tip: you can also use Google's mobile site speed suggestions to improve mobile load speed, and reduce this post-click drop-off. 3. A Javascript bug is preventing GA receiving data from in-app browsers It’s possible your page has a specific problem that prevents the GA tag firing only for mobile Safari (or Android equivalent). You’ll need to get your developers to test out the landing pages specifically from Facebook’s app. Luckily Facebook Ad Manager has a good way to preview the adverts on your mobile. Facebook Revenue vs GA Ecommerce revenue 4. Attribution: post-click vs last non-direct click Currently, Facebook has two types of attribution: post-view and post-click. This means any sale the user makes after viewing the advert or clicking on the advert, within the attribution window (typically 28 days after clicking and 1 day after viewing), is attributed to that advert. GA, by contrast, can use a variety of attribution models, the default being last non-direct click. This means that if the user clicks on an advert and on the same device buys something within the attribution window (typically 30 days), it will be attributed to Facebook.  GA doesn't know about views of the advert. If another campaign brings the same user to your site between the Facebook ad engagement and the purchase, this other campaign takes the credit as the ‘last non-direct click’. So to match as closely as possible we recommend setting the attribution window to be '28 days after clicking the ad' and no 'after view' attribution in Facebook (see screenshot above) and then creating a custom attribution model in GA, with the lookback window at 28 days, and the attribution 'linear' The differences typically come when: a user engages with more than one Facebook campaign (e.g. a brand campaign and a re-targeting one) where the revenue will only be counted against the last campaign (with a priority for ads clicked vs viewed) a user clicks on a Facebook ad, but then clicks on another advert (maybe Adwords) before buying. Facebook doesn’t know about this 2nd advert, so will attribute all the revenue to the Facebook ad. GA knows better, and will attribute all (or part) of it to Adwords. 5. Facebook cross-device tracking The main advantage Facebook has over GA is that users log in to its platform across all of their devices, so it can stitch together the view of a mobile advert on day 1 with a purchase made from the user’s desktop computer on day 2. Here’s a fuller explanation. By contrast, unless that user logs into your website on both devices, and you have cross-device tracking setup, GA won’t attribute the sale to Facebook. 6. Date of click vs date of purchase In Facebook, revenue is attributed to the date the user saw the advert; in GA it is to the date of purchase. So if a user clicks on the advert on 1st September, and then buys on the 3rd September, this will appear on the 1st on Facebook – and on the 3rd in GA. 7. The sampling problem Finally, did you check if the GA report is sampled? In the top right of the screen, in the grey bar, you'll see that the report is based on a sample.  If that sample is less than 100% it means the numbers you see are estimates.  The smaller the sample size used, the larger the possibility of error.  So in this example, a 45% sample of 270,000 sessions could skew our results plus or minus 0.2% in the best case. As a rule of thumb, Google applies sampling when looking over more than 500,000 sessions (even if you select the 'greater precision' option from the drop-down menu). You can check your own sample using this confidence interval calculator. Conclusion Altogether, there’s a formidable list of reasons why the data will never be an exact match, but I hope it gives you a way to optimise the tracking. Please let us know if you’ve seen other tracking issues aside from these.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Are you using Eventbrite for event registrations? And would you like to see the marketing campaign which drove that event registration correctly attributed in Google Analytics? Then you've come to right place! Here is a simple guide to adding a Google Tag Manager tag to ensure the correct data is sent to Eventbrite to enable cross-domain tracking with your own website. Many thanks to the Lunametrics blog for their detailed solution, which we have adapted here for GTM. Before this will work you need to have: links from your site to Eventbrite (including mysite.eventbrite.com or www.eventbrite.co.uk) the Universal Analytics tracking code on both your site and your Eventbrite pages. only have one GA tracking code on your own site - or else see the Lunametrics article to cope with this 1. Create a new tag in GTM Create a new custom HTML tag in GTM and paste this script: [code language="javascript"] <script> (function(document, window) { //Uses the first GA tracker registered, which is fine for 99.9% of users. //won't work for browsers older than IE8 if (!document.querySelector) return; var gaName = window.GoogleAnalyticsObject || "ga" ; // Safely instantiate our GA queue. window[gaName]=window[gaName]||function(){(window[gaName].q=window[gaName].q||[]).push(arguments)};window[gaName].l=+new Date; window[gaName](function() { // Defer to the back of the queue if no tracker is ready if (!ga.getAll().length) { window[gaName](bindUrls); } else bindUrls(); }); function bindUrls() { var urls = document.querySelectorAll("a"); var eventbrite = /eventbrite\./ var url, i; for (i = 0; i < urls.length; i++) { url = urls[i]; if (eventbrite.test(url.hostname) === true) { //only fetches clientID if this page has Eventbrite links var clientId = getClientId(); var parameter = "_eboga=" + clientId; // If we're in debug mode and can't find a client if (!clientId) { window.console && window.console.error("GTM Eventbrite Cross Domain: Unable to detect Client ID. Verify you are using Universal Analytics."); break; return; } url.search = url.search ? url.search + "&" + parameter : "?" + parameter; } } } function getClientId() { var trackers = window[gaName].getAll(); return trackers[0].get("clientId"); } })(document, window); </script> [/code]   2. Set the tag to fire 'DOM ready' Create a new trigger (if you don't have a suitable one) to fire the tag on every page at the DOM ready stage.  We need to make sure the Google Analytics tracker has loaded first. 3. Test the marketing attribution With the script working you should see pageviews of the Eventbrite pages as a continuation of the same session. You can test this by: Opening the 'real time' reporting tag in Google Analytics, on an unfiltered view Searching for your own site in Google Navigating to the page with the Eventbrite link and clicking on it Looking under the Traffic Sources report and checking you are still listed as organic search after viewing the Eventbrite page Need more help? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Reading Max Hasting’s excellent book on The Secret War, 1939-1945, I was struck by the parallel between the rise of radio communications in the 1930s and the more recent rise in internet data. The transmission of military and diplomatic messages by radio in the 1930s and 1940s provided intelligence agencies with a new gold mine. Never before had so much potential intelligence been floating in the ether, and yet it threatened to flood their limited manpower with a tide of trivia. The bottleneck was rarely in the interception (trivial with a radio set) or even decryption (made routine by Bletchley Park with the Enigma codes), but rather in filtering down to the tiny number of messages that contained important facts – and getting that information in real time to the commanders in the field. The Ultra programme (Britain’s decryption of German radio intercepts) was perennially understaffed due to the fact that other civil servants couldn’t be told how important it was. At Ultra’s peak in 1943, only around 50% of the 1,500 Luftwaffe messages a day were being processed – and it is unknown how many of those were in time to avert bombing raids. The new age of technology provided an almost infinitely wide field for exploration, as well as the means of addressing this: the trick was to focus attention where it mattered. The Secret War, page 203 The ‘new age of technology’ in the last two decades poses much the same problem. Data on internet behaviour is abundant: there are countless signals to listen to about your website performance, and the technology to monitor users is commonplace. And the bottleneck is still the same: the filtering of useful signals, and getting those insights to the ‘commanders’ who need them in real time. I started Littledata to solve this modern problem in interpreting website analytics for managers of online businesses. There is no decryption involved, but there is a lot of statistics and data visualisation know-how in making billions of data points appreciable by a company manager. Perhaps the most important aspect of our service is to provide insights in answer to a specific question: Group-Captain Peter Stewart, who ran the Royal Air Force’s photo-reconnaissance operations, was exasperated by a senior offer who asked for ‘all available information’ on one European country. Stewart responded that he could only provide useful information if he knew roughly what intelligence the suppliant wanted – ‘naval, military, air or ecclesiastical’. The Secret War, page 203 In the world of online commerce, the question is something like whether the client needs insights into the checkout conversion rate of all customers (to improve site design) or for a specific marketing campaign (to improve campaign targeting). So by focusing on insights which are relevant to the scale, stage or sector of the client company, and making these accessible in a real-time dashboard, Littledata can feed into decision making in a way that raw data can never do. Want to discuss this further? Get in touch or comment below!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Many businesses spend a disproportionate amount of time tweaking copy, design and interactive content for their homepage. Yet they miss the fact that the action is increasingly elsewhere. Homepage traffic has traditionally been seen as a proxy for ‘brand’ searches – especially when the actual search terms driving traffic are ‘not provided’. Now, brand search traffic may be finding other landing pages directly. Our hypothesis was that over the last 2 years the number of visits which start at the homepage, on the average website, are decreasing. To prove this, we looked at two categories of websites in Littledata’s website benchmarks: Websites with more than 20,000 monthly visits and more than 60% organic traffic (227 websites) Large websites with more than 500,000 monthly visits (165 websites) In both categories, we found that the proportion of visits which landed on the homepage was decreasing: by 8% annually for the smaller sites (from 16% of total visits to 13% over two years), and 7% annually for the larger sites (from 13% to 11%). If we ignore the slight rise in homepage traffic over the November/December period (presumably caused by more brand searches in the Christmas buying season), the annual decline is more than 10%. From the larger websites, only 20% showed any proportionate increase in homepage traffic over the 2 years – and those were mainly websites that were growing rapidly, and with an increasing brand. I think there are three different effects going on here: Increased sophistication of Google search usage is leading to more long-tail keywords, where users want a very specific answer to a question – usually not given on your homepage. The increase in mobile browsing, combined with the frustrations of mobile navigation, is leading more users to use search over navigation – and bypass your homepage That Google’s search-engine result page (SERP) changes have made it less likely that brand searches (searching for your company or product names) will navigate to your landing page – and instead browse social profiles, news, videos or even local listings for your company. In conclusion, it seems that for many businesses the homepage is an increasing irrelevance to the online marketing effort. Spend some time on your other content-rich, keyword-laden landing pages instead! And would you like to see if you are overly reliant on your homepage traffic, compared with similar websites? Try Littledata’s reporting suite.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Every online business presence has a goal. These goals (bookings, donations, subscribers, events, or purchases) are the reason for our efforts. But how many of us really track how our goals really perform? In this article, you will find out how to take these business goals and track them on Google Analytics with an ecommerce approach. This article is not about how to set up goals in Google Analytics, but if you are interested in finding out more about the setup or what there are, then read: Setting up a destination goal funnel in Google Analytics. The advantage of using an ecommerce approach for non-ecommerce websites is that after the setup is done, you have a basis to develop correct marketing strategies. You will know what channels brings you money, you will know what channels interact with each other and you can adjust your budget to maximise the ROI. If you're in the business of selling tickets (planes, concerts, conferences), book medical exams or collect donations, this article concerns you! I will show you a step-by-step guide on where to implement the Enhanced Ecommerce features and I will provide links for each to find out how to implement them. Let's say you are Wizz Air. You sell flight tickets and book cars and so on. Promotion impressions and promotion clicks Each time Wizz Air displays a banner with some kind of marketing communication that banner can be tracked as a "promotion" in Google Analytics. In Google Analytics, you can see the performance of each banner and make decisions to replace them, change the order or even make them bigger based on the tracking you implement. The technicalities: implementing via Google Tag Manager or implementing via Google Analytics. After you implement the tracking and create the tags (for GTM) you will be able to see the data in Google Analytics under Ecommerce > Marketing > Internal Promotions Based on the position, click-thru-rate, and revenue gained for each, Wizz Air can then rearrange banners, eliminate some of them or boost their visibility. Ecommerce activities (catalogue views, service page views, click on call to actions) Wizz Air provides multiple sections on the website where you can search for flights. These sections can be mapped as product lists. For WizzAir, the product lists are in the homepage section, timetable section, and maps section. Typically, Google Analytics and Google Tag Manager requests the fields below when sending a product list view (product impressions). I will provide you with a schema that will capture the flight booking particularities but you can use your own business specific examples. When you click on a red point on the map, the customer can see the flights from a particular city. We will send all the flight information from that city as product impressions. 'id': 'LTN - PRG',                          // The departure airport code - The arrival airport code 'name': 'London Luton - Prague',             // City name of departure - City name for arrival 'category': 'Flight',                        // WizzAir offers flight booking along with car booking, and hotel booking 'brand': 'WizzAir',                          // If this would be a tourism agency instead of WizzAir will be other company. 'variant': '010117',                      // If the page has the option to add the date we will add the date as a MMDDYY When the search button is present, you send the action "click". ga('ec:setAction', 'click', {                                    // click action. 'list': 'Maps'                                                          // Product list (string). }); After searching, the client can see the selection page from the product list. For Wizz Air customers, they can search the best price and see the package options. In the case of Wizz Air, these pages can be considered the product pages. The usual structure that needs to be sent to Google Analytics and Google Tag Manager is: 'id': 'LTN - PRG',                                    // The departure airport code - The arrival airport code 'name': 'London Luton - Prague',          // City name of departure - City name for arrival 'category': 'Flight',                                 // WizzAir offers flight booking along with car booking, and hotel booking 'brand': 'WizzAir',                               // If this would be a tourism agency instead of WizzAir will be other company. 'variant': '010117',                             // If the page has the option to add the date we will add the date as a MMDDYY Each time the client changes the day a new detail view should be sent. Clicking on the price box will trigger an Add to cart action. The usual content of an Add To cart activity is: 'name': 'London Luton - Prague',    // The departure airport code - The arrival airport code 'id': 'LTN - PRG',                               // City name of departure - City name for arrival 'price': '61.99',                                  // Selected price for the flight 'brand': 'WizzAir',                          // If this would be a tourism agency instead of WizzAir will be other company. 'category': 'Flight',                        // WizzAir offers flight booking along with car booking, and hotel booking 'variant': '010117',                         //If the page has the option to add the date we will add the date as a MMDDYY 'quantity': 1'                                   // Person number 'dimenstion1': 'LTN13432',           // Flight number 'dimenstion2': 'WizzGO'              // Package option (Basic, Wizz Go, Wizz Plus) Check out steps and booking In the case of Wizz Air, each "continue" button will send a checkout step to Google Analytics. Sending the checkout steps will provide insights about where the customers drop off and what process steps can be improved. Wizz Air has a 4-steps checkout (choose flight, choose passengers, services, and payment). The final thing to send is the transaction (the booking). The structure and implementation details for Google Analytics and Google Tag Manager are in the links and the fields, in this case, will be: 'ecommerce': { 'purchase': { 'actionField': { 'id': 'T12345',                                           // Transaction ID. Required for purchases and refunds. 'affiliation': 'booking.com'                    // Affiliation agent, 'revenue': '35.43',                                 // Total booking value (incl. tax, airport fees etc) 'tax':'4.90', 'shipping': '5.99',                                 //can use this field to capture airport fees or thir party operators fees 'coupon': 'SUMMER_SALE'              //if a discount cupon was used }, 'products': [{                                      //if the flight has a return flight then two products will be sent 'name': 'London Luton - Prague',     // The departure airport code - The arrival airport code 'id': 'LTN - PRG',                                // City name of departure - City name for arrival 'price': '61.99',                                  // Selected price for the flight 'brand': 'WizzAir',                           // If this would be a tourism agency instead of WizzAir will be other company. 'category': 'Flight',                         // WizzAir offers flight booking along with car booking, and hotel booking 'variant': '010117',                          //If the page has the option to add the date we will add the date as a MMDDYY 'quantity': 1'                                   // Person number 'dimenstion1': 'LTN13432',           // Fligh number 'dimenstion2': 'WizzGO'               // Package option (Basic, Wizz Go, Wizz Plus) 'coupon': 'SUMMER_SALE'         // Optional fields may be omitted or set to empty string. }, { 'name': 'Prague -London Luton',    // The departure airport code - The arrival airport code 'id': 'PRG -LTN',                               // City name of departure - City name for arrival 'price': '61.99',                                 // Selected price for the flight 'brand': 'WizzAir',                           // If this would be a tourism agency instead of WizzAir will be other company. 'category': 'Flight',                         // WizzAir offers flight booking along with car booking, and hotel booking 'variant': '150117',                        //If the page has the option to add the date we will add the date as a MMDDYY 'quantity': 1'                                   // Person number 'dimenstion1': 'LTN2143432',        // Flight number 'dimenstion2': 'WizzGO'             // Package option (Basic, Wizz Go, Wizz Plus) 'coupon': 'SUMMER_SALE'        // Optional fields may be omitted or set to empty string. }] } } Sending all these steps to Google Analytics about the customer activity, on any kind of website, will provide you with information about return on marketing spends, improve page layout performance, improve conversion rate, find out insights about customer needs and a lot more. Having the full enhanced ecommerce setup is very powerful and can bring many advantages. You can test the full setup on the Google Analytics demo account. Have any questions or need some help? Please get in touch or comment below!  

We will go further into newsletter tracking and try to get all important stats from Google Analytics such as emails sent and emails openings. The advantage to doing this is that for most digital teams, the people creating the newsletters are not necessarily the ones analysing the data. This can help bring the teams a more in-depth view into their work and also a new angle in analysing the newsletter. Before you go ahead and implement this, you should be aware of a few aspects and make some important decisions. First, will you all be using the same Google Analytics account? Since the newsletter opens will send a lot of visits to your Google Analytics account and most of them will be bounces (a high percent of users will not click on the newsletter to go to the website), take into consideration that using the same account will interfere with your existing data from the website. Second, you can create a new, separate account. If you choose to create a new account you need to find out, if you use user tracking, how to link the user activity with the user activity on the website. For Google 360 users this is simpler because they can join views, but for regular Google Analytics users, this might be a struggle. The third option, which I recommend, is to create a second Google Analytics tracking code and run it in parallel with the one you're currently using for the newsletter. Now, let's dive into how you can track email opening and email clicks. The usual Google Analytics script will not work for email clients. However, Google Analytics also includes event tracking which can be used through an embedded image pixel within the email body. Implementing the Google Analytics pixel provides great information like real-time tracking, browser and operating system details and demographics. Insert this snippet in the body of your email like this: <html> <head> ... </head> <body> .... <img src = "Paste the URL here of the Google Analytics implementation"> </body> <footer> ... </footer> </html> Most of the newsletter platforms have an HTML editor, which you can find by searching the sign " <> " in the template. This will let you add <img src = URL> in the body of your email. The URL image pixel looks might like this: <img src="http://www.google-analytics.com/collect?v=1&tid=UA-12345678-1&cid=User_ID&t=event&ec=email&ea=open&el=recipient_id&cs=newsletter&cm=email&cn=Campaign_Name"> Building the URL of the Google Analytics implementation can be done with Google Analytics tool named: Hit Builder. You can also test the URL in the tool and see the hit in real time in Google Analytics. You have two options when sending the openings: as an event or as a custom metric.  Before you go ahead with the HIT Builder let's get familiar with the components of the URL: URL Component Explanation cm1=Custom metric This can be cm1,cm2 etc based on what you've created as a custom metric tid=UA-12345678-1 Your Google Analytics Tracking ID cid=User_ID A systematic tracking ID for the customer t=event Tells Google Analytics this is an Event Hit Type ec=email The Event Category helps segment various events ea=open The Event Action helps specify exactly what happened el=recipient_id Event Label specifies a unique identification for this recipient cs=newsletter Campaign Source allows segmentation of campaign types cm=email Campaign Medium could segment social vs. email, etc. cn=Campaign_Name Campaign Name identifies the campaign to you   To see openings as a custom metric, you should first create a new custom metric in the Google Analytics admin interface named Email Opens. Log in to Google Analytics, and click on Admin. Select the Account and Web Property, and click on Custom Definitions under the Web Property column. Then click on Custom Metrics. In the next window, click on the New Custom Metric button, and give your custom metric a name, formatting type, minimum and maximum value, and make sure the box is checked for Active. You may also find some other benefits to using Google Analytics tracking this way over most email service provider (ESP) tracking. It provides great system information like real-time tracking, browser and operating system details, demographic information including location, and will even tie in nicely with your web reports. How To Use Your Results The event tracking results can be seen in Google Analytics right away. Below are some examples of where you can see reports within Google Analytics. Real Time Events of openings for the newsletter: GA events This report shows the tracking for opens of the emails sent. You can now see how long it takes for people to start opening the newsletter after you've sent them. With this information, you can compare it with past newsletters and see if people are opening it faster or slower, which helps you determine if the subject of the message is motivating enough. Also, you can see what times of the day get the most opens and plan your newsletter schedule around that information. User location With the user location, you can see where in the world people are opening the message you're sending. This can help you determine who your most active audience is and if you should start tailoring your content towards different nations. If you have access to a translation service, this would also be helpful to determine what languages would be beneficial to add to your marketing content. Google Analytics also has a guide, which I recommend to read as well:  Email Tracking - Measurement Protocol.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Here at Littledata we continuously challenge ourselves to come up with ideas that would benefit more and more people, which is why we created our Shopify app. We take the analysis and optimisation of data seriously and to prove that we made it possible with just one click of a button. In order to familiarise yourself, we have created this guide to help you install the app and unlock its full potential. 1. First things first. Let’s begin on your Shopify starting page. Go into the app section by pressing Apps. Once you get on the next page scroll down until you see the “Visit Shopify App Store” button and press it: 2. Once you're in the Shopify App Store, search for our Littledata app: 3. Start the installation process by pressing the “GET” button on the page: 4. Install the app: 5.  Approve the charge and have access to a trial period of 30 days. 6. Click sign in with Google in order for the app to scan your Google Analytics Setup and select the preferred account. Choose the Google Account that you normal use to login in the Google Analytics platform.   7. Next step would be to choose the best data source from the ones you have access to in Google Analytics. We recommend that you choose the one you use to analyse your data and the one you're most familiar with: 8. You are on the app now and almost done with setting everything up! This should be the first page you see after login: Now, let’s dive into fixing and improving everything for your store. Press fix and wait for the magic to happen. After everything is “Correct” we will create a different Littledata test account in which the data will be further collected. We've done that in order for you to be able to compare the new tracking versus the old tracking. 9. Now you will the see GO LIVE button. We recommend, for big traffic stores, to wait at least 24 hours before you go live in order for enough data to be collected in the test Google Analytics to compare them with your current tracking. 10. As the last step, once you go live, you will be prompted to confirm that you have stopped the Shopify default Google Analytics tracking. This means that you need to add a blank space in your Shopify admin section under Preferences instead of your UA-XXXXX-1 code. See this image bellow how. Thank you for subscribing and installing our app! Please, get in touch if you have any questions about the setup.    

Newsletters are the most common form of digital marketing I have seen in the past years. I really don't know any website that doesn't send at least 1 newsletter a month, whether it's an ecommerce website, news website or a B2B presentation website. There are a lot of email marketing platforms, but the question is how profitable are these newsletters? Most platforms provide some form or analysis on the performance of each newsletter. Most providers can show you the numbers of emails sent, the number of users that opened your newsletter and the number of clicks in the email. Along with Google Analytics, you can see how impactful these newsletters are. I want to show you some hacks to dive deeper in analysing each part of your newsletter and improve your newsletter marketing. Analyse each section in the newsletter separate Most of the newsletter that I saw had several links in them so the best way to track them is to tag each link in a distinctive way using the Campaign Content parameter (utm_content). If you do not know what UTM parameters are, please take a moment to read this article: Why should you tag your campaigns? Using the blog post above create your tagged link and add the &utm_content=link1 OR &utm_content=second banner OR &utm_content=Discount banner (whatever works best for you when analysing the data) at the end. Here is an example: http://www.littledata.ro/?utm_source=newsletter&utm_medium=email&utm_campaign=20%25off&utm_content=banner1 Here is a newsletter as part of a campaign named: "black friday2" with 3 banners in it. You can see from the data bellow that the top banner had the most clicks, but, in fact, the second banner is the only one that converted. This means that in the future we should move the second banner as a primary banner to have a higher visibility and in this way increase the number of transactions. You can tag all your links in the newsletter (the logo, banners, hyperlinks, products and so on) And see how each section is performing and what is driving the customers to click in the email. In a real email marketing platform, I strongly recommend searching the provider blog to see if they already support this in any way. Here is MailChimp solution for tracking the newsletter performance in Analytics. If the platform you are using does not support Google Analytics at the moment you can just build the URL with Google's URL builder or our simple Littledata URL builder and add it as you normal do in the newsletter. Track users on how they get on your website from a particular newsletter We've tested some hypotheses and the first one is to make a group of users in Google Analytics that come from a newsletter. The standard way is just to tag the newsletter with UTM parameters and create an audience based on that traffic. But to be more precise and go further with the analysis, we can add a new UTM parameter to all the links in the newsletter that contained the User ID. So now this traffic is not random but it's from a customer we've engaged with already and I do have historical data. The benefit of doing so is that, in an era of mobile devices and cross-device interactions, people read newsletters on the move and react or buy on different devices at different times as a result of the same campaign. You, as a marketer need to understand the cross-device movement and so I recommend that you read about this in the blog post: User Tracking To be able to track the activity of each individual user in your newsletter, you need to build a URL with a User ID parameter in it. This step is similar to the one before so you can add on to the URL you already built for your banners and add the unique identifier number of each client like this: http://www.mywebsite.com/?utm_source=newsletter&utm_medium=email&utm_campaign=20%25off&userID=3D12345 The User ID is generated by the platform you're using, so please take your time and find out if your email marketing solution supports this, along with the email address you've imported and the User Id from your back end. We use Intercom, where you can just add it into the link with a simple click, like this: The platform you're using might be different but if there is an option to import the User Id along with the email address then it is likely that your platform supports this in some way. Once you've added this to the URL, you can then set up a URL variable in Google Tag Manager to pick it up and set up a field with the pageview that will be sent to Google Analytics. For more information, here's how to set a field in Google Tag Manager. Be sure to check back next week for part 2! If you have any questions or would like more help, please get in touch with one of our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

In internet marketing, conversion optimisation, or conversion rate optimisation (CRO) is a system for increasing the percentage of visitors to a website that converts into customers, or more generally, takes any desired action on a web page. Let's find out how you can improve your conversion rate optimisation with some easy to implement ideas. To start improve your conversion rate optimisation you need tools and analysis. Analytics Google Analytics (free) KISSMetrics Mixpanel Segment.io Chartbeat Clicky RJ Metrics Woopra Chart.io Custora Sumall GoodData Omniture There are more, and depending on your business size, type and traffic you’ll need to determine which is best for you. For most companies Google Analytics is plenty. If you want to have a cohort analysis, using a combination of Google Analytics and KissMetrics will do the trick. User Surveys Qualaroo offers online surveys that allow you to ask questions on specific pages or at specific points in your funnel. Survey Monkey is an online survey tool, which helps create surveys, customer feedback and market research via email and social media. SurveyGizmo is a software company focusing on creating online surveys, questionnaires, and forms for capturing and analysing data. PollDaddy is a user-friendly polling software that can be used to get user feedback via email or social media. Survey.io is a fixed survey designed for startups to determine if their product is delivering an irreplaceable must-have experience. User Testing Optimizely is a website optimisation platform focused on A/B and multivariate testing, making them easier to use and understand on your site. Google Content Experiments is integrated with Google Analytics and is Google’s free website testing and optimisation tool. Visual Web Optimiser also focuses on an easier approach to A/B and multivariate testing but includes behavioural targeting, heatmaps, usability testing, as well. Unbounce also offers A/B testing, while focusing predominantly on the efficiency of your landing page. Google Optimize, a new tool from Google will conduct A/B tests for free and it is currently is gradually rolling out. Now, with one of each category, we can run tests and improve our conversion rate optimisation and also our revenue. 1. Site Speed This factor can't be ignored. As the Tag Man blog reports, a single 1-second delay in page-load can result in a 7% decrease in conversions. Pay attention to your site speed to ensure your optimisation efforts aren’t in vain. Use an analytics tool to find your Page Speed. For ecommerce the conversion rate is a closed sale, but for a blog the conversion can be any goal you want. How to fix this: Minimise HTTP Requests. Reduce server response time. Enable compression. Enable browser caching. Minify Resources. Optimise images. Optimise CSS Delivery. Prioritise above-the-fold content. 2. Take advantage of what you have Your website is your salesperson. A good salesperson markets their most appealing and important attributes. Double-check your website and make sure you’re communicating your value and advantages. Also, be sure to track these interactions and how people react. Use an analytics platform to measure the importance. Social proof. Testimonials will give users a feeling of security and trust. Appeals to authority. Try to find a trend, belief, or position that’s advocated by someone of stature in your area of expertise to promote you. Third party validation. A variant of the social proof above, but instead of testimonials you can use trusted brand logos to borrow their brand equity for your brand. Build a community. Users are the main reason to be online. Give them a way to participate in comments, reviews and feedback. Referrals. Try to make your clients your most important advocates. Help them refer you, with incentives like discounts or free gifts to users who recruit others through email, social media, etc. 3. Raise Your Average Order Value (AOV) Here are a few methods of increasing your AOV. You can improve your revenue even without improving your conversion rate. Bundle the products. Combine complementary products, and give the user a discount for purchasing them as a bundle. You can A/B test, measure and survey to find out what has the biggest impact. Promotions. Promotions come in many shapes and forms (free shipping, 1+1, 2+1, etc). Implement Enhanced Ecommerce if you're an ecommerce store and track the promotions interaction and how each contributes to the sale. Rewards. Loyalty programs will keep users returning. In particular, programs that reward higher levels of spending (escalating coupons are an example of this) can positively impact AOV. Track this with an analysis platform as with a user-centred platform. 4. How Friendly is your online presence? Do you have a responsive website? There is a good chance that some of your users will be arriving via their phones and tablets, and almost nothing is more difficult to navigate than a site that's not mobile-friendly. If a user cannot navigate your site, they can’t become customers. Compare your conversion rate with your analytics platform for each device. Does your website work on most browsers? Not all browsers are built the same–that goes without saying, but do you know what browsers are most popular among your users? There is a chance that your site is awesome on Chrome, but a mess on Internet Explorer. Do the research. Load up the browsers and make sure a user’s arrival is always solid. Fixing any browser specific issues could result in a rise in conversions. Do you have a healthy privacy policy? It is good to show users their information is secure: signals, like SSL (https://) lock images, trusted badges, and social proof can all allay fears. Make sure you have a complete privacy policy linked from the footer of every page on your site. Do you speak your client's language? If you're a client based website that accessible worldwide, wouldn't you want to adjust to offer your services to your audience? If you’re ignoring language support, you could be losing vital clients. Did you build your website starting from the user? No user will ever complain that your site is too easy to use, fast or clear. How many clicks does it take for a user to get to your must have experience? Have you ever counted? Make sure you are thinking as the client where less is more. Do you adjust for your customers time? Information on your landing page should be prioritised by importance. You typically have five seconds to convince a visitor to stick around. Make the most of that brief moment in time. How good is your hook, and how well do you deliver on the promise? Are you adapting to the new video trend? A video on your landing page has the chance to drive conversions. Consider YouTube, or other services as long as users do not have to download additional plugins. Can your customers leave ratings and reviews? Having reviews and ratings bring real feedback from real clients. Clients are then more likely to make a decision based on what they read from other perspectives. Have any questions? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If you have an online presence you know that every day you find new and interesting app's and platforms that can increase your revenue. From integrations with Adwords, DoubleClick, Facebook to custom plugins, you need some help inserting all this script in the page that makes it as easy as possible and without asking for developer help. Google Tag Manager can launch new tags with just a few clicks. Google Tag Manager supports both Google and third-party tags and is the web’s most popular enterprise-grade tag management solution. We have written a lot or articles on how to use it, but we never provided a list of why you should use it, so here it is: 1. Reliable and accurate data. When your tags aren’t working properly they can impair your site performance, resulting in slow load times, website unavailability, or a loss of functionality. That’s why it’s critical to have a tag management solution in place that allows you to quickly determine the status of your tags. Easy-to-use error checking and speedy tag loading in Google Tag Manager means you know that every tag works. Be assured that your mission-critical data is being collected reliably and accurately. The IT team will feel confident that the site is running smoothly, so everyone's happy, even during busy holidays or the launch of a new campaign. Large brands have implemented Tag Manager to launch their tags exactly for this reason: reliable and accurate data. PizzaHut, Made.com, AgeUk and many others use Google Tag Manager to manage their tags for Google and third-party platforms. 2. Quickly deploy Google and third-party tags. With so many measurement tools out there, marketers need flexibility — whether that’s changing tags on the fly or having the ability to easily add tags from other sources. In Google Tag Manager, marketers can add or change their own tags as needed. Google Tag Manager supports all tags and has easy-to-use templates for a wide range of Google and third-party tags — for web and mobile apps. Don’t see a tag listed? You can add it immediately as a custom tag. With so much flexibility, your campaign can be underway with just a few clicks. Even if you are using Adwords, Adroll, Facebook, Hotjar, Criteo or your own script you can implement it with Google Tag Manager. Even if you're a publisher as nationalgeographic-magazine.com, sell furniture at Made.com, sell event tickets as eventbrite.com or organise courses as redcrossfirstaidtraining.co.uk, Google Tag Manager will be the best way to organise all the scripts your partners provides. 3. Collaborate across the enterprise and make tag updates efficiently. Collaboration across a large team can be a challenge. Not having the proper tools can stall workflows — decreasing productivity and efficiency. Workspaces and granular access controls allow your team to work together efficiently within Google Tag Manager. Multiple users can complete tagging updates at the same time and publish changes as they’re ready. Multi-environment testing lets you publish to different environments to ensure things are working as expected. I don't know about you but for me, every time I need to add a new script on my website I hesitate because I am afraid that my website will break and I would never know how to fix it. I wanted a solution where I could add a script on my own, test it and then publish it without any developer help. And then I found Google Tag Manager. Google Tag Manager lets you collaborate and work independently, at the same time, on the same website. You can publish a tag at the same time your marketing team-mate is creating an A/B testing experiment, all in the same GTM container. Large and small websites use Google Tag Manager to integrate and increase the value of their website. It is free, it is reliable and you find a lot of how-tos on the web so you can start using it right away. Google Tag Manager currently provides out-of-the-box integration with these ones: Universal Analytics - Google Analytics Classic Google Analytics - Google Analytics AdWords Conversion Tracking - AdWords AdWords Remarketing - AdWords DoubleClick Floodlight Counter - DoubleClick DoubleClick Floodlight Sales - DoubleClick Google Optimize - Google Optimize Google Surveys Website Satisfaction - Google Surveys AB TASTY Generic Tag Adometry AdRoll Affiliate Window Affiliate Window Audience Center 360 Bizrate Insights ClickTale comScore Crazy Egg Criteo Dstillery Eulerian Analytics Google Trusted Stores Hotjar Infinity Tracking Intent Media K50 LeadLab by wiredminds LinkedIn Marin Software Mediaplex Microsoft Bing Ads Mouseflow Neustar Nielsen Nudge Content Analytics Optimise Media OwnerListens Perfect Audience Personali Placed Inc. Pulse Insights Quantcast SaleCycle SearchForce Shareaholic Survicate Tradedoubler Turn Twitter Ve Interactive VisualDNA Yieldify This out-of-the-box integration doesn't require any special knowledge. And, for any other script that you might have, most of the providers have a how-to guide for integrating with Google Tag Manager. Have any questions about Google Tag Manager? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Websites and apps typically gather a huge flow of user behaviour data, from tools such as Google Analytics and Adobe Analytics, with which to better target their marketing and product development. The company assumes that either: Having a smart web analyst or online marketer skim through the reports daily will enable management to keep tabs on what is going well and what aspects are not Recruiting a ‘data science’ team, and giving them access to the raw user event data, will surface one-off insights into what types of customers can be targeted with which promotions Having worked in a dozen such companies, I think both assumptions are flawed. Humans are not good at spotting interesting trends, yet for all but the highest scale web businesses, the problem is not really a ‘big data’ challenge. For a mid-sized business, the problem is best framed as, how do you extract regular, easy-to-absorb knowledge from an incomplete online behavioural data set, and how do you present / visualise the insight in such a way that digital managers can act on that insight? Littledata is meeting the challenge by building software to allow digital managers to step up the DIKW pyramid. The DIKW theory holds that there are 4 levels of content the human mind can comprehend: Data: the raw inputs; e.g. the individual signals that user A clicked on button B at a certain time when visiting from a certain IP address Information: provides answers to "who", "what", "where", and "when" questions Knowledge: the selection and synthesis of information to answer “how” questions Wisdom: the extrapolation or interpretation of this knowledge to answer “why” questions Information is what Google Analytics excels at providing an endless variety of charts and tables to query on mass the individual events. Yet in the traditional company process, it needs a human analyst to sift through those reports to spot problems or trends and yield genuine knowledge. And this role requires huge tolerance for processing boring, insignificant data – and massive analytical rigour to spot the few, often tiny, changes. Guess what? Computers are much better at the information processing part when given the right questions to ask – questions which are pretty standard in the web analytics domain. So Littledata is extending the machine capability up the pyramid, allowing human analysts to focus on wisdom and creativity – which artificial intelligence is still far from replicating. In the case of some simpler insights, such as bounce rates for email traffic, our existing software is already capable of reporting back a plain-English fact. Here’s the ‘information’ as presented by Google Analytics (GA). And here is the one statistically significant result you might draw from that information: Yet for more subtle or diverse changes, we need to generate new ways to visualise the information to make it actionable. Here are two examples of charts in GA which are notoriously difficult to interpret. Both are trying to answer interesting questions: 1. How do users typically flow through my website? 2. How does my marketing channel mix contribute to purchasing? Neither yields an answer to the “how” question easily! Beyond that, we think there is huge scope to link business strategy more closely to web analytics. A visualisation which could combine a business’ sales targets with the current web conversion data, and with benchmarks of how users on similar sites behave, would give managers real-time feedback on how likely they were to outperform. That all adds up to a greater value than even the best data scientist in the world could bring. Have any questions? Comment below or get in touch with our team of experts! Want the easier to understand reports? Sign up!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

The out-of-the-box analytics solution Shopify provides is a basic one, and unfortunately, the ecommerce data (transactions, add-to-carts, etc.) is incomplete and unreliable. With the help of Littledata, you can now be sure that "Shopify has you covered" with Analytics data collection. If you run a store with a large marketing budget you know how important it is to have accurate Analytics data to establish how your marketing budget is performing. It's also important to read the top 5 pitfalls in tracking ecommerce in Google Analytics as these will also apply to Shopify users. These are the known pitfalls for the out-of-the-box Analytics solution from Shopify: 1.Cross-domain and subdomain tracking issues The Shopify checkout is sending the customers to a Shopify domain (checkout.shopify.com). This makes the visitor sessions end suddenly even if they are in the process of buying something. The sales attribution for Shopify store owners is also painful due to the change of domains causing 'checkout.shopify.com' or a payment gateway to be attributed as the 'last click'. At the moment, Google Analytics can help you track both micro and macro moments in a customer journey. Example of micro-moments are: Clicking on a product link Viewing product details Impressions and clicks of internal promotions Adding / removing a product from a shopping cart Purchases and refunds All of these ecommerce interactions help you as a marketer / acquisition manager / owner to know more about your customer's interactions with your products. You can read more about the benefits of tracking the enhanced e-commerce in the article: use enhanced ecommerce to optimise product listings. 2.Clicking on a product link Clicking on a product link will show you the most appealing products, so you can improve the click-through-rate on the category page. If the click through rate is bad, the action to take is to check your product's master picture and see if there are any errors in getting to the product page. Also, you can investigate if these products are in the right category list. See how can you make these products more appealing to your audience. Read more on our blog on how to improve click-through-rate. 3.Viewing product details Viewing product details will show what are the most viewed product details. You can see this using the URL also, but having this info in a structured way (the product name and product SKU) will make the business analysis far easier. 4.Impressions and clicks on internal promotions Impressions and clicks on internal promotions. Every website uses at least one banner. But how many are tracking the effectiveness of these marketing assets? Knowing how they perform can mean a better visual strategy, a better usage of website space and maybe will save you some money when creating fancy banners with fancy designers! 5.Add-to-carts and removes from cart. Add-to-carts and removes from cart. Every store owner before Christmas asks themselves which products should have discounts or which to should be promoted? Finding out what products are added to cart and removed can answer some of those most vital questions in ecommerce. You can check your product picture and description and see if there are any errors on getting to the checkout. Also, be sure you give your customers access to the information about delivery and refunds. You can compare these products with your competition and see if the price and delivery costs are for the customer's advantage. See how can you make these products more appealing to the customer. 6.Purchases and refunds Purchases. The solution Littledata comes with is a server-side integration to provide a 100% match between your Shopify store and Google Analytics. This ensures that you register the sales data, even if the customer never gets to see the thank you page on your store. Refunds. We all know when seeing online sales, that it doesn't necessarily mean the end of the process. There can be a lower or higher percentage of returns from customers. Shopify is adding back the refunds on the day the packages return to the warehouse and this can be really sad for a normal day when there are negatives sales. There are multiple ways in which you can mess up your Google Analytics data while using Shopify but these were the most important ones to take in while tracking a Shopify store. Want more information on how we will help improve your Shopify analytics? Get in touch with our experts! Interested in joining the list to start a free trial? Sign up!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If the lack of consistency between Shopify’s dashboards and the audience numbers in Google Analytics is confusing, you might conclude that it’s safer to trust Shopify. There is a problem with the reliability of transaction volumes in Google Analytics (something which can be fixed with Littledata’s app) - but using Shopify’s reports alone to guide your marketing is ignoring the power that has led Google Analytics to become over by over 80% of large retailers. Last-click attribution Let’s imagine your shoe store runs a Google AdWords campaign for ‘blue suede shoes’. Shopify allows you to see how many visits or sales were attributed to that particular campaign, by looking at UTM ‘blue suede shoes’. However, this is only capturing those visitors who clicked on the advert and in the same web session, purchased the product. So if the visitor, in fact, went off to check prices elsewhere, or was just researching the product options, and comes back a few hours later to buy they won’t be attributed to that campaign. The campaign reports in Shopify are all-or-nothing – the campaign or channel sending the ‘last-click’ is credited with 100% of the sale, and any other previous campaigns the same customer saw is given nothing. Multi-channel attribution Google Analytics, by contrast, has the ability for multi-channel attribution. You can choose an ‘attribution model’ (such as giving all campaigns before a purchase equal credit) and see how much one campaign contributed to overall sales. Most online marketing can now be divided into ‘prospecting’ and ‘retargeting’; the former is to introduce the brand to a new audience, and the latter is to deliberately retarget ads at an engaged audience. Prospecting ads – and Google AdWords or Facebook Ads are often used that way – will usually not be the last click, and so will be under-rated in the standard Shopify reports. So why not just use the analytics reports directly in Google AdWords, Facebook Business, Twitter Ads etc.? Consistent comparison The problem is that all these different tools (and especially Facebook) have different ways of attributing sales to their platform – usually being as generous as possible to their own adverting platform. You need a single view, where you can compare the contribution of each traffic source – including organic search, marketing emails and referrals from other sites – in a consistent way. Unfortunately, Google Analytics needs some special setup to do that for Shopify. For example, if the customer is redirected via a payment gateway or a 3D secure page before completing the transaction then the sale will be attributed to a ‘referral’ from the bank - not the original campaign. Return on Advertising Spend (ROAS) Once you iron out the marketing attribution glitches using our app, you can make meaningful decisions about whether a particular form of marketing is driving more revenue that it is costing you – whether there is a positive Return on Advertising Spend. The advertising cost is automatically imported when you link Adwords to Google Analytics, but for other sources, you will need to upload cost data manually or use a tool like funnel.io . Then Google Analytics uniquely allows you to decide if a particular campaign is bringing more revenue than it is costing and, on a relative basis, where are the best channels to deploy your budget. Conclusion Shopify’s dashboards give you a simple daily overview of sales and products sold, but if you are spending more than hundreds of dollars a month on online advertising – or investing in SEO tactics – you need a more sophisticated way to measure success. Want more information on how we will help improve your Shopify analytics? Get in touch with our experts! Interested in joining the list to start a free trial? Sign up! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If your business relies on customers or subscribers returning to your site, possibly from different devices (laptop, smartphone, etc.) then it’s critical you start tracking unique customers rather than just unique visitors in Google Analytics. By default, Google Analytics tracks your customers by browser cookies. So ‘Bob’ is only counted as the same visitor if he comes to your site from the same browser, but not if he comes from a different computer or device. Worse, if Bob clears his cookies or accesses your site via another mobile app (which won't share cookies with the default browser) then he'll also be counted as a new user. You can fix this by sending a unique customer identifier every time your customer signs in. Then if you send further custom data about the user (what plan he / she is on, or what profile fields they have completed) you can segment any of the visits or goals by these customer attributes. There are 2 possible ways to track registered users: Using Google Analytics’ user ID tracker By storing the clientId from the Google cookie when a new user registers, and writing this back into the tracker every time the same user registers In both cases, we also recommend sending the user ID as a custom dimension. This allows you segment the reports by logged in / not logged in visitors. Let's look at the pros and cons. Session stitching Tracking customers involves stitching together visits from different devices into one view of the customer. Option 1, the standard User ID feature, does session stitching out the box. You can optionally turn ‘session unification’ on which means all the pageviews before they logged in are linked to that user. With option 2 you can stitch the sessions, but you can't unify sessions before the user logs in - because they will be assigned a different clientId. So a slight advantage to option 1 here. Reporting simplicity The big difference here is that with option 1 all of the user-linked data is sent to a separate 'registered users' view, whereas in options 2 it is all on the same view as before. Suppose I want a report of the average number of transactions a month for registered vs non-registered visitors. With both options, I can only do this if I also send the user ID as a custom dimension - so I can segment based on that custom dimension. Additionally, with option 1 I can see cross-device reports - which is a big win for option 1. Reporting consistency Once you start changing the way users are tracked with option 2 you will reduce the overall number of sessions counted. If you have management reports based on unique visitors, this may change. But it will be a one-time shift - and afterwards, your reports should be stable, but with a lower visit count. So option 1 is better for consistency Conclusion Option 1 - using the official user tracking - offers a better route to upgrade your reports. For more technical details on how this tracking is going to work, read Shay Sharon’s excellent customer tracking post. Also, you can watch more about customer tracking versus session tracking in this video. Have any questions? Comment below or get in touch with our team of experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Selecting time ranges for comparison in Google Analytics can trip you up. We find comparing 28-day or 7-day (one week) periods the most reliable method. Gotcha 1: Last 4 days with previous 4 days This is comparing the same time periods (4 days) so shouldn't they be comparable? No! Most websites show a strong weekly cycle of visits (either stronger or weaker on the weekend), so the previous four days may be a very different stage of the week. Gotcha 2: Last month compared with the previous month Easy - we can see traffic has gone up by 5% in March. No! March has 11% more viewing time (3 extra days) than February. So the average traffic per day in March has actually dropped by 5.5%. Gotcha 3: Last week compared with the previous week You can see what's coming this time... Certain weeks of the year are always abnormal, and the Christmas period is one of them. But most business / educational sites it is a very quiet period. The best comparison would be with the same week last year. Have any questions? Let us know by commenting below or get in touch with our lovely experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Stop using vanity metrics to measure your website's performance! The pros are using 5 detailed metrics in the customer conversion journey to measure and improve. Pageviews or time-on-site are bad ways to measure visitor engagement. Your visitors could view a lot of pages, yet be unable to find the right product, or seem to spend a long time on site, but be confused about the shipping rates. Here are the 5 better metrics, and how they help you improve your Shopify store: 1. Product list click-through rate Of the products viewed in a list or category page, how many click through to see the product details? Products need good images, naming and pricing to even get considered by your visitors. If a product has a low click-through rate, relative to other products in the list, then you know either the image, title or price is wrong. Like-wise, products with very high list click-through, but low purchases, may be hidden gems that you could promote on your homepage and recommended lists to increase revenue. If traffic from a particular campaign or keyword has a low click-through rate overall, then the marketing message may be a bad match with the products offered – similar to having a high bounce rate. 2. Add-to-cart rate Of the product details viewed, how many products were added to the cart? If visitors to your store normally land straight on the product details page, or you have a low number of SKUs, then the add-to-cart rate is more useful. A low add-to-cart rate could be caused by uncompetitive pricing, a weak product description, or issues with the detailed features of the product. Obviously, it will also drop if you have limited variants (sizes or colours) in stock. Again, it’s worth looking at whether particular marketing campaigns have lower add-to-cart rates, as it means that particular audience just isn’t interested in your product. 3. Cart to Checkout rate Number of checkout processes started, divided by the number of sessions where a product is added to cart A low rate may indicate that customers are shopping around for products – they add to cart, but then go to check a similar product on another site. It could also mean customers are unclear about shipping or return options before they decide to pay. Is the rate especially low for customers from a particular country, or products with unusual shipping costs? 4. Checkout conversion rate Number of visitors paying for their cart, divided by those that start the process Shopify provides a standard checkout process, optimised for ease of transaction, but the conversion rate can still vary between sites, depending on payment options and desire. Put simply: if your product is a must-have, customers will jump through any hoops to complete the checkout. Yet for impulse purchases, or luxury items, any tiny flaws in the checkout experience will reduce conversion. Is the checkout conversion worse for particular geographies? It could be that shipping or payment options are worrying users. Does using an order coupon or voucher at checkout increase the conversion rate? With Littledata’s app you can split out the checkout steps to decide if the issue is shipping or payment. 5. Refund rate Percent of transactions refunded Refunds are a growing issue for all ecommerce but especially fashion retail. You legally have to honour refunds, but are you taking them into account in your marketing analysis? If your refund rate is high, and you base your return on advertising spend on gross sales (before refunds), then you risk burning cash on promoting to customers who just return the product. The refund rate is also essential for merchandising: aside from quality issues, was an often-refunded product badly described or promoted on the site, leading to false expectations? Conclusion If you’re not finding it easy to get a clear picture of these 5 steps, we're in the process of developing Littledata’s new Shopify app. You can join the list to be the first to get a free trial! We ensure all of the above metrics are accurate in Google Analytics, and the outliers can then be analysed in our Pro reports. You can also benchmark your store performance against stores in similar sectors, to decide if there are tweaks to the store template or promotions you need to make. Have more questions? Comment below or get in touch with our lovely team of Google Analytics experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

The referral exclusion list is only available for properties using Universal Analytics ... so please make the jump and take advantage of the benefits! Let's find out how excluding referral traffic affects your data and how you can correct some of the wrong attributions of sales. By default, a referral automatically triggers a new session. When you exclude a referral source, traffic that arrives to your site from the excluded domain doesn’t trigger a new session. Because each referral triggers a new session, excluding referrals (or not excluding referrals) affects how sessions are calculated in your account. The same interaction can be counted as either one or two sessions, based on how you treat referrals. For example, a user on my-site.com goes to your-site.com and then returns to my-site.com. If you do not exclude your-site.com as a referring domain, two sessions are counted, one for each arrival at my-site.com. If, however, you exclude referrals from your-site.com, the second arrival to my-site.com does not trigger a new session, and only one session is counted. Common uses for referral exclusions list in Google Analytics: Third-party payment processors Cross-subdomain tracking If you add example.com to the list of referral exclusions, traffic from the domain example.com and the subdomain another.example.com are excluded. Traffic from another-example.com is not excluded. Only traffic from the domain entered in the referral exclusions list and any subdomains are excluded. Traffic from domains that only have substring matches are not excluded. How to add domains in the referral exclusion list: Sign in to your Gooogle Analytics account. Click admin in the menu bar at the top of any page. In the account column, use the drop-down to select the Google Analytics account that contains the property you want to work with. In the property column, use the drop-down to select a property. Click tracking info. Click referral exclusion list. To add a domain, click +add referral exclusion. Enter the domain name. Click create to save. The referral exclusion list used contains matching. For example, if you enter example.com, then traffic from sales.example.com is also excluded (because the domain name contains example.com). Need help with these steps? Get in touch with one of our experts and we'd be happy to assist you!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

At a previous Measurefest conference, one of the speakers, Craig Sullivan, recommended a classic research paper from Microsoft on common pitfalls in running conversion rate experiments. It details five surprising results which took 'multiple-person weeks to properly analyse’ at Microsoft and published for the benefit of all. As the authors point out, this stuff is worth spending a few weeks getting right as ‘multi-million-pound business decisions’ rest on the outcomes. This research ultimately points out the importance of doing A/A Testing. Here follows an executive overview, cutting out some of the technical analysis: 1. Beware of conflicting short-term metrics Bing’s management had two high-level goals: query share and revenue per search. The problem is that it is possible to increase both those and yet create a bad long-term company outcome, by making the search algorithm worse. If you force users to make more searches (increasing Bing’s share of queries), because they can’t find an answer, they will click on more adverts as well. “If the goal of a search engine is to allow users to find their answer or complete their task quickly, then reducing the distinct queries per task is a clear goal, which conflicts with the business objective of increasing share.” The authors suggest a better metric in most cases is lifetime customer value, and the executives should try to understand where shorter-term metrics might conflict with that long-term goal 2. Beware of technical reasons for experiment results The Hotmail link on the MSN home page was changed to open Hotmail in a separate tab/window. The naïve experiment results showed that users clicked more on the Hotmail link when it opened in a new window, but the majority of the observed effect was artificial. Many browsers kill the previous page’s tracking Javascript when a new page loads – with Safari blocking the tracking script in 50% of pages opening in the same window. The “success” of getting users to click more was not real, but rather an instrumentation difference. So it wasn’t that more people were clicking on the link – but actually that just more of the links were being tracked in the ‘open in new tab’ experiment. 3. Beware of peeking at results too early When we release a new feature as an experiment, it is really tempting to peek at the results after a couple of days and see if the test confirms our expectation of success (confirmation bias). With the initial small sample, there will be a big percentage change. Humans then have an innate tendency to see trends where there aren’t any. So the authors give the example of this chart: Most experimenters would see the results, and even though they are negative, extrapolate the graph along the green line to a positive result and four days. Wrong. What actually happens is regression to the mean. This chart is actually from an A/A test (i.e. the two versions being tested are exactly the same). The random differences are biggest at the start, and then tail off - so the long term result will be 0% difference as the sample size increases. The simple advice is to wait until there are enough test results to draw a statistically significant conclusion. That generally means more than a week and hundreds of individual tests. 4. Beware of the carryover effect from previous experiments Many A/B test systems use a bucketing system to assign users into one experiment or another. At the end of one test the same buckets of users may be reused for the second test. The problem is that if users return to your product regularly (multiple times daily in the case of Bing), then a highly positive or negative experience in one of the tests will affect all of that bucket for many weeks. In one Bing experiment, which accidentally introduced a nasty bug, users who saw the buggy version were still making fewer searches 6 months after the experiment ended. Ideally, your test system would re-randomise users for the start of every new test, so those carryover effects are spread as wide as possible. Summary For me the biggest theme coming out of their research is the importance of A/A tests – seeing what kind of variation and results you get if you don’t change anything. Which makes you more aware of the random fluctuations inherent in statistical tests. In conclusion, you need to think about the possible sources of bias before acting on your tests. Even the most experienced analysts make mistakes! Have any comments? Let us know what you think, below!    

Universal Analytics promises some juicy benefits over the previous standard analytics. But having upgraded 6 different high traffic sites there are some pitfalls to be aware of. Firstly, why would you want to upgrade your tracking script? More reliable tracking of page visitors - i.e. fewer visits untracked More customisation to exclude certain referrers or search terms Better tools for tracking across multiple domains and tracking users across different devices Track usage across your apps for the same web property Ability to send up to 20 custom dimensions instead of the previous limit of only 5 custom variables If you want to avoid any interruption of service when you upgrade, why not book a quick consultation with us to check if Universal Analytics will work in your case. But before you start you should take note of the following. 1. Different tracking = overall visits change If your boss is used to seeing dependable weekly / monthly numbers, they may query why the number of visits has changed. Universal Analytics is likely to track c. 2% more visits than previously (partly due to different referral tracking - see below), but it could be higher depending on your mix of traffic. PRO TIP: Set up a new web property (a different tracking code) for Universal Analytics and run the old and new trackers alongside each other for a month. Then you can see how the reports differ before sharing with managers. Once this testing period is over you'll need to upgrade the original tracking code to Universal Analytics to you keep all your historic data. 2. Different tracking of referrals Previously, if Bob clicked on a link in Twitter to your site, reads, goes back to Twitter, and within 30 minutes clicks on a different link to your site - that would be counted as one visit and the 2nd referral source would be ignored. In Universal Analytics, when Bob clicks on the 2nd link he is tracked as a second visit, and 2nd referral source is stored. This may be more accurate for marketing tracking, but if Bob then buys a product from you, going via a secure payment gateway hosted on another domain (e.g. paypal.com) then the return from the payment gateway will be counted as a new visit. All your payment goals or ecommerce tracking will be attributed to a referral from 'paypal.com'. This will ruin your attribution of a sale to the correct marketing channel or campaign! PRO TIP: You need to add all of the payment gateways (or other third party sites a user may visit during the payment process) to the 'Referral Exclusion List'. You can find this under the Admin > Property > Tracking codes menu: 3. Tracking across domains If you use the same tracking code across different domains (e.g. mysite.co.uk and mysite.com or mysite.de) then you will need to change the standard tracking script slightly. By default the tracking script you copy from Google Analytics contains a line like: ga('create', 'UA-XXXXXXX-1', 'mysite.com');. This will only track pages that strictly end with 'mysite.com'. PRO TIP: It's much safer to change the tracker to set that cookie domain automatically. The equivalent for the site above would be ga('create', 'UA-XXXXXXX-1', 'auto');. The 3rd argument of the function is replaced with 'auto'. 4. Incompatibility with custom variables Only relevant if you send custom data already Custom variables are only supported historically in Universal analytics. That means you will need to change any scripts that send custom data to the new custom dimension format to keep data flowing. Read the developer documentation for more. PRO TIP: You'll need to set the custom dimension names in the admin panel before the custom data can be sent from the pages. You can also only check that the custom dimensions are being sent correctly by creating a new custom report for each dimension. 5. User tracking limitations We wouldn't recommend implementing the new user ID feature just now, as it has some major limitations compared with storing the GA client ID. You need to create a separate view to see the logged-in-user data, which makes reporting pageviews a whole lot more complex. Visits a user made to your site BEFORE signing up are not tracked with that user - which means you can't track the marketing sources by user PRO TIP: See our user tracking alternative. Got more tips on to setting up Universal Analytics? Please share them with us in the comments, or get in touch if you want more advice on how to upgrade!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

I was asked recently about the best way to track a widget, loaded in an iframe, on a third-party site with Google Analytics. The difficulty is that many browsers now block 3rd party cookies (those set by a different domain to the one in the browser address bar) – and this applies to a Google Analytics cookie for widgets as much as to adverts. The best solution seems to be to use local storage on the browser (also called HTML5 Storage) to store a persistent identifier for Analytics and bypass the need to set a cookie – but then you have to manually create a clientID to send to Google Analytics. See the approach used by ShootItLive. However, as their comment on line 41 says, this is not a complete solution - because there are lots of browsers beyond Safari which block third party cookies. I would take the opposite approach and check if the browser supports local storage, and only revert to trying to set a cookie if it does not. Local storage is now possible on 90% of browsers in use and the browsers with worst 3rd party cookie support (Firefox and Safari) luckily have the longest support for local storage. As a final note, I would set up the tracking on a different Google Analytics property to your main site, so that pageviews of widgets are not confused with pageviews of your main site. To do list: Build a script to create a valid clientID for each new visitor Call ga('create) function, setting 'storage' : 'none', and getting the 'clientID' from local storage (or created from new) Send a pageview (or event) for every time the widget is loaded. Since the widget page is likely to be the same every time it is embedded, you might want to store the document referrer (the parent page URL) instead Need help with the details? Get in touch with our team of experts and we'd be happy to help!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

If you are running an AdWords campaign you must have a Google Analytics account. We will show you how to link these two accounts so you can unleash the full reporting potential of both platforms. 1. Why should you link Analytics and AdWords? When you link Google Analytics and AdWords, you can: See ad and site performance data in the AdWords reports in Google Analytics. Import Google Analytics goals and ecommerce transactions directly into your AdWords account. Import valuable Analytics metrics—such as bounce rate, avg. session duration, and pages/session—into your AdWords account. Take advantage of enhanced remarketing capabilities. Get richer data in the Google Analytics multi-channel funnels reports. Use your Google Analytics data to enhance your AdWords experience. 2. How to link Google Analytics and AdWords The linking wizard makes it easy to link your AdWords account(s) to multiple views of your Google Analytics property. If you have multiple Google Analytics properties and want to link each of them to your AdWords account(s), just complete the linking wizard for each property. Sign into your Google Analytics account at www.google.com/analytics. Note: You can also quickly open Google Analytics from within your AdWords account. Click the tools tab, select analytics, and then follow the rest of these instructions. Click the admin tab at the top of the page. In the account column, select the analytics account that contains the property you want to link to one or more of your AdWords accounts. In the property column, select the analytics property you want to link, and click AdWords Linking. Use one of the following options to select the AdWords accounts you want to link with your analytics property. Select the checkbox next to any AdWords accounts you want to link with your analytics property. If you have an AdWords manager (MCC) account, select the checkbox next to the manager account to link it (and all of its child accounts) with your analytics property. If you want to link only a few managed accounts, expand the manager account by clicking the arrow next to it. Then, select the checkbox next to each of the managed AdWords accounts that you want to link. Or, click all linkable to select all of managed AdWords accounts under that MCC. You can then deselect individual accounts, and the other accounts will stay selected. Click the continue button. In the link configuration section, enter a link group title to identify your group of linked AdWords accounts. Note: Most users will only need one link group. We recommend creating multiple link groups only if you have multiple AdWords accounts and want data to flow in different ways between these accounts and your analytics property. For example, you should create multiple link groups if you need to either link different AdWords accounts to different views of the same Google Analytics property or enable auto-tagging for only some of your AdWords accounts. Select the Google Analytics views in which you want the AdWords data to be available. If you've already enabled auto-tagging in your AdWords account, skip to the next step. The account linking process will enable auto-tagging for all of your linked AdWords accounts. Click advanced settings only if you need to manually tag your AdWords links. Click the link accounts button. Congratulations! Your accounts are now linked. If you opted to keep auto-tagging turned on (recommended), Google Analytics will automatically start associating your AdWords data with customer clicks. For a deeper view and debugging you should also read the Google Analytics guide. Have any questions on setting this up? Get in touch and we'd be happy to help!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

The biggest day for online retail sales among Littledata’s clients is the Sunday after Black Friday, followed closely by the last Sunday before Christmas. Which is more important - Black Friday or Cyber Monday? Cyber Monday saw the biggest year-on-year increase in daily sales, across 84 surveyed retailers from the UK and US. In fact, Cyber Monday is blurring into the Black Friday weekend phenomenon – as shoppers get used to discounts being available for longer. We predict that this trend will continue for 2016, with the number of sales days extending before and after Black Friday. Interested in what 2016 will bring? Stay tuned for our upcoming blog post! Want to see how you did against the benchmark? Sign up for a free trial or get in touch if you have any questions!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Shoppers on Black Friday are becoming more selective – with a decrease in the number of retailers seeing an uplift in Black Friday sales, but an increase in the purchase volumes seen at those selected stores. Littledata looked at the traffic and online sales of 84 ecommerce websites* over the Black Friday weekend (four days from Friday to the following Monday), compared with the rest of the Christmas season (1st November to 31st December). 63% of the surveyed retailers saw a relative increase in traffic on Black Friday weekend 2015 versus the remainder of the season, compared with 75% of the same retailers seeing traffic rise on Black Friday 2014. This implies some decided to opt out of Black Friday discounting in 2015 or got less attention for their discounts as other retailers spent more on promotion. The same proportion of retailers (60% of those surveyed) also saw a doubling (on average) in ecommerce conversion rate** during Black Friday 2015. In 2014, over 75% of retailers saw an improved conversion rate during Black Friday, but the median improvement over the rest of the season was just 50%. 61% of websites also saw an increase in average order value of 16% during Black Friday 2015, compared with only 53% seeing order values increase the previous Black Friday. We predict that this trend will continue in 2016, with a smaller number of websites benefiting from Black Friday sales, but a greater increase in ecommerce conversion rate for a select few. Be sure to check back for what the actual trends will be for 2016! Let us know what you think below or get in touch! * The surveyed websites were a random sample from a group which got a majority of their traffic from the UK or the US. The data was collected from Google Analytics, and so represents real traffic and payments. ** The number of purchases divided by the total number of user sessions   Image credit: HotUKDeals   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

In every retail business, knowing your customers is vital to succeeding. All decisions you make about business and marketing strategies must begin from the user's perspective. Let's find out how we can build the user persona with the data that lies in Google Analytics. Even though Google's user profile is not as fancy as Facebook's, you can still have a pretty good idea about your customers. Let's start with the basics, and ask the most basic questions: How many of my customers are men or women? What is the age range of my customers? What devices do they use to access my website? How often do they visit my website? What are their interests? What makes them convert? For the first two questions, you should already have enabled Demographics and Interest reports in your Google account. If not, go to Admin > Property Settings > Enable Demographics and Interest reports. The split of age and sex can be seen in Audience > Demographics. The most interesting thing here is that you can add a second dimension to compare and see how people are different based on more than one vector. If you add a second dimension, such as Device Category, you will get a split like this: You can see from the above screenshot that females prefer mobile and are the majority user. Also when females are on desktop, they are more likely to spend more time on the website. You can go into more depth and analyse the conversion rate also. You can find out the behaviour of new vs. returning customers from the report, New vs. Returning under Audience. Add a second dimension "Gender" and you will see who's more likely to come back to your website. Based on the above screenshot, women are returning about 25% of the time, while men return about 21% of the time. Also, men have a higher bounce rate. Under Audience, you will also find the Frequency & Recency report and the Engagement report. If you create two new segments by gender: female and male, you will find who your most loyal visitors are. The interests (Google reads them from the user behaviour online) can be found under Audience > Interests. It is best to split the report based on females and males. You will now have a full view of your customers. And for the final and most important question: what makes them convert?, you can find this out by going to Aquisition > Channels. Add a second dimension by gender, age or interests and analyse the traffic for each channel. Find out what channel brings the most important users. In the screenshot below, you can see that woman are more likely to buy if the website is referred. This means that the reputation of the website is a big factor in their decision. Don't be shy when creating custom reports because you can drill down the data to multiple levels of understanding. Applying second dimensions has its limitations and you can see only a part of the information at once. If you still need a more detailed view of what each customer does on the website, we strongly recommend the User Explorer menu. We found it useful to find out how different touch points are important and how long the path is for a valuable customer. Also, it was useful in debugging and creating a marketing strategy based on the customer's flow. The bottom line is that you can answer "who is your customer?" with Google Analytics through its reports if you learn to see the report from different perspectives. Feel free to drop us a line if you use any other report that is relevant to this article!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

By default, Google Analytics allows you to segment traffic by standard dimensions such as visitor location, screen size, or traffic source. You can view smarter reports by adding custom dimensions specific for your business. Give me an example Let's say when your members register they add a job title. Would you like to see reports on the site activity for a particular job title, or compare conversion for one job title versus another? In which case you would set a custom dimension of 'Job Title' and then be able to filter by just the 'Researchers' for any Google Analytics report. Or if you run a blog / content site, you could have a dimension of 'author' and see all the traffic and referrals that a particular author on your site gets. How do I set this up? First, you need to be on Universal Analytics, and then you need to tag each page with one or more custom dimensions for Google Analytics. This is more easily done with Google Tag Manager and a data layer. It may be that the information is already on the web page (like the author of this post), but in many cases, your developer will need to include it in the background in a way that can be posted to Google Analytics. Then you will need to set up a custom report to split a certain metric (like page views) by the custom dimension (e.g. author). Please contact our specialists if you want more advice on how to set up custom dimensions!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Ever wondered why so few visitors convert on your site? One answer is that a big chunk of your traffic is from search engine spiders and other web 'bots' which have no interest in actually engaging with you. Google Analytics has a great new feature to exclude this bot traffic from your site. All you need to do is check a box under the Admin > View > View Settings. The new option is down the bottom, underneath currency selection. It uses the IAB /ABC Bots and Spiders list, which is standard for large publishers, and updated monthly. Warning: you will see a dip in traffic from the date you apply the setting. If you're looking for a more comprehensive method to exclude spam and ghost referrals, check out our how-to guide! Have some questions about this? Get in touch with our Google Analytics experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

In May 2014 Google Analytics introduced a new feature: Enhanced Ecommerce tracking. If you run an ecommerce operation, this gets you much more detailed feedback on your checkout process. What will I see? Shopping behaviour: how are people converting from browsers to purchasers? Checkout behaviour: at what stage of your checkout do buyers abandon the process Product performance: which products are driving your sales, and which have a high return rate Real campaign returns: see your real return on marketing investment including promotional discounts and returns How do I set this up? The bad news is it definitely requires an experienced software developer for the setup. The reports require lots of extra product and customer information to be sent to Google Analytics. You can read the full developer information on what you can track, or our own simpler guide for tracking ecommerce via Tag Manager. However, if you already have standard ecommerce tracking and Google Tag Manager, we can set Enhanced reports up in a couple of days with no code changes on your live site - so no business disruption or risk of lost sales. Is it worth implementing? Imagine you could identify a drop-off stage in your checkout process where you could get a 10% improvement in sales conversion or a group of customers who were unable to buy (maybe due to language or browser difficulties) – what would that be worth? Many businesses have that kind of barrier just waiting to be discovered…   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Our script for accurate tracking of time on page beats Google's default measurement to give you an accurate picture of how long users are spending on your page open and in focus. This post translates the approach into Google Tag Manager. The setup consists of two tags (one custom), one firing rule and two variables. Step by step: 1. Add the timer script as a custom HTML tag <script><br /> /*<br /> Logs the time on the page to dataLayer every 10 seconds<br /> (c) LittleData consulting limited 2014<br /> */<br /> (function () {<br /> var inFocus = true;<br /> var intervalSeconds = 10; //10 seconds<br /> var interval = intervalSeconds * 1000;<br /> var eventCount = 0;<br /> var maxEvents = 60; //stops after 10 minutes in focus<br /> var fnBlur = function(){inFocus = false; };<br /> var fnFocus = function(){inFocus= true; };<br /> if (window.addEventListener) {<br /> window.addEventListener ('blur',fnBlur,true);<br /> window.addEventListener ('focus',fnFocus,true);<br /> }<br /> else if (window.attachEvent) {<br /> window.attachEvent ('onblur',fnBlur);<br /> window.attachEvent ('onfocus',fnFocus);<br /> }<br /> var formatMS = function(t){<br /> return Math.floor(t/60) +':'+ (t%60==0?'00':t%60);<br /> }<br /> var timeLog = window.setInterval(function () {<br /> if (inFocus){<br /> eventCount++;<br /> var secondsInFocus = Math.round(eventCount * intervalSeconds);<br /> dataLayer.push({"event": "LittleDataTimer", "interval": interval, "intervalSeconds": intervalSeconds, "timeInFocus": formatMS(secondsInFocus) });<br /> }<br /> if (eventCount>=maxEvents) clearInterval(timeLog);<br /> }, interval);<br /> })();<br /> </script> 2. Add two variables to access the data layer variables One for the formatted time, which will feed through the event label And one for the number of seconds in focus since the last event, which will feed through the event value 3. Add the firing rule for the event 4. Add the tag that reports the timer event to Google Analytics Options and further information You can change the timer interval in the custom HTML tag - the reporting will adjust accordingly. Choosing the interval is a trade-off between the resolution of the reporting and the load on the client in sending events, as well as Google's 500 hit per session quota. We've chosen ten seconds because we think the users who are in 'wrong place' and don't engage at all will leave in under ten seconds, anything more is some measure of success. If you'd like assistance implementing this or something else to get an accurate picture of how users interact with your site, get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

There’s a flaw in the way Google Analytics measures ‘time on site’: the counter only starts from the second page visited, so all one-page visits are counted as zero time on site. If a visitor comes to your page, stays for 10 minutes reading – and then closes the window… that’s counted as ZERO time. With landing pages that have lots of interaction, or the call to action is a phone call rather than a click, this can be a real problem. Pasting the Javascript below onto all the pages of your site will fix the problem. The script logs an event to Google Analytics for every 10 seconds the visitor stays on the page, regardless of whether they bounced or not. But it won't affect your bounce rate or time on site for historical comparison *. We suggest you look closely at how visitors drop off after 10, 20 and 30 seconds to see which of your web content could be improved. Paste this into the source of your all your pages, after the Google Analytics script <!-- Time on Site tracking (c) LittleData.co.uk 2014 --><script>(function(e){var t=true;var n=0;var r=true;var i=function(){t=false};var s=function(){t=true};if(window.addEventListener){window.addEventListener("blur",i,true);window.addEventListener("focus",s,true)}else if(window.attachEvent){window.attachEvent("onblur",i);window.attachEvent("onfocus",s)}var o=function(e){return Math.floor(e/60)+":"+(e%60==0?"00":e%60)};var u=window.setInterval(function(){e=e+10;if(t){n=n+10;if(typeof _gaq==="object"){_gaq.push(["_trackEvent","Time","Log",o(n),n,r])}else if(typeof ga==="function"){ga("send",{hitType:"event",eventCategory:"Time",eventAction:"Log",eventLabel:o(n),eventValue:10,nonInteraction:"true"})}}},1e4);window.setTimeout(function(){clearInterval(u)},601e3)})(0)</script> What you'll see In Google Analytics go to Behaviour .. Events .. Top Events and click on the event category 'Time'.                               Searching for a particular time will find all the people who have stayed at least that length of time. e.g. 0:30 finds people who have stayed more than 30 seconds. FAQs Does this affect the way I compare bounce rate or time-on-site historically? No. The script sends the timer events as 'non-interactive' meaning they won't be counted in your other metrics. Without this, you would see a sharp drop in bounce rate and an increase in time on site, as every visitor was counted as 'non-bounce' after 10 seconds. If you prefer this, see below about adapting the script. Will this work for all browsers? Yes, the functions have been tested on all major, modern browser: IE 9+, Chrome, Safari and Firefox. What if I upgrade to Universal Analytics? Don’t worry – our script already checks which of the two tracking scripts you have (ga.js or analytics.js) and sends the appropriate log. Will this max out my Google Analytics limits? The script cuts off reporting after 5 minutes, so not to violate Google’s quota of 200 – 500 events that can be sent in one session Can I adapt this myself? Sure. The full source file is here. Need more help? Get in touch with our experts!

Google Analytics engagement reports can provide great insight into user behaviour on your site. However, it’s not obvious how to read them - and when you figure out how to read them, it’s not always obvious what’s good! The visitor frequency report is found under Audience > Behaviour > Frequency and recency in the Google Analytics menu. The report shows the sessions, by the number of visits for each visitor. Google’s explanation of how to read the frequency graph is nice and clear. However, their simplified example leaves out something important: returning users. In the graph, the visit count shown is for the whole user history, not just the period of the report. So if a visitor has come three times before the period their session will show in the three band. Similarly, if a user has visited the site five times in the past and then visits the site twice during the period, they will in count of sessions as 6 and 7. The example below is from a newly released site, where nearly all the visits are from the developers, who have been many times before - so there are no visitors in the 1,2,3,4 or 5 visit bands for this site in this period. The fact that the banding is based on the whole user history, not just behaviour during the period, can make the report much harder to interpret - you can't easily see the drop off in repeat visitation if an unknown number of return visitors at some point in their many visits history are also coming in. Fortunately, Google Analytic's segmentation capability comes to the rescue! For example, you can find out about the returning behaviour of visitors who came the first time during the period in question, with the segment - the settings are in the screenshot below. Note that you need to change the segment to filter users, not sessions, otherwise you will just create a more complex version of the built-in new users segment! Here’s an example of the sort of thing you might see with the segment, showing 3 segments: All Session (built in) 'User sessions = 1'  - custom segment for users having their first session in the period New Users (built in) Note: For the visit count = 1 band, the session count is the same across all three segments, For the visit count = 2 band, (and above) the number for all sessions is higher, because it includes all the users who came in on their second visit during the period. The number for the user sessions = 1 segment, is lower because it includes only the users who had their first visit during the period. The number for new users is zero because users are not new on their 2nd visit As you can see, the custom segment makes it possible to see the real return rate of new visitors in the period, narrowing to visitors who came the first time in the period in question. From this example, you can also see how misleading it would be to naively interpret the default 'all sessions' segment for, say, four sessions as the number who returned four times during the period - clearly there is a large number who have previous visits outside the period of the report. Note that none of the segments in the example actually gives the number of users who returned four times during the period - this is actually really difficult to obtain. Leaving that question aside for now, to extract some real insight from the approach of segmenting in the frequency report, combine that segment condition with a goal, say ‘transactions per user > 0’ - then you can see how many new users went on to a transaction, and how many visits they made during the period. Need help to set this up or have any questions? Get in touch with our team of experts and we'd be happy to answer any questions! This is a valuable segment to monitor and analyse - how many users have gone from first visit to a transaction this week, and how many sessions did they make along the way?

Enhanced ecommerce tracking requires your developers to send lots of extra product and checkout information in a way that Google Analytics can understand. If you already use GTM to track pageviews you must send ecommerce data via Google Tag Manager Step 1 Enable enhanced ecommerce reporting in the Google Analytics view admin setting, under 'Ecommerce Settings' Step 2 Select names for your checkout steps (see point 4 below): Step 3 Get your developers to push the product data behind the scenes to the page 'dataLayer'. Here is the developer guide. Step 4 Make sure the following steps are tracked as a pageview or event, and for each step set up a Universal Analytics tracking tag: Product impressions (typically a category or listing page) Product detail view (the product page) Add to basket (more usually an event than a page) Checkout step 1 (views the checkout page) Checkout step 2 etc - whatever registration, shipping or tax steps you have Purchase confirmation Step 5 Edit each tag, and under 'More Settings' section, select the 'Enable enhanced ecommerce features' and then 'use data layer' options: Of course, there's often a bit of fiddling to get the data layer in the right format, and the ecommerce events fires at the right time, so please contact us if you need more help setting up the reports! Step 6 - Checking it is working There is no 'real time' ecommerce reporting yet, so you'll need to wait a day for events to process and then view the shopping behaviour and checkout behaviour reports. If you want to check the checkout options you'll need to set up a custom report: use 'checkout options' as the dimension and 'sessions' and 'transactions' as the metrics. Need some more help? Get in touch with our lovely team of experts and we'd be happy to answer any questions!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.  

The primary concern of all PPC specialists is how to take all the traffic their ads and content generate and turn it into converting users. If you are taking the time and energy to allocate a budget and strategy for your PPC ad campaigns, literally throwing money at the problem, then you should at least be capitalising on as many conversions as possible. So what is the difference between traffic and conversions? What is it that bridges the gap between the two? Simple: the user’s experience on your page. That’s all there is to it. Optimising your landing page experiences to better fit the user’s needs and to generate a sense of delight in them is how you close the distance between traffic and conversions. There’s countless different tactics and styles of landing page optimisation that different PPC agencies employ. But, for the most part, they all circulate around the same basic concept: using consumer behaviour and basic psychology to increase the “delight factor” of a user’s experience on your landing page. The more delighted a user is with your page and your content, the more naturally they will be inclined to convert on your site. A more user-centric experience is what psychology based CRO is aiming for. Starting from the source Reverse engineering the problem’s of your campaigns is just as important as reverse engineering your goals. Just like when establishing a content marketing strategy, a landing page optimisation strategy requires you to first establish your goal (higher CRO), and then work backwards to identify the tangible changes you need to implement. To better understand how your paid ad campaigns and landing pages are performing as a unit, you need to make sure you are monitoring the right KPIs. Better yet, understanding what each KPI signifies about your user’s experience is an even deeper and more useful insight regarding your psychological research. VTC vs CTC For simplicity’s sake, let’s narrow down the field of analysis to just the advertisement and the landing page. For the first, you’re going to want to be looking at click-through conversions and view-through conversions. Now, VTC is harder to monitor because it records whenever a user sees your ad (an impression) but doesn’t click on it. Later that user revisits your page via a different route and converts on your page. If you were looking only at CTC, this conversion actually wouldn’t be given any credit. But for the most part what either form of conversion metric is doing is looking at how successful your ad is at getting the user to click through to your landing page. Conversion rate, bounce rate, exit rate Once you’ve determined the success of your ad in regards to getting them to your site, it’s time to check out how your pages themselves are performing. This is the where the fault between traffic and conversions splits open. This is where conversion rate and bounce rate come into the picture. The conversion rate is pretty self-explanatory, but the bounce rate needs a bit more nuanced definition because of its relation to exit rate, which can get confusing. Basically, the exit rate of your page examines how frequently a user clicks through your ad to your landing page and leave that specific page via regular means of navigation. They might have gone to a different content page of your domain, they may have left altogether. The bounce rate shows you how often users are leaving your page by means of the back button or closing the browser entirely. While they both monitor the departures from your landing page, one gives a very different picture from the other. You can check out the infographic below by ion interactive for basic schematics and values of the five major landing page KPIs. Asking “why they aren’t” instead of “why they are” With your performance data in hand, you now need to look one step further into the reasons behind your lack of conversions and high bounce rate. Start, as always, by reverse engineering the problem. Ask why users aren’t converting on your site and fix the wrongs of your page before you celebrate the rights. There are three major psychological reasons for a user to be displeased or distrusting of a landing page. Identifying this friction points within your landing page content will help you tailor your pages to user’s preferences and increase the “delight factor.” Lack of information The first psychological red flag for a first-time visitor is a lack of information. This can be a very significant and harmful deterrent. Not supplying the user with adequate information instantly puts them into a sceptical state. The human mind does not like uncertainty. We are famous for “catastrophizing” the unknown because our minds are programmed to fill empty spaces. We subconsciously prefer to imagine the worst case scenario rather than a complete up-in-the-air unknown. When confronted with a lack of information, users often make one of two assumptions: either your site lacks the expert level content they are looking for and your business is not a well-informed authority on the matter; or - even worse - your landing page is a scam and is actually just click-bait looking for meaningless traffic. Don’t let a lack of information put a Vader style force-choke-hold on your conversion rate. Trust leaps The biggest hindrance to a landing page is the inability to generate trust in the user. Creating genuine trust leaps between the first-time visitor and the uncertainty of a business proposition is, at the same time. the sole purpose of landing pages and their toughest obstacle. Trust leaps, however, are a three step process that takes more than just the necessary and adequate information to complete the cycle. The common progression of a trust leap, beginning to end, is “trusting the idea” - “trusting the institution” - and, finally, “trusting the individual.” Too many landing pages over-prioritize the first two of the steps and for that reason fail to convert at a satisfying rate. Making sure you are transparent and authentic in your presentation through and through is key when it comes to user experience. These days, with digital media so entrenched in our culture, we all have a strong nose for spam and we are quick to jump ship if we feel we are in shady territory. Analysis paralysis Lastly, even if you are able to build a successful trust leap with the user, there are still psychological roadblocks that can stop them from converting. You may be so eager to impress and delight your visitor that you provide them with all the different options and services you make available to them. This may seem like a transparent and efficient way to market your services. But what it really does is throws your user into pits of analysis paralysis. While you want to provide all the necessary information you can, too much info can overload the user. As much as we all would like to believe the opposite, absolute freedom of choice is one of the quickest ways to drive a person crazy. An old idiom comes to mind when discussing the issue: “When given too many options to choose from, the exit becomes the only clear choice.” Keep your landing pages simple and specified. In almost all cases, you should limit each landing page to a single CTA and a single goal. Make the decision to convert an easy one. Fixing the common problems with transparent solutions So how do you make converting on your page such an easy decision? By removing any obstacles that may be obscuring your message or deterring your viewer. The checklist is simple and straightforward. You want to lower friction between your page and the user by filling in any gaps of information that they need and eliminating any superfluous or extraneous information that may distract them from converting. After you start to lower the friction and build a more user-centric landing page experience, you can consider the more nuanced forms of data presentation that you are employing. For example, many sites love to compare their prices and performance to their competitors on their page. Comparison pricing If you have the lowest prices in the business, why not advertise by putting your low price right next to the jacked up prices of your competitors - right? This may seem like a good idea, at first. But it can actually put the idea of comparison shopping into the minds of users that previously might not have even been considering your competition. On top of that, bragging about your drastically lower prices has been shown to actually inspire a sense of hesitancy in users. They tend to believe that if you are advertising your low price as your main selling point, then your services might not be top notch and it may be worth their while spending a pretty penny on a service that is worthwhile. Don’t overthink your landing page presentations. You’re taking the time to develop trust with your first-time users, so trust them to make the comparisons on their own. Don’t impose market statistics on them as if you are in court arguing your dominance in the field. Let them come to their own decision organically - that’s where “delight” comes from. Urgency with solutions If you are looking to break down roadblocks to ease the user’s conversion path you will also be working towards speeding up and optimising that conversion path as well. True landing page streamlining requires removing inefficiencies and implementing optimizers to replace them. Many PPC management services love to inject a sense of urgency into their CTAs in order to emotionally evoke a higher conversion tendency in their audience. While this is a good idea in and of itself, and a strong “click now!” or “don’t miss out!” CTA can really close a conversion out, urgency only works to emotionally evoke readers when used correctly. Studies show that when given “urgent” warnings, subjects were actually not necessarily more eager to act. What the results showed was that when they were not given any information on how to remedy the urgent situation, test subjects were actually more likely to rationalise themselves as exempt from the urgency and were actually less eager to act! On the other hand, those subjects that were given information regarding the urgent situation (or at least most of them) followed the information provided to them and acted immediately. Remember that we do not like the unknown, so if you are trying to change the mentality of a user with urgency, you must be specific with the reasons why it is urgent and the actions necessary to remedy the situation. Like in the above graphic: if not here, then where? If not now, then when? And if not us, then who?! Put a face to the service Unless you are a snake-haired Greek gorgon who goes by the name of Medusa, matching a face to your service will always help your brand appear more trustworthy. If your landing page doesn’t have any pictures of your business teams or employees and lacks any personable touch, users might start sniffing out your pages for spam. At the very least you should have an employee directory page somewhere within your pagination - which should be streamlined and flat for easy user experience (but that’s another point of discussion, you can check out this post for internal linking strategy if you’re interested). Having a brief personal bio for each of your employees brings an approachability to your page that is sometimes lost in the online retail world. (Also, as a bonus, it will show your employees that they matter to you and aren’t just cogs in a system.) If you really want to wow the users clicking to your landing page, you can go one step further than an employee directory page and introduce employee testimonial videos or team introductions for your possible clients. Our eyes have a natural inclination to pay attention to motion, then image, then text last. So using video on your landing page (above the fold!) is a huge way to increase engagement, even if it isn’t focused on building trust. The trick is not to appear authentic, but be authentic. Users today are well informed and ready for your business, your job isn’t to finagle them into converting, but to get them to embrace you as a trusted authority - the conversions will follow. Focusing on the inputs not the outputs Using psychology in your CRO campaigns means looking one step deeper than the behaviour of users on your landing pages. It means looking into the reasons and emotions behind those behaviours. Too many conversion campaigns these days over emphasise the importance of hitting their quotas and monthly growth percentages. “Don’t make your goals, your goals, make the habits that lead to your goals, your goals.” Focusing on the inputs that will build trust and lower friction on your page instead of making all of your decisions based on minor bumps in your CR% is a simple re-allotment of your priorities and focus, but will make huge and long-lasting changes in the way you develop and design your pages. Happy users are converting users, that transitive step is a natural and quick one. So don’t focus so much on turning your users into business opportunities. Focus on delighting them and making them happy. And making them happy starts with knowing how they tick. Team Bio About Sean Martin - I am a Content Marketing Manager at Directive Consulting, a digital marketing agency in Southern California. We specialise in integrating SEO, PPC, Social, and Content into our online marketing campaigns. Check out my posts on the DC blog to see how we are innovating and changing the game.

Looking at a sample of 400 ecommerce websites using Littledata, we found mobile ecommerce conversion rates vary hugely between operating systems. For Apple devices, it is only 1% (and 0.6% for the iPhone 6), whereas for Android devices the conversion rate is nearly 4% (better than desktop). It’s become accepted wisdom that a great ‘mobile experience’ is essential for serious online retailers. As 60% of all Google searches now happen on mobile, and over 80% of Facebook ad clicks come from mobile, it’s highly likely the first experience new customers have of your store is on their phone. So is it because most websites look worse on an iPhone, or iPhone users are pickier?! There’s something else going on: conversion rate on mobile actually dropped for these same sites from July to October (1.25% to 1.26%) this year, even as the share of mobile traffic increased. Whereas on desktop, from July (low-season) to October (mid-season for most retailers), the average ecommerce conversion rate jumped from 2% to 2.5%. It seems during holiday-time, consumers are more willing to use their phones to purchase (perhaps because they are away from their desks). So the difference between Android and iOS is likely to do with cross-device attribution. The enduring problem of ecommerce attribution is that it’s less likely that customers complete the purchase journey on their phone. And on an ecommerce store you usually can’t attribute the purchase to the initial visit on their phone, meaning you are seriously underestimating the value of your mobile traffic. I think iPhone users are more likely to own a second device (and a third if you count the iPad), and so can more easily switch from small screen browsing to purchase on a large screen. Whereas Android users are less likely to own a second device, and so purchase on one device. That means iPhone users do purchase – but you just can’t track them as well. What’s the solution? The only way to link the visits on a phone with the subsequent purchases on another device is to have some login functionality. You can do that by getting users to subscribe to an email list, and then linking that email to their Google Analytics sessions. Or offering special discounts for users that create an account. But next time your data tells you it’s not worth marketing to iPhone users, think again. Need help with your Google Analytics set up? Comment below or get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.  

We all need our Google Analytics data to be correct and realistic. Ecommerce, just like any other website, needs correct data. What makes ecommerce websites more open to error is the ecommerce data capturing. We have put together a list of 5 mistakes in a Google Analytics integration that you should check before starting reporting on your online store! Top 5 pitfalls in tracking ecommerce in Google Analytics Tracking code is missing from some pages Multiple page views sent Multi- and subdomain tracking issues Wrong usage of UTM parameters Wrong usage of filters   Tracking code is missing from some pages The easy way for an established website to see if the tracking is complete is to go to Google Analytics > Acquisition > Referrals and search the report for the name of your website, as shown below. If you have a lot of pages and are not sure how to find which exact pages are missing the code, you can use the GA Checker.   Multiple page views sent The second most common issue we found is having multiple Google Analytics scripts on the same page. The easiest way to check this is with the Tag Assistant extension from chrome. Go on your website and inspect the page (see image below). You can also use the GA Checker for this. The solution is to leave only one script on the page. There are situations where you're sending data through Google Tag Manager. If you see 2 pageviews in Tag Assistant or gachecker.com, you should take a look at your tags. There should be only one for pageview tracking!   Multi- and Subdomain Tracking Issues Are you seeing sales attributed to your own website? Or your payment gateway? Then you have a cross-domain issue. And you can read all about it in our blog post: Why do you need cross-domain tracking?. You can see if this is the case by going to Acquisition > Overview > Source/Medium and find your domain name or payment provider.   Wrong usage of UTM parameters You should never tag your internal links with UTM parameters. If you do so every time a clients click's on a UTM tagged link, a new session and the original source will be overwritten. Pay attention to your campaign sources and search if something suspicious appears in the list. You'll find, you have internal links tagged when you will try to find the source of your transactions and find the name of the UTM parameters from your website instead. Read what UTM's are and why you should use them in our blog post: Why should you tag your campaigns?.   Wrong usage of filters Using filters will improve the accuracy of your data, however, data manipulated by your filters cannot be undone! To prevent your filter settings or experiments to permanently alter your traffic data you should set up separate views, and leave an unfiltered view with raw data just in case. Check your filters section and be sure you know each purpose. You can check more on this blog post: Your data is wrong from gravitatedesign.com. Need help with any of these common mistakes? Get in touch and we'd be happy to help!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

According to W3Techs, Google Analytics is being used by 52.9 percent of all websites on the internet, more than 10 times the next most popular analytics option, Yandex Metrics. But how do we really use the information in Google Analytics so we can increase our revenue? BuiltWith says that 69.5 percent of Quantcast’s Top 10,000 sites (based on traffic) are using Google Analytics, and 54.6 percent of the top million websites are those that it tracks. Most of the large websites use the information in Google Analytics to make strategic decisions about the product or information posted online. Ecommerce websites, in particular, have the possibility to improve their performance looking at ecommerce data available in Google Analytics. The Enhanced ecommerce tracking from Google Analytics is a complete revamp of the traditional ecommerce tracking in the sense that, it provides many more ways to collect and analyse ecommerce data. Enhanced e-commerce provides deep insight into e-commerce engagement of your users. You can read more on Google Support about what is possible with Enhance Ecommerce data. We will try to show you how you can optimise product listings using Enhance Ecommerce - the non-technical way. We assume that you already have the full ecommerce setup for Analytics in place and you already have access to data like this in your account: If you don't, it's worth going through this blog post: Set up Ecommerce tracking with Google Tag Manager. Also, before moving forward, you should generate the product listing performance reports based on the first part of this blog post: Use Enhanced Ecommerce to optimise product listings. As you've seen in the blog post mentioned above, having enhanced ecommerce data, gives you unlimited ways to react to the customer's behaviour. Starting with this graphic above, let's make a strategy to improve product listing and increase the website conversion rate. We have 3 situations First, we have the non-starters product category. These products never get clicked on within the list. Either there are incorrectly categorised, or the thumbnail / title doesn’t appeal to the audience. They need to be amended or removed. Second, we have the lucky products: quick sellers: these had an excellent add-to-cart rate, but did not get enough list clicks. Many of them were 'upsell items', and should be promoted as ‘you may also like this’. And last, poor converters: these had high click-through rates, but did not get added to cart. Either the product imaging, description or features need adjusting. We will focus on the non-starters and poor converters ones and give you a list of things to do. Non-starters As we mentioned before these products are never clicked. For these kinds of products, you should check and improve the following. Are they in the correct category? If not put adjust them! Does this product have the correct position on the category page? If is a product is important to you, don't leave it at the end of the category listing on page 100. Does this product have a picture? If yes, change it as it is clearly not performing. Is this product easy to find in the category when filters are applied? Is this product easy to find using the internal search of the website? Is this product part of an upsell or cross-sell strategy? Poor Convertors Are the pictures of this product clear and from all relevant angles? If this product is an expensive one, does it have a video showing the benefits? On this product page are there sufficient details about the product, their benefits, age limit, and so on? If this is an assembled type of product do you have the assembly e-book or mention that they will receive it with the package? Do you mention, on a scale, how hard it is to assemble this product? Do you have reviews from previous customers that describe this product? Do you make all the costs of this product clear, including VAT, shipping, and other taxes? Is your add-to-cart button on this page working? Is the flow from add-to-cart to check out a smooth one, with no errors, and no "out of stock" notice? Do you use retargeting if the client sees a product multiple times but doesn't seem to add it to the basket? If you have other suggestions for the list above fell free to send us your ideas and we will update it. If you are interested in setting up Enhanced Ecommerce to get this kind of data or need help with marketing analytics then please get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Google Optimize (standard edition) will be released publically at the end of October, allowing free access to powerful AB testing and personalisation features. Here’s a guide to launching your first test, assuming you have the Google Optimize 360 snippet installed on your page. Step 1: Create the experiment I want to trigger a personalisation on Littledata’s homepage, shown only to visitors from London, which promotes a local workshop we have running later this month. It’s not a real AB test, as we won’t have enough traffic to judge whether the banner is a success, but we can use the ‘experiment’ to launch this personalisation for a local audience. First, I need a new test (click the big blue plus sign) and select an AB test. I’ll name my test, and set the editor page as our homepage – which is pre-filled from Google Analytics anyway… Since I have Google Analytics linked, I can select a goal from GA as the objective. In this case, the banner will promote the event (which isn’t tracked on our site) so the only sensible goal is promoting more pageviews – but it’s possible it will also increase signups for our app, so I’ll include that as a secondary objective. Next, I need to add a variant, which is going to load my event banner. I’ve named it ‘add yellow bar’. Clicking on the variant row will take me to the editor. Step 2: Edit the ‘B’ version Note: Optimize’s editor works as a Chrome Plugin, so you’ll need to install that in Google Chrome first. It’s easy to select an element on the page to edit or hide, but my variant will load a new snippet of HTML code which is not already on the page. So I’ll select the element at the top of the page (with ID ‘content’) and then go to the select elements icon in the top left. Now I’ve got the right element to use as a building block, I’m going to add an ‘HTML’ change. And set it to insert the HTML ‘before’ the current element. I’ve pasted in the HTML I’ve recycled from another page. Once I click apply we can see the new element previewing at the top of the page. Next, let’s check it looks OK on mobile – there’s a standard list of devices I can select from. Yes, that is looking good – but if it wasn’t I could click the ‘1 change’ text in the header to edit the code. Lastly, in the editor, you may have noticed a warning notification icon in the top right of the Optimize editor. This is warning me that, since Littledata is a single-page Javascript site, the variant may not load as expected. I’m confident Optimize is still going to work fine in this case. Step 3: Launching the experiment After clicking ‘Done’ on the editor, I go back to the experiment setup. Usually, we’d split the traffic 50:50 between the original and the variant, but in this case, I want to make sure all visitors from London see the message. I’ll click on the weighting number, and then set ‘add yellow bar’ to show 99.9% of the time (I can’t make it 100%). Then, we want to set the geotargeting. The experiment is already limited to the homepage, and now I click ‘and’ to add a 2nd rule and then select ‘geo’ from the list of rules. I want the yellow bar to show only for visitors from London. The city is a standard category, and it recognised London in the autocomplete. As the final step, I need to click ‘Start Experiment’. I can’t edit the rules of any running experiments (as this would mess up the reporting), but I can stop and then copy an experiment which is incorrect. Conclusion Google Optimize makes it really simple to set up tests and personalisations, although it is missing a few features such as scheduling. The premium edition (Optimize 360) will allow more analysis of tests using Google Analytics, and also allow the import of custom audiences from other Google 360 products. This is powerful if you want to launch a customised landing pages experience based on, say, a DoubleClick display ad campaign. So try it out, and if you have any questions, contact one of our experts! Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Google Tag Manager has recently had quite a revamp to its interface. Not to mention the addition of much talked about workspaces feature. Google Tag Manager (GTM) is a great tool that saves the development and implementation time, and the new drastic changes in any of Google’s tools can be quite a shock when you’re used to one way of workflow. The latest changes to the interface are radical but as with everything else, it just takes a short while to get used to. GTM still works the same, though. There’s no change to how your tags, triggers and variables are set up. So let’s see what's changed! Overlays on top of overlays This is the biggest change in the interface! Whether you’re creating a new tag or changing an existing one, you’ll be making your updates in overlays that slide in from the right hand side of the screen. Whilst this may be confusing initially, this is a great improvement on the previous workflow. Before you had to create your variables before the tag, or if creating the tag, save the progress, then create the variable separately, and then return to the tag to add in your variable. Too many steps! The new overlay doesn’t cover the whole screen and instead, leaves a bit of space on the left so you can see where you started from. Now that I’ve embraced the workspaces, I’ve realised how great it is to be able to do changes and updates without navigating elsewhere. Icons replace colours Previously, when viewing a list of tags all the triggers were colour coded so you could quickly see types of triggers used. Now, they’re all grey with icons at the beginning. I’ve previously found the colour coding very handy in quickly determining where the tags have been set to work. I’m not convinced that the icons will do as great of a job, but like with all of the changes – just embrace them and move on. List of variables They’ve lost the ‘enabled built-in variables’ section at the top. It used to have checkboxes so you could quickly enable or disable select variables. Now you have a list of built-in variables and for any changes, you have to click ‘configure’ button and then select which ones you want or not. And of course, you’ll have to do these changes in the overlay that slides over. The variables you've created previously will be in a separate list when you scroll down the page. If you want to view the details of the variable, then you’ll have to click on the variable and see its setup in the new overlay. Remember, remember… Do you tend to forget to specify your container's name and description? Now you get reminded to do so when you click to ‘publish’ your container and haven’t set the details. Timestamps I love it when a small change can make a big difference! This is that kind of change. When hovering over any relative timestamps in the triggers, overview or other sections, you will see the exact date and time of the latest change. What are workspaces? Workspaces are multiple containers that teams and users can work on without worrying about publishing someone else’s updates that may not be ready to go live. For someone working within a number of teams, like we do, this is a very welcomed update. After using it for a few weeks, I’ve already seen improvements in the speed of publishing updates. Now, fewer people have been blocked from progressing on their tags, which is really great! So now you can make your additions or amendments in a separate space and publish them when they're ready. What really happens when you publish is that anything new in your workspace gets added to the default workspace. This may include any updates to tags, triggers, variables, and any notes you may have added. If you can, stick to making smaller sets of changes within workspaces so you have a more robust version history, allowing you to trace updates and roll back to previous versions more quickly. You’ll get 3 workspaces in total so 1 default one + 2 custom workspaces, whilst 360 accounts get unlimited workspaces. Here’s how they work. To create a separate workspace click on the ‘Default Workspace’ in the left panel. In the new overlay click on the + icon in the top right corner. Now enter the name and description for the workspace so when you choose a workspace you can quickly see what's being worked on in there, or what the purpose of the workspace is. You can always refer to these for information on what was worked on or published as part of this workspace. A new workspace will always be created based on the latest GTM version and include the latest tags, triggers, and variables. If you're publishing a workspace that has conflicting updates with another workspace, then GTM will let you know and give you the option to resolve conflicts in their very easy to use conflict resolution tool. Once you publish the non-default workspace, it will be automatically removed. Better tag management You know how GTM has a number of tag templates for the most typical tracking needs, for example, AdWords and DoubleClick. These templates are very useful for creating and maintaining tags without codes, allowing to insert only required data, and making the whole process less error-prone. Well, they've expanded their selection with additional templates from vendors such as Bing, Twitter, Hotjar, Nielsen, Yieldify and many many more. I've been setting up a number of tags from the new vendors so I'm glad to see they've finally caught up with this. Here's a full list of supported tags is available in Tag Manager's Help section.   So these are some of the most notable changes. My favourite ones are overlays, timestamps and workspaces for reasons I mentioned above. The overlays don't seem to have got much love when they were first launched, but it's definitely a step up on the previous workflow. Got strong feelings about any of the latest updates? Let me know what you love or hate in the comments below.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.   Image credit: screenshot of 'conflict resolution tool' courtesy of Google Analytics Blog

Many contact forms now use Javascript to submit and do not redirect to a new page. So to track the form, unless you trigger an event on the submit button, you need to listen for a piece of text (usually saying thank you). We have created a custom HTML script that listens to the changes in the page and triggers an event called 'formSubmitted'. This event can then be used to fire a separate tag with event details to Google Analytics. We've tested this on our contact form at Littledata and here's how you can set it up too. Step 1 The first step is to go through the contact form and see what the steps are in completing it. On ours, you just enter the information in the fields and press "SUBMIT MESSAGE". When the message is sent out, the button will say "SENT!". Here the only thing that changed was the text on the button from 'submit message' to 'sent'. We built this HTML script that listens to the changes on the page, but you'll need to change line 10 to be whatever the message is in your form. You will also need to change line 15 if you have multiple forms on the page. [code lang="js"] &lt;script&gt; // **** Littledata Javascript form tracker **** // Generates a GTM custom event called 'formSubmitted' // When an on-page form is submitted // CHANGE the text to match the message displayed // when the form is successfully completed // It is not case sensitive var text = "sent!" // By default it will search for text within the first form // Set to false if text is outside a form // or change to a higher false if there are multiple forms var formIndex = 0; // OPTIONALLY, restrict the search to an HTML element ID // If you leave this blank, the whole page will be searched; // this causes the script to run more slowly var targetId = "" // **** No changes needed to the script below **** text = text.toLowerCase() dataLayer = dataLayer || []; if (!formIndex &amp;&amp; targetId.length == 0) console.error('Form tracker needs either a form or an element ID') var checkEveryMilliseconds = 500; formTrackerInterval = window.setInterval(function(){ var target = "" if (formIndex &gt;= 0) { var form = document.getElementsByTagName('form') target = (form.length &gt; 0) ? form[formIndex].textContent : ""; } else target = document.getElementById(targetId).textContent target = target.toLowerCase() if (target.indexOf(text) &gt; -1) { window.clearInterval(formTrackerInterval); dataLayer.push({ event: 'formSubmitted' }) } },checkEveryMilliseconds) &lt;/script&gt; [/code] Step 2 Now we need to add the script to listen out for when the form is submitted. Create a custom HTML tag in your GTM container. You can name the tag 'LISTENER Contact form submit event' or anything else you will remember it by. Choose the tag type 'Custom HTML'. Copy and paste your HTML/Javascript into the textbox, and remember to change the var text (line 10) with your own text. Step 3 This tag needs a firing trigger, specifying the rules when it needs to be activated. If you can, only fire on specific pages - the script will slow down the page a little, as it runs every half a second to check the form. Give the trigger a descriptive name - here I've chosen "PAGE About us" Select trigger type as 'Custom Event' and for the event name put " gtm.load ", which means this trigger at page load. We want this trigger to work on a specific page only, so the firing rule goes 'page path equals /about-us', which means that our trigger will work on the www.littledata.io/about-us page only. If you have a number of pages that have the form you're tracking, then you could use 'contains' rule and select part of the link that is applicable to all. For example, if all of your links have word 'contact' in them, then your firing rule would say 'page path contains contact'. Step 4 Now that you have your listener tag set up, you need to create a separate tag to send the event details to Google Analytics. Again, give it a descriptive name so you know what it's for - here I've used 'GA event - contact form submitted'. Select tag type as 'Universal Analytics' and in the tracking ID field, select the variable that contains your GA tracking id. For event category, action and label you have to specify the namings by which this data will be categorised in Google Analytics. Step 5 This tag needs its own trigger to know when to fire, and here you have to use the event created by the listener tag set up during steps 2-3. Here you have to specify that this tag can only fire when event 'formSubmitted' happens. I've called my trigger 'Contact form event', selected trigger type as 'custom event' and entered event name 'formSubmitted. Now you can save it and test in the debugger mode. Try submitting your contact form and see if the event 'formSubmitted' appears. You should also see the tag 'GA event - contact form submitted' fire. If everything's ok, publish the container and do a final test. Make a new form submission and check if you can see the event details come through in Google Analytics real time reports, under events. Need some help setting this up or Google Tag Manger? Why not get in touch by contacting our lovely Google Analytics experts?   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights. Further reading: How to set up event tracking in Google Tag Manager Why should you tag your campaigns? Set up Ecommerce tracking with Google Tag Manager

I’ve been an Optimizely certified expert for a couple of years and have now trialled Google Optimize 360 for a few months, so it seems a good time to compare how they stack up. Optimizely is the current market leader in AB testing (or content experimentation), due to its ease of use and powerful reporting tools. It gives companies an easy way to run many concurrent tests and manage their setup and roll out without the involvement of developers. That was a big step up from Google Content Experiments, where the only way to set up an experiment is to write some Javascript code. The Guardian had some success with Optimizely, where they increased subscriptions by 46%. Google Optimize is an equivalent testing tool, and has copied much of the user interface that made Optimizely popular: you can click on elements within the page to experiment, and change their style, hide them or move them. My only complaint is that the interface is so simple it can take a while to unbury powerful features, such as transform the page via a custom script. There have been many success stories of companies implementing Google 360. Technically, Optimize’s editor is a bit smoother; using a Chrome plugin avoids some of the browser security issues that bugged Optimizely (since internet browsers confused the Optimizely in-page editor with some kind of script hacking). For example, to load Littledata’s homepage in their editor I have to enable ‘insecure scripts’ in Chrome and then navigate to a different page and back to force the editor to re-render. For reporting, Google Optimize 360 gives the ability to see results either in Optimize or as a custom dimension in Google Analytics – so equivalent to Optimizely. Right now Optimize lacks some features for advanced scheduling and user permissions, but I expect those to evolve as the product gathers momentum. The critical difference is with the targeting options Optimizely allows you to target experiments based on the device accessing the page (mobile vs desktop, browser, operating system) and for enterprise plans only to target based on geolocation. The limitation is that every time Optimizely needs to decide whether to run the test, the check for the user’s location may take a few seconds – and the landing page may flicker as a test rule is triggered on not. Google Optimize can target to any audience that you can build in Google Analytics (GA). This means any information you capture in Google Analytics – the number of previous visits, the pages they have previously seen or the ecommerce transactions – can be used in a test or personalisation. For example, in Google Optimize you could serve a special message to users who have previously spent more than $100 in your store. Optimizely has no knowledge of the users’ actions before that landing page, so the only way you could run an equivalent personalisation is to expose this previous purchase value as a custom script on the landing page (or in a cookie). The beauty of Google Optimize is that you are targeting based on information already captured in Google Analytics. There is no technical setup beyond what you were already doing for Google Analytics, and it doesn’t take a developer to build targeting for a very specific audience. Pricing Optimizely starts from under $100/month, but to get access to enterprise features (e.g. for geo-targeting) you will need to spend $2000 plus per month. Google Optimize is currently being sold at a flat rate of $5000 / month for the basic tier of Google 360 customers (which have between 1M to 50M sessions per month), but in future, it could be offered at a lower price to smaller companies. Conclusion Where you’ll appreciate the benefits of Google Optimize is for running personalisations based on complex rules about previous user behaviour, or the campaigns they have seen. The more different tests you are running, the more time and simplicity saving you will get from building the audience in Google Analytics rather than some custom scripts. Google Optimize 360 is currently in beta but you can currently add your email to invite list. For smaller customers, or those with less complex needs, Optimizely still offers better value – but that might change if Google were to offer a limited version of Optimize at a lower price.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.   Further reading: Create and customise dashboards and widgets in Google Analytics New in Littledata: an improved navigation, trend detection algorithm, and more How to set up internal searches in Google Analytics Image credit: Blastam  

Every view in Google Analytics comes with a default "My Dashboard". Learn how to customise your dashboards and widgets for the best account overview. Dashboards contain one or more widgets (up to 12 per dashboard) that give you an overview of the KPI’s that you care about most. Create your dashboard To create a dashboard, navigate to your view, then: Go to reporting tab. Click dashboards. Select + new dashboard. In the create dashboard pop-up select blank canvas (no widgets) or starter dashboard (default set of widgets). You can also import dashboard configurations from the solutions gallery, where is most likely that someone thought about some of the KPI’s you are interested and already build a dashboard. Give your dashboard a title, then click create dashboard. Add widgets to your dashboard A dashboard can have up to 12 instances of the following kinds of widgets <piece of information>: Metric—displays a simple numeric representation of a single selected metric. Timeline—displays a graph of the selected metric over time. You can compare this to a secondary metric. Geomap—displays a map of the selected region, with the specified metric plotted on the map. Hover over the map to see the actual metric values. Table—displays up to 2 metrics describing the selected dimension, laid out in a tabular format. Pie—displays a pie chart of the selected metric grouped by a dimension. Mouse over a slice to see the specific metric values. Bar—displays a bar chart of the selected metric grouped by up to 2 dimensions. Mouse over a slice to see the specific metric values. Difference between standard vs. real-time widgets Some of the available widgets can display their data in real-time. These widgets update the metrics automatically (standard widgets, by comparison, update when you load or refresh the dashboard). Real-time widgets can display only the active users or pageviews metrics, depending on the widget. The following widget types are available as real-time widgets: Counter—displays a count of the active users on your site. You can optionally group these users by a selected dimension. Timeline—displays a timeline graph of pageviews on your site for the past 30 to 60 minutes. Geomap—displays a map showing where your active users are coming from. Table—plots a table of your active users against up to 3 selected dimensions. How to add a widget to a dashboard: Create a new dashboard and select blank canvas, or click + add widget on an existing dashboard to open the widget editor. Select the type of widget. Configure the widget’s dimensions, metrics and other options. These vary depending on the type of widget. Scroll or use the search box to locate the specific metric or dimension you want. You can limit the data shown by the widget by clicking add a filter. Filters let you include or exclude data in the specified dimension that match your filter criteria. You can add multiple rows to your filter definition. All conditions must be met for the filter to work. Report and dashboard filters are not the same as view filters. View filters permanently change your data, while report and dashboard filters only limit the data displayed in the report or dashboard. Dashboard filters are specific to the dashboard in which you define them. You can link the widget to a report or a URL. Doing so makes the widget title a link, taking you to the specified report or web page. To link to a report, begin typing a report name. Google Analytics will autocomplete your entry, trying to match it to an existing report. Alternatively, you can copy and paste the report’s URL into this field. Enter a widget title or accept the suggested title. Click save. Add a linked report directly to your dashboard Another way to link a report to your dashboard is to add it directly from the Google Analytics reporting tool. Locate or create the report you want to see in your dashboard. Click add to dashboard below the report title. Select an existing dashboard, or create a new one by clicking new dashboard. Select the check boxes for the dashboard widgets you want to include (e.g., table, pie chart, timeline). You can add up to 2 widgets per report to your dashboard. You can change the widget titles using the click to edit links. Click add to dashboard. Your new linked report widget opens on the dashboard you selected. Use the widget title link to open the underlying report. Linked report limitations Linked reports can’t have metric filters or secondary dimensions. If you try to add a report with a metric filter or secondary dimension, you will see a warning icon. Hover over the icon to see the warning message. You can still add the report, but it will not include the filter or secondary dimension. You can only embed the data view of a report in your dashboard. If you try to add a report that uses another view of the table (e.g., percentage, performance, comparison or pivot), you will see a warning icon. Mouse over the icon to see the warning message. You can still add the report, but it will display only the data view. Linked reports display only the first two metric columns from your reports. If your report contains more than two metrics, additional metrics will not be displayed in the dashboard. Edit a widget To modify an existing widget, mouse over the widget title, then click the edit (pencil) icon. To delete an individual widget, mouse over the widget title, then click the close (X) icon. Clone a widget You can create an exact copy of a widget using the clone widget link. This is convenient when you want to use one widget as a base for another. Add segments to your dashboard In the Google Analytics reports, you can add segments to your dashboard, allowing you to compare and contrast metrics generated by different session or user groupings. To edit an existing segment, click the segment label at the top of your dashboard. To add a segment, click the empty + add segment label. You can learn more about segments. Share your dashboard with other users Dashboards are private to you until you share them. If you develop a dashboard that you think is useful to other users in your account, or to other Google Analytics users in general, you have several options for sharing it. You can also send a snapshot of your dashboard data via email or generate a PDF file you can distribute however you please. Share dashboards with the current view Once you have your private dashboard working the way you like, you can create a copy of it to share with other users. When you do this, anyone with access to this view can see the dashboard’s data and add to or edit any widgets contained in the dashboard. There’s no way to make dashboards read-only; however, changes to the shared dashboard won’t affect your private version of that dashboard. You must have edit permission to share dashboards and data with the current view. If you have only read-only permission, you can still share your private dashboard by sending it as a template link or by adding it to the solutions gallery. See below for more information. To share a dashboard with the current view: View the dashboard you want to share. Click share > share object A copy of the current dashboard will now be available to all other users in that view, located in the shared dashboards section of the reports panel. Note: to unshare the dashboard you must delete it. Share dashboard templates with other views and accounts The share > share template link option generates a URL you can copy and send to other users, embed in a document or host on a website. When you share a dashboard via a template, you share only the settings for the dashboard - you do not share any data. You can send the link to anyone with a Google Analytics account, and that person can then import the settings. Learn more about sharing customizations via templates. Share dashboards in the solutions gallery The solutions gallery lets you share and import custom reporting tools and assets, like dashboards and segments, into your Google Analytics accounts. When you share a dashboard using the share > share in solutions gallery, only the dashboard’s configuration is shared. Your personal information and Google Analytics data stay private in your account. Learn more about the solutions gallery. Send dashboards via email If you need to distribute a snapshot of your dashboard data to people who might not have access to your Google Analytics account, the share > email option is for you. You can send them a customised email with an attached PDF file showing your dashboard to any valid email account. Scheduling dashboard emails Dashboard emails can be sent as “one-offs”, or you can schedule them on a recurring basis. Use the frequency controls to select the timing of the email. By default, recurring emails will be sent for 6 months. The advanced options let you adjust this from 1 month to 1 year. After this period expires, you’ll need to set up the recurring email schedule again. Tip: If there are any previously scheduled emails, you’ll see a link allowing you to add to an existing email. This lets you send out multiple dashboards or reports using the same distribution and timing. Manage all your scheduled emails by navigating to admin > views > select your view > personal tools & assets > scheduled emails. Export dashboards to PDF The export > PDF option saves a copy of your current dashboard exactly as it appears on screen to a PDF file. You can then embed or distribute this exported view in other documents as needed. Get Social! Follow us on LinkedIn, Twitter, and Facebook to keep up-to-date with Google Analytics.   Further reading: Vital Google Analytics custom reports and dashboards for ecommerce Attributing goals and conversions to marketing channels Tips to optimise your ecommerce landing pages

Every business has their own strategies and tools to achieve goals and performance. There are millions of new apps and software being built from accounting software to simple infographic tools. We did a bit of digging and found some small business tools, we think are great and you may like as well! Intercom Intercom is a customer messaging platform, which allows companies to communicate with their clients in a way that’s ‘simple, personal, and fun for everyone’. They have a few internal tools to make communication easier, including a live chat, marketing automation, and customer support. These allow you to chat with visitors while they’re on your website so you can convert them right away, you can onboard and retain customers through emails, push and in-app messages, and customers can ask for help in your app by email or social. So Intercom has done wonders for communications! We investigated more, and they’ve done a little more... They offer books that help companies communicate better and luckily for you, you can check them out here! At Littledata, we’ve integrated Intercom into our web app to allow clients to contact us directly in their own time, and for us to send important updates. Read more about it in our blog post: New In Littledata! Xero Xero is a ‘beautiful accounting software’ that gives you a real-time view of your cashflow. It’s set up in the cloud, so you’re able to login anytime, anywhere and from any device. It’s the best way to get paid faster; you can send invoices directly to your customers online, and get updates when they’re opened. As Xero says, “it’s a small business accounting software that’s simple, smart and occasionally magical”. Here’s a wonderful and insightful video of how it works: To give you real customer feedback, Xero has a few stories that give you insights into why small business have used them. Think it’s a branding source for Xero? Nope. They’ve taken the soul of these companies and created videos to showcase thriving businesses. Some testimonials include getting up to speed on financials with no number-crunching, bringing tech and craft together, efficiency and transparency, and more. Trello Trello is an ‘easy, free, flexible, and visual way to manage’ projects and organise anything. It’s used by many companies from all over the world for many different reasons. Not only can you visualise a whole company, but you can personalise the boards to your company branding, making it your own. Through Trello boards, you can keep track of clients, assign tasks to individuals, move projects along a path, customise your approach, and more. It’s the perfect small business tool to help you visualise your progress. At Littledata, we’ve created numerous boards based on different aspects of our business from development to marketing, which allows us to work better as a team. Skype Skype is a communication application that ‘keeps the world talking, for free’. It’s a perfect small business tool to not only keep in contact internationally, but you can create group calls among team members with both internally and to remote teams. Over the past few years, Skype has evolved bringing more efficient communication to companies and individuals. You’re not only able to call Skype to Skype, but you can have group calls, call phones anywhere in the world, and trust us, at a much lower rate, and you can screen share, which simplifies training or calls. At Littledata, we currently use Skype to communicate within our London office when working remotely and to share documents, and we use it to keep up to date with our Romanian office. Through weekly meetings and constant updates, we’re able to know how to efficiently help one another and work as a team, regardless of the time zone. Meetup ‘Meetups are neighbours getting together to learn something, do something, share something...;’. It’s the world’s largest network of local groups, making it easier for anyone to organise groups based on common interests. It’s a perfect small business tool, helping people around the world organise themselves to make a difference. As a business you can create groups to showcase your product, giving potential clients a more personal contact, while taking advantage of Meetup’s vast audience. Not only can you use it for business purposes, but there are numerous creative groups from badminton, marketing analytics to cultural groups. Canva Canva empowers the world through design by giving individuals an easy-to-use program for creating beautiful designs and documents. Whether you’re using one of their professional layouts or creating one yourself, you’ll always be showing off stunning graphics, that are simply created through their drag-and-drop feature. You’re not only able to create flyers and banners, but magazine covers, CVs, business cards, and even social media graphics. Canva provides perfect sizing to make all of your designs perfect for any online profile. Not only do they give you different options, but you can add all those cool extras, such as fonts, shapes, and filters. Fireshot You can use the business tool, Fireshot to take screenshots with a few clicks. It gives you different options, including selections, entire web pages, and the visible part of a website. This tool saves time, and allows you to customise by performing quick edits, add text annotation, choose the format of the file, and there are different options to keeping the file. At Littledata, we use this strategy to take screenshots of our web app, which helps us in writing our blog posts to show our clients, and people needing Google Analytics information. It basically helps us promote ourselves! Dropbox Dropbox gives people a trustworthy and secure approach to managing their files. It ‘simplifies the way you create, share, and collaborate’. With a simple download, businesses can have access to all company files from anywhere, bringing teams together constantly. This is a great tool for small businesses as it’s inexpensive, it works with all email providers, and you have an unlimited amount of space. Zoho CRM Zoho CRM ‘empowers the teams and businesses that use it’. It offers insights into running your business, an easy-to-use program, and a solution to processes. It combines good practices, smart choices, and ideal situations into a customised business tool. This business tool is great for small businesses who want to keep track of their sales and manage their client relationships. It allows for custom layouts that make it easy to tailor different approaches to getting more leads or accounts. For the amount of flexibility, Zoho CRM is inexpensive and their customer support is great in helping determine the perfect layout for your business needs. AnswerThePublic AnswerThePublic captures individual’s questions and gives you an aggregated view into motivations and emotions. They basically developed a mind-reading platform that gives topics for content, allowing for new conversations and direct answers to the public’s questions! Here’s a fun video on how this business tool works: The Seeker Littledata Our web app gives you simple and actionable insights into your website’s performance by wading through hundreds of Google Analytics metrics and trends. Our goal is to give you summarised reports that matter based on your goals and priorities. You can find out more about specifics in our blog post: A guide to reporting in Littledata’s web app. We also offer some great freebies! These include a free 30-day pro trial or an audit. With the trial, you get access to pro reporting, where you can see intricate details of significant analytics. With the audit, you get a list of recommendations for how to improve your tracking, which we can set up for you and provide further analytics support. Want more info? Contact one of our wonderful experts! We’re a business tool that allows you to get more from your Google Analytics. Grasping the data can be overwhelming so we’d like to remove that stress and help you look at trends that matter. Our web app does the hard work for you by finding important data, so you just need to look at the app or wait for important alerts that you receive by email! Have any other great business tools? Why not let us know in the comments below! Get Social! Follow us on LinkedIn, Twitter, and Facebook to keep up to date with Google Analytics. Further reading: Inspirational stories of data A guide to reporting in Littledata's web app Image credit: Image courtesy Intercom, Xero, Trello, Skype, Meetup, Canva, Fireshot, Zoho CRM, AnswerThePublic

I took part in an interesting discussion about when the popular ‘freemium’ model for web apps is viable. Startup dogma says that scalable software/web products must be (at least partly) free, so it's worth reiterating the downsides of this approach. Here’s how I see the economic realities: 1. Free brings you the wrong sort of users UK supermarkets are currently locked in a price war to try to grab market share, so let’s imagine Tesco were crazy and desperate enough to offer free cases of beer to all shoppers. Do you think their overall sales would suddenly rise that day? Or would freeloaders come from around town to collect free beer… and then buy their groceries from Asda or Sainsbury’s, as usual? Giving away free products, including free web apps, discourages users from thinking about whether they value the product – and would ever pay for it. Often free attracts the kind of time-rich, cash-poor user who will go to extreme lengths to avoid paying – so frustrating the ‘pay for extra convenience’ premium package of many freemium models. Conversely, offering a free trial and taking payment options up front confirms that customers can and will be able to pay. GoToMeeting’s CFO found their conversion rate of ACTIVE trial users to paying customers was 45% when credit card details were taken up front – as opposed to 3% when they were not. 2. Low payment conversion rates need massive active user bases Most freemium products report less than 5% of active users paying for the service, with the conversion rate generally closer to 1% if you look at all users (including inactive). So with a standard consumer subscription fee of $20/month you would have an Average Revenue Per User (ARPU) of $20 x 12 x 1% = $2.40. To get to a respectable turnover of $10m per year, (I'd suggest the minimum aim for an Angel or seed funded startup) you would need over 4m users. And to get to VC-exit/IPO scale you would need 50m users. That is achievable for mass-adoption products like Evernote and Dropbox but really isn’t if you’re in a niche market like schools. There are less than 4m teachers in the whole of the USA, and expecting to get more than 10% of them adopting your product is cuckoo-land talk. For example, Busuu (a language learning marketplace) boasted 45m million users last year but only $12m in revenue – under 30 cents per user. Busuu is probably just safe with a huge market, but for an app with impressive global traction that is a very small reward: Facebook makes $6 per user per year just from advertising. 3. Low customer lifetime values limit your marketing options If your lifetime value per user is $3 - since the average subscription length is likely to be around a year – there are very few marketing options beyond SEO or word-of-mouth. You can’t justify affiliate deals, pay-per-click or display advertising if you can’t afford to buy customers. e.g. If you buy a keyword for even $0.30 you would need a bullish 10% signup rate even to break even on the marketing spend. Freemium businesses have genuinely got to sell themselves, and so must focus on the product first. The exact opposite was ScreenSelect (which merged into LoveFilm and then Amazon film rental) – customer growth could be bought with the predictable recurring revenue. All LoveFilm did, was promise a marketing agency the first few months of a customer’s subscription payments, and the agency worked out which tactics would be profitable at that level. See William Reeve’s great explanation of the economics. But that only worked when the customer lifetime value was $100 or more. 4. Freemium generates huge buzz but little sustainable profit A big trap in startup business model innovation is following pundits saying ‘freemium is really working for X company’ when ‘working for’ means they are getting loads of users and publicity. In itself publicity is a good thing – ‘product as the message’ – but it will only translate into profit if there is a massive market to capture. Here's the dirty secret: many venture-capital funded businesses are more focused on user growth than revenue because hyper-growth of users increases their valuation faster than moderate revenue growth. So don’t copy them if you plan to grow your company without massive VC funding! How many truly big businesses make the majority of their revenue from premium subscriptions backed by free software? From an article in 2011 here is a decent list who are still going strong: LogMeIn (switched to free trial) Dropbox Skype Spiceworks Lookout Eventbrite Zendesk Evernote SurveyMonkey GitHub What they have in common is mass-market, simple tools with massive international business audiences, and masses of venture funding behind them. But there are plenty of other former tech darlings who flamed out before making the critical mass of users – e.g. Helpstream in 2010. Conclusion: freemium is not for bootstrapped companies I’m not saying freemium can’t work for you, but be very wary of following the freemium orthodoxy unless you have: A potential user base of more than 10m (and preferably 100m users) A product so simple it doesn’t need training or support to get set up Substantial funding – it takes a long time to build enough users to generate cost-covering income For many businesses, the fabled networked effects of all those free users will be out-weighted by the opportunity cost of not charging some of them from the start. To profitability and beyond! Have any questions? Comment below or get in touch! (Chart: How Much Is the Average Facebook User Worth? | Statista)   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

We're very used to having to explain what the difference is between total and unique events in Google Analytics. Like many other puzzling metrics, this has consistently been a head-scratcher for more people than we can count. Whilst you may have been in this situation like we have, you might not know that this was often due to a problem in the metric! But thanks to the released update, this is now fixed for both internal and clients’ reporting. You can read more about this update in Google's blog post: Improving Google Analytics Events with Unique Events. So what was the issue? The issue was that the unique events metric wasn’t correctly taking into account all event dimensions when calculating your numbers for the reporting. This caused many discrepancies, which probably created those numerous confusing situations around what the number stood for. The unique events metric was always meant to show you the unique count of individual interactions (or events) within a single session. So if someone downloads the same PDF 3 times during 1 session, then that counts as 1 unique event. Instead, it has been counting how many unique numbers of times a specific combination of values is seen in the report per each row. This example by Google is very helpful in getting to grips with what this means. In the example at the top where you can see all three values for various event fields, you get the same count for both new and old unique events metric - each gets 3. In the second example, we exclude one dimension and get a different result. Now, because one set of values is hidden (event label) then the calculation takes into account only what is seen in the report. But the new metric, accurately now, knows that there is a third set of data, which is taken into account in its calculation. What’s the fix? Current unique events metric has been renamed to ‘Unique Dimension Combinations’ (UDC) - a bit of a mouthful - to reflect that it was counting the uniques of dimension combinations, not individual interactions! You’ll still be able to use it as a metric if you need to compare old versus new data or are doing any analysis on the legacy data that it is attached to. The calculation for the unique events metric will now take into account all event dimensions when calculating the number. Due to this change, all event fields are now also required to contain a value - any blanks will get a (not set) value. In your standard Google Analytics reports, you’ll see the new unique events metric with the label ‘NEW’ attached to it. That’s when you know you’ve got the fixed metric in your reports. The new unique events metric will apply to the data as far back as May 2016. BUT, the fix won’t be applied automatically to your custom reports. If you have any custom reports that reference the old unique events metric, the naming will be updated to UDC. Google has provided a neat method to update your custom reports too. So you get a choice whether you want to keep using the deprecated old metric or switch to the updated unique events metric. When making the choice, bear in mind that UDC may eventually be removed so you might want to jump on the fixed uniques metric straight away. Whilst not the most exciting update on its own, this is important for the accuracy of reporting. All of our clients use events tracking so any updates to improving the accuracy of events reporting and analysis are a welcome change. Have any questions about this update? Get in touch with one of our experts! Further reading: What is Google Analytics? Overview for beginners Common reasons for tracking events How to set up event tracking in Google Tag Manager Images: courtesy of Google

Learn how to set up site search (internal search) with and without query parameters and see how users search your site. Find what your customers are researching for on your website and improve your website content. The site search reports provide data on the type of content people are looking for on your site. Having site search data is like reading the minds of a subset of your audience. You can easily see what they’re looking for, the words and terminology they are using and how quickly they found what they were looking for (or if they did at all). Site search must be set up for each reporting view in which you want to see user search activity. To set up site search for a view: sign into your analytics account, navigate to a view in which you want to set up site search then click view settings and under site search settings, set site search tracking ON. In the query parameter field, enter the word or words that designate an internal query parameter, such as "term,search,query". Sometimes the word is just a letter, such as "s" or "q". Enter up to five parameters, separated by commas. The simplest way to know what your query parameter is is to go to your site and perform a search for something, anything! On the following page, take a look at the URL – do you see your keyword? If your keyword appears at the end of a URL following a question mark, like this: http://www.yourwebsite.com/?s=your+keyword, this means that your website is using query parameters. If your keyword appears in the middle of the URL, with no query parameters, like this: http://www.yourwebsite.com/search/your-keyword/ then this means you need to use the Page Paths. How to identify search query parameters for Site Search with Queries If you’ve identified that your search keywords show up in the query parameter portion of the site, you’re in luck! This is the easiest way to set up Site Search. When you're searching on your website, you might see the URL like this: http://www.yourwebsite.com/?s=your+keyword, or in this example blog.littledata.io?s=internal+search. The query parameter is the bit between ? and =, which is 's' in this example. So you must use the query parameter ‘s’ when setting up the internal search in Google Analytics settings. Now to set this up in Google Analytics, follow these steps: Select whether or not you want analytics to strip the query parameter from your URL. This only strips the parameters you've provided, not any other parameters in the same URL. Select whether or not you use categories, such as drop-down menus to refine a site search. If you select 'no', you are finished. Click save changes. If you select 'yes': In the category parameter field, enter the letters that designate an internal query category such as 'cat, qc,'. Select whether or not you want analytics to strip the category parameters from your URL. Note that this only strips the parameters you provided, not any other parameters in the same URL. This has the same functionality as excluding the URL query parameters in your main view: if you strip the category parameters from your site search view, you don't have to exclude them again from your main view. Click apply How to set search terms for Page Path Search Terms (No Queries) Another common behaviour of site search is to have the terms appear within the page path instead of a query. Like this: http://www.yourwebsite.com/search/your-keyword/ To track this type of site search, an advanced filter should be used for views that will be using these reports. First, navigate to filters > new filter under your view. (Note: when adding a filter, you must have EDIT rights on the property level!) After choosing the filter name, select ‘custom’ and ‘advanced’ in the filter’s settings. Choose ‘request URI’ for field A since we are getting the information from the URI, or page path. Your site’s page path goes in the text box, so for this example, it would look like this: search/(.*). When we do this, we are telling Google Analytics to look at this page path and extract the characters from within the parentheses. The dot and asterisk are regular expressions representing any character and any number of characters - so we are storing anything after the slash. Field B will be blank since we are only concerned with extracting from the page path and nowhere else. The next field, ‘output yo’, is the one we are interested in. Now that we have stored the keyword from the URI, we need to output it to the correct dimension. In the drop-down menu, select ‘search term’ and type ‘$A1’ into the input box. This tells Google Analytics to grab the user-defined value from field A and output it as a search term. For the checkbox options below, only ‘field A required’ and ‘override output field’ need to be selected. See site search data To see the site search reports: sign into your analytics account, navigate to your desired account, property, and view, then select the reporting tab and under behaviour go to site search. Your report must look like this: Take into consideration that the report will be populated with data from the moment you activate the internal search or add the filter. It is not retroactive and may need 24h to you see the queries in your report. If you'd like to know more about how to set up internal searches in Google Analytics, get in touch with one of our experts! Further reading: Attributing goals and conversions to marketing channels 9 tips for marketers using Google Analytics Trust your Google Analytics data with correct setup Image credit: Image courtesy of hub.3dissue.net  

In this day and age, I find it hard to imagine how an online business is able to ensure its competitiveness without seeing how they're performing digitally. How will you know whether you need to re-design your basket or product page without seeing how these pages are performing? Or which social networks are best at driving your sales? That's why you need analytics tracking. You have a choice between multiple platforms, like Google Analytics, Kissmetrics, Mixpanel, and Heap, each with its strengths and weaknesses. Depending on what you are trying to achieve, a choice of two platforms might be most suitable, and we are able to help if needed. We have done a number of audit sessions with clients where we talked through their requirements and what they wanted to achieve and then suggested which platform or platforms are most suitable for them. Get in touch if you need help determining what is most suitable for driving your business growth! If you're looking for more information about Google Analytics, have already chosen it as your analytics platform and feel lost, then read on and check out the video below. It is the most common analytics tool used worldwide, with an estimated 30 - 50 million websites having installed the tracker (Source: Marketing Land). It is an undisputed leader in website performance tracking and because it is so commonly used, it is much easier to find support and services for it. Not to mention a plethora of plugins, widgets, guides and resources online! Google Analytics helps you find what people are doing on your site or mobile app, which marketing campaigns are driving your traffic, and how people are converting into engaged users or paying customers. You get a number of standard reports by default, but reports around acquisition and conversions, which require additional setup, unlock the true power of Google Analytics. In the video below you'll find out what Google Analytics reporting looks like, what it can do for you and explain some key reporting features by showing you: what a standard report looks like typical reports to look at conversion goals and how to set them up attribution Have a look! Now that you've seen what Google Analytics is about, you should have a play with a fully-implemented Google Analytics demo account. It's a great way to get a practical experience with their various reports, and what you can achieve if you get expert help to set up the advanced reports. Check out the demo account and get in touch with our team if you want to unlock the true power of Google Analytics reporting.   Further reading: Attributing goals and conversions to marketing channels 9 tips for marketers using Google Analytics Trust your Google Analytics data with correct setup Image credit: Image courtesy of hub.3dissue.net

Littledata’s web app gives you simple and actionable insights into your website's performance. Our app scours through hundreds of Google Analytics metrics and trends, in order to give you summarised reports, alerts on significant changes, custom reports and benchmarks against competitor sites.       This guide will give you the ins-and-outs of how we generate those important reports that help you make decisions in driving your business. Here’s a glimpse of what’s below: Free core reporting for unlimited users How to authorise access to your Google Analytics data Picking the right Google Analytics view for reporting Our range of reporting features, including custom reports and industry benchmarks How to check significant changes and page trends Long-term tracking and reporting You’ve signed up - what are the benefits? So you’ve now signed up and you’re ready to get started… but what are the benefits of signing up? Well… You’re getting automated reporting, meaning our web app looks through all of your Google Analytics reports to find significant changes. There are over 100 of them, so it will save you a lot of time not having to look through these manually. We split these findings across 5 different sections so you know quickly what you can find under each. We help you keep your data clean by looking for spam referrals. This has been a common problem for a while and a fix can be complex to set up. So we’ve created a feature that does it automatically for you (or you just need to approve it when you see it). If you get new spam referrals, we’ll spot these and let you know again. We’re also benchmarking your site against other websites, so you know where you have a competitive advantage and where you don’t. On top of all these goodies, there’s no installation needed so you get access to our web app right away! We recently updated a few important aspects of our app and you can read all about them in our blog post: New in Littledata: an improved navigation, trend detection algorithm, and more. Accessing your Google Analytics data As a Google Analytics user, you will already be sending data to Google every time someone interacts with your website or app. Google Analytics provides an API, where our app can query this underlying data and provide you with summary reports. During the signup, you would have seen an authorisation window, asking for permission to view your Google Analytics data. This means you granted us READ access. Be assured, that we will not be able to change any data or settings in your Google Analytics. Your data is viewed only by the algorithms in the web app. You pick which Google Analytics view to report on Once you’ve authorised the access, you will select the Google Analytics view that you want to set up reporting for. Some companies will have multiple views set up for a particular website. They might have subtly different data – for example, one excludes traffic from company offices or focuses on the blog traffic only – so pick the most appropriate one. If you’ve made a mistake in choosing your view or want to set up another one, don’t worry, you can always do it by clicking on the existing view in the top-right corner and selecting the option ‘set up another site’ from the drop-down menu! During the initial signup, we ask for an email where you want to get your alerts. This is because a lot of people don’t necessarily use the same email address to access Google Analytics and check their emails. Don’t worry… we’re not going to spam you, we just want to make sure you don’t miss any of your reports! When you get to the reports list, you might see something like this: Now, don’t be sad if you’re not seeing anything quite yet - we’re still checking and will only let you know when there’s something interesting to check. Just be sure to check back or wait for an email alert from your talented expert! Google Analytics Audit The first thing that we are going to analyse is your setup, in order to see what is working on your website and what is not working properly. There are more than 10 Google Analytics checks that we are verifying. The audit is almost instant and it will give you an idea about what is happening throughout your website. For each correct check, there will be provided a brief description and the dates when it was verified, whereas for the wrong checks there will be a guide on how to fix that issue and also the dates when it was found as faulty setup. Some of the checks include aspects about demographics tracking, excluding spammers, checkout steps, visitors' anonymity, campaign tagging on social and email, exclusion of company traffic, if conversion goals are set up and many other. If you ever have doubts regarding what to do or where to check, you can book a free 30 minutes consultation with our experts. They will offer guidance to set up your account in order to have accurate reporting. Dashboard If you are tired of getting complicated graphs and endless tables, our dashboard will be exactly what you need. This feature will present a clear picture of your online business performance through graphs and stats reporting the most important metrics for your website. Don't forget to set the metrics that best apply to your business from the settings page (see below more details). One of the advantages of the smart dashboard is the ability to compare the current day/week/month with a previous date range. This feature will allow you to contrast the metrics that matter to you in order to target adds or marketing campaigns in periods that generate profit for you. Custom reports Our consultants can create for you easy-to-understand custom reports that reflect the traffic or transactions from your website. The numbers are transformed into tables, pie-charts and graphs that can be interpreted by anyone in your team.   We created some general custom reports - conversion rate by channel or by device, changes in landing page value, product category revenue and purchases by blog post. You can choose one of those custom reports or have us create something entirely new for you. Either way, we review every new custom report by hand to ensure proper setup and accurate data. Free users get one basic custom report with setup by our team of experts. Pro users can take advantage of all custom report templates and even work with our consultants to create something new. Accuracy guaranteed – link to prices. Benchmarks Here, you’ll find the performance of your web analytics compared with aggregated data from other companies. You will be able to compare your web performance, conversion rate, bounce rates and more to a benchmark, which is created by analysing more than 3000 other websites. The data is gathered anonymously from Google Analytics to give you insight into how your digital product or online marketing is performing. For example, you can find out how you compare (whether above or below median) to other websites and adjust your campaigns in order to generate growth. Alerts    This report shows you trends in your data and includes in-app alerts. It will highlight significant changes, giving you details into what they mean and what to investigate. You can always customise the notifications that we will send via email from the settings section. Get the most out of your reporting - adjust your settings We’ve got a few important sections in your settings that we’d like to highlight, to make sure your reporting runs smoothly! First, adjust your revenue settings based on your website’s income generation. This will allow you to receive accurate alerts about how changes in your traffic affected your income. This will be done automatically if you have an enhanced ecommerce setup in your Google Analytics account. Second, you have your metrics and your segments, where you can select which reports you want to see based on the standard, predefined metrics or segments in Google Analytics. This will help you define your goals and see the relevant reports necessary to increase performance. Lastly, you notifications settings, where you can set up  email alert frequency or recipients. In this way to can always be informed and also be able to share with your team the important alerts regarding changes in your website. You always have the option of adjusting this at any time. But, we recommend you get this setup, as this will allow you to get the most relevant reports for your company. You can find this section by pressing the settings icon in the top-right corner of your screen, and then clicking report preferences. Every day we look for significant changes and trending pages There are over 100 Google Analytics reports and our clever algorithm scans through all of them, finding the most interesting changes to highlight. We recently improved that algorithm, and luckily for you, you can read all about how we made the detection of significant trends in your traffic easier to see. It’s been live since August, giving you fewer distractions and more significant alerts tailored to your company’s goals. Every morning (around 4am local time) our app fetches your traffic data from the previous period – broken down into relevant segments, like mobile traffic from organic search – and compares it against a pattern from the previous day, week, or month depending on the type of report. This isn’t just signalling whether a metric has changed – web traffic is unpredictable and changes every day (scientists call this ‘noise’). We are looking for how likely a specific value was out of line with the recent pattern. We are selective about the reports you see in the interface so we’ve set up the algorithm to find changes in trends in which we are 95% sure of the importance of the change. But to adjust which changes you actually get alerted to, you can change the significance to be much more limiting, like 98% or 99%, so that you get email alerts only in those cases We also use smiley faces to help you see quickly which changes are good or bad. If you’re particularly interested in “bad” things happening in your traffic to address potential issues, then you should look out for red sad faces to help you pinpoint these reports on the list. We email the most significant changes to you Every day – but only if you have significant changes – we generate a summary email, with the highest priority reports you should look at. An example change might be that 'the bounce rate from natural search traffic is down by 8% yesterday’ or 'the worst performing mobile device resulted in 59 fewer engaged visits'. If you usually get a consistent bounce rate for natural / organic search traffic, and one day that changes, then you should investigate why. Need to change your email settings? You can always adjust the frequency or add more colleagues so they can stay on top of the changes. If the reports you get are not the ones you need, based on your goals, remember you can always adjust your settings! Every Sunday or first of the month, we look for changes Every week (Sunday) or month (first of the month) we look for long-term trends – which are only visible when comparing the last week with the previous week. You should get more alerts on a Sunday. If you have a site with under 10,000 visits a month, you are likely to see more changes week-by-week then day-by-day. Already signed up? Login and check the setup of your reports. Need help with the process or have any questions? We’re always available to help, whether you need help with existing reports, need help finding the best reports for your company, are interested in the reports we’re currently working on and/or want us to provide feedback. Feel free to contact one of our experts or ask them in the web app. We hope you enjoy the web app and all of the wonderful reports and insights included! Happy analysing! This blog post was last updated in June 2017.  Further reading: New in Littledata: an improved navigation, trend detection algorithm, and more Making the detection of significant trends in your traffic easier to see 9 tips for marketers using Google Analytics

Littledata provides daily insights in your inbox. These include alerts on significant changes to your web traffic, tips on better tracking, and longer term trends in a daily summary email. All this, along with advice on how to act, will improve your ecommerce performance. Key performance indicators (KPIs) are the milestones to online success of an ecommerce store. Monitoring them will help ecommerce entrepreneurs identify problems and find solutions for better sales, marketing, and customer service goals. Once you have set goals and selected KPIs, monitoring those indicators should become an everyday exercise. And most importantly: performance should inform business decisions, and you should use KPIs to drive actions. Here are the most used reports in our Littledata software that monitor ecommerce performance: Sales Key Performance Indicators Hourly, daily, weekly, monthly Our web app generates reports, based on your traffic volume, on a daily, weekly, monthly or hourly schedule. This helps you keep up to pace with your campaign changes, your developer's releases, and your new interface changes. This way, you can react fast to changes. If your campaign is performing badly, you can see it at once and change it. If your developers release something and it breaks a page or the tracking code, you will see it fast and can correct it. Conversions The efficacy of conversion marketing is measured by the conversion rate, i.e. the number of customers who have completed a transaction divided by the total number of website visitors. The conversion rate is influenced by multiple factors. We track the conversion performance with reports like: Performance of the mobile devices Find out if you have errors on particular devices and check how the user can progress through the checkout flow on these devices. You may have some blocking steps on these particular phones or tablets like coding incompatibilities or a bad user interface. Campaign performance Find out how your new campaign is doing compared with the benchmark. We compare your campaign performance across all campaigns of its kind from your own website and others so you will know where to improve the moment the information is vital. Goal and purchases evolution across time Find out what days are the best for your sale and what days are the worst and schedule your budgets and actions accordingly. Read more about setting up goals in: 'Setting up a destination goal funnel' or find out about using Enhanced Ecommerce to optimise product listings. Marketing Key Performance Indicators: Site traffic In ecommerce, part of the conversion rate equation is the site traffic, which makes monitoring the amount of people that get on a website a big thing. We monitor the performance of the website traffic in multiple reports divided by other segments. The segments monitored can be turned on and off in the Control Panel section of each account under segments. The segments currently available are Direct, Paid Search, Organic Search, Referral, Email, Mobile and Tablet. Segmentation of your traffic puts light on what channels fluctuate at some point in time so you can correct it. Page views per visit Average page views per visit are an excellent indicator of how compelling and easily navigated your content is. The formula is the total number of page views divided by the total number of visits during the same timeframe. Sophisticated users may also want to calculate average page views per visit for different visitor segments. We track the page views per visit across your website and compare them with your benchmark so you can see if the customer journey can be more easy and compelling. Traffic source We track each channel that brings you traffic and spot when traffic sources drop or spike. We have a smart reporting system that calculates traffic sources from different segments so you can see each traffic source fluctuations, giving you the opportunity to react promptly. Have any questions about these reports? Just contact us and ask!   Further reading: Auditing web analytics ecommerce tracking Attributing goals and conversions to marketing channels Why do you need cross domain tracking

We’ve been searching high and low for some of those feel-good stories to bring you a little joy and we found the perfect data stories to put you in a good mood! Mike Schmoker said it well: “Things get done only if the data we gather can inform and inspire those in a position to make a difference.” Here are the stories that inspired us, making a difference in our lives. And if you like data as much as we do, trust us, you’re going to love these! The Dear Data project  We recently came across this fun project, Dear Data by Giorgia Lupi and Stefanie Posavec, about sharing their personal data, as pen pals. Dear Data, is a year-long endeavour of two designers living in different parts of the world, creating a friendship that will last a lifetime. They collected and hand-drew their personal data, sending it to each other in the form of postcards. With social media being the forefront of conversations these days, this beautiful story helps bring back the nostalgia of communication. If this doesn’t give you chills, we don’t know what will! What they did Every week, for a year, they collected and measured some sort of data about their lives through drawings. Each recipient would be given a code to decipher the picture. They used postcards to express themselves, and you can see a beautiful example below: Spirit of Alan Turing Now here’s a story that’s a little different, bringing the wonders of art and data together. There’s a new installation in Paddington commemorating Alan Turing, a computer pioneer and codebreaker that was born in 1912. The piece of public art shows an array of flashing lights that showcase changing words by Nick Drake, a Hackney-based poet. His poem brings a look into Alan Turing’s past in the present, presenting his spirit through data. It’s a thought-provoking installation using algorithms that bring with it intensity. The intent is to find some sort of pattern or code, and as people stroll by, someone will notice the meaning behind the project. And as the Londonist says, “That really is good art” and we agree! This is not the first attempt at celebrating Alan Turing, and we definitely hope it’s not the last! The design of data for the world  We’ve found the man that’s dedicated his life to data and in a creative way! Brendan Dawes creates projects focused on data for himself and the world around him, whether they’re art installation, interactive forms of communication, or a way to bring out a smile. As he perfectly sums up, “whilst I often work with data, I believe data by itself is not enough; data needs poetry.” One of his 2014 exhibitions that struck interest is the Dot Dot Dot exhibition. The show made use of data in some form or another. A few data-inspired installations included ‘The Happiness Machine’ and ‘Moments in Music’. When a button or dot on display was pressed on The Happiness Machine, a mention of the word ‘happy’ by a random stranger on the internet was printed for all to see. What a feel-worthy moment to showcase happiness through data. The Moments in Music exhibit developed unique art pieces, from data derived from sound waves. Through a software, songs were analysed and then specific moments were printed, showing real-world moments from digital music. Our final thoughts These wonderful stories prove that data doesn’t have to be overwhelming and mundane and you can really add your creative twist to any project. Individuals observing data needs to decipher it in a creative way, whether it’s to bring results or prove an experiment as there are a multitude of aspects. At Littledata, we come up with creative solutions to improve your performance through Google Analytics. We make data creative so you can enjoy the benefits! Have you read any other inspirational stories recently? Leave a comment below or contact us! Further reading: New in Littledata: an improved navigation, trend detection algorithm, and more Take your ecommerce website to the next level Analytics in store - online and offline Image credit: Image courtesy of Engadget, Dear Data, Brendan Dawes, and Londonist. 

Our core belief at Littledata is that machines are better at spotting significant changes in your website’s performance than a human analyst. We’ve now made it easier for you to get specific alerts, reducing the time spent wading through data. This is the story of how we produced the new trend detection algorithm. Enjoy! Back in 2014, we developed the first version of an algorithm to detect if today or this week’s traffic was significantly different from previous periods. This allows managers to focus in on the aspects of the traffic or particular marketing campaigns which are really worthy of their attention. Although the first version was very sensitive, it also picked up too many changes for a single person to investigate. In technical language, it was not specific in enough. In June and July, Littledata collaborated with a working group of mathematicians from around Europe to find a better algorithm. The European Study Group with Industry (ESGI) originated in the University of Limerick’s mathematics department in Ireland and has helped hundreds of businesses link up with prominent mathematicians in the field to solve real-world problems. Littledata joined the latest study group in University College, Dublin in July, and was selected by a dozen mathematicians as the focus for their investigation. Andrew Parnell from the statistics department at University College, Dublin helped judge the output from the four teams that we split the group into. The approach was to use an algorithm to test the algorithms; in other words, we pitted a group of statistical strategies against each other, from clustering techniques to linear regression, through to Twitter’s own trend detection package, and compared their total performance across a range of training data sets. Initially, the Twitter package looked to be doing well, but in fact, it had been developed specifically to analyse huge volumes of tweets and perform badly when given low volumes of web traffic. In between our host’s generous hospitality, with Guinness, Irish folk music, and quite a lot of scribbling of formulas on beer mats, myself and our engineer (Gabriel) worked with the statisticians to tweak the algorithms. Eventually, a winner emerged, being sensitive enough to pick up small changes in low traffic websites, but also specific enough to ignore the random noise of daily traffic. The new trend detection algorithm has been live since the start of August and we hope you enjoy the benefits. Our web app allows for fewer distractions and more significant alerts tailored to your company’s goals, which takes you back to our core belief that machines are able to spot major changes in website performances better than a human analyst. If you’re interested in finding out how our web app can help you streamline your Google Analytics’ data, please get in touch! Further reading: 7 quick wins to speed up your site analysis techniques Online reporting turning information into knowledge Will a computer put you out of a job?

We’ve got some exciting news! We’ve launched some great updates on our web app, which will make your lives a little easier. Find out how the navigation has improved and new in-app messaging will help you find out more, get a glimpse into our trend detection algorithm and new reports on mobile devices! Our mission is to make the way you gain access to important analytics, an all-around easier process and we know we’re heading in the right direction with these updates. We already give you actionable and easier to understand insights of your Google Analytics and now we’ve made the experience more friendly based on your invaluable feedback! Find your reports quicker We’ve improved the navigation of the web app, giving you one new category, and two updated categories on the left-hand side of your profile, which are now simpler to find and easier to understand. There are currently three categories: Dashboard, Benchmark, and Reports, which will be visible to you depending on your Littledata package. Instead of having them in separate locations, we brought them together into one navigation panel so that you can find specific reports and findings quickly based on your current questions or company needs. Under the reports category, we have changed types of reports into tags. Now you can select one or multiple tags, and decide how you prefer to view the different types of insights you get. For example, if you want to view your trends reports with tips you’re getting, then all you need to do is select those two. The benchmark category brings together all the benchmark metrics available for your site, and to see more detail click on the individual benchmark you’re interested in. You can still see the category you are being benchmarked against just above your benchmarks. If your current category is ‘all websites’ then you should make this more specific by updating the category in the settings. The Dashboard is the latest addition to these categories, which we added to be able to provide a flexible and customised solution that is perfect for reporting needs that go beyond standard Google Analytics reports. See below for more detail. Get our custom dashboard This is a new feature, available to clients who are also receiving consulting services on top of our Pro package. Please contact one of our lovely experts if you’d like to know more about these features, and how they can give you the results you strive for. The dashboard category is completely customisable, which we develop through consulting services by going over what your goals and needs are, and then creating these reports for simple and actionable insights of your data. These reports are completely flexible and allow you to see metrics that are difficult to view in Google Analytics, which include: Calculations, such as performance changes in percentages and conversion rates Combined metrics and dimensions from different reports Custom visualisations of trends based on how you prefer to see the data. Want to include a pie or bar chart? Not a problem. A custom schedule for dashboard data refresh. If your reporting requires weekly, quarterly or annual updates, we’ll set it up for you. Customised reports based on your formatting preferences, so if you'd like to include your brand colours, it's a possibility! Our smarter algorithm When we started Littledata, we developed a trend detection algorithm to find significant changes in your data and send you alerts, reducing the time spent wading through data in Google Analytics. But as times change and data gets busier, we needed a better way to serve your reporting needs. So recently we collaborated with mathematicians to improve the algorithm, which is now sensitive enough to pick up small changes in low traffic website, but also specific enough to ignore the random noise of daily traffic. Want to hear more about this intriguing story? Find out more in our blog post: Making the detection of significant trends in your traffic easier to see! Are mobile devices losing you customers? Analytics from mobile devices is extremely important. Through our web app, you will find out how many transaction or users you lost due to poor experience on mobile devices. According to Dave Chaffey at Smart Insights, 80% of internet users own a smartphone. A growing number of people are searching through their phones and as a result, we’ve incorporated mobile devices reports. They will spot and highlight potential issues around responsiveness, layout or bugs. Finding out which devices are the worst will allow you to optimise your website and campaigns to capture all of these individuals. Your personalised communication We completely agree with Intercom’s belief that “customers today want to communicate with the people behind the business, not with a faceless brand”! This is why we’ve integrated their messenger into our web app so that you can chat with us directly and quickly. There’s a great deal of custom features available, including formatting, delivery, and most importantly the different ways to respond. You can choose your own way to chat and react, with images, audio, emojis, video, and more. If you want to know more about the expert you’re talking to, you can view their profile within the app. Our customer experience is key in our business model and we hope this function delivers that. If you have any questions regarding any of the new features, please contact us, or use the in-app messenger!   Image credit: Image courtesy of Smart Insights and Intercom

Standard reports are useful to an extent. Custom reports and dashboards, on the other hand, allow you to compile metrics that give you much more useful insights of how your online shop is performing. Monitoring and reviewing the right data is essential for deciding which tactics or initiatives you should try, or marketing platforms to focus on, to help you sell more. If you are very familiar with how Google Analytics (GA) works, then you would set up some custom reports and dashboards to quickly access your key metrics. But if you are not as knowledgeable about the quirks and inner workings of GA then you should take advantage of the many custom reports and dashboards available for import. We can also help you build custom dashboards. There is a huge number of reports available in Google Analytics Solutions Gallery; used, created and shared by experts. They’re all done from scratch and designed to maximise your use of Google Analytics, but the huge amount of solutions from dashboards and channel groupings to segments and custom reports do require some time to find what’s right for your needs. From our experience setting up ecommerce tracking and reports for companies like MADE.com, British Red Cross Training, Pensions and Lifetime Savings Association, these reports and dashboards are valuable when analysing purchase data. Don't lose sight of your conversion rate Keep an eye on your ecommerce conversion rate across five different tabs covering channels, keyword, mobile devices, cities and campaigns. Focussed on high traffic sources, each section shows where it's not up to scratch and needs your attention and tweaking. Get ecommerce conversion rate performance custom report. Find duplicate transactions Duplicate transactions can greatly skew your numbers and affect your reporting, making you doubt the accuracy of your data. Duplicate order data is sent to Google Analytics typically because the page containing such information has been loaded twice. This can happen when the page is refreshed or loaded again. To find whether your data contains duplicate transactions, add our custom report to the view you want to check. Get a custom report to check for duplicate transactions. If you have more than 1 transaction in any row (or per an individual transaction ID), that means you have duplicate transactions stored in your data. It’s worth checking the report on a regular basis, eg monthly, to make sure that there are no duplicates or they’re kept to the minimum. Lunametrics blog has a number of suggestions for how to fix duplicate transactions. Overview of ecommerce performance This overview dashboard brings important top level metrics into one place, so you don’t have to go searching for them in multiple reports. You will quickly see which of your campaigns, channels, and sources are bringing in the most revenue, whilst comparing conversion rates across each. Get ecommerce overview dashboard. How is your store content performing See how your customers are engaging with your site, content and product (or page, depending on the setup) categories. You'll get information on what they search for, and which categories and landing pages bring in the most revenue. Get ecommerce content performance dashboard.   Looking for improving your ecommerce tracking and reporting? Get in touch with our qualified experts.   Further reading: Take your ecommerce website to the next level Attributing goals and conversions to marketing channels Tips to optimise your ecommerce landing pages Image credit: Image courtesy of Juralmin at Pixabay

Many of the popular email providers make it easy to automatically tag up links in your emails to allow Google Analytics to track them under the 'Email' channel. Without this, the traffic from email links will be dispersed under 'Direct' and 'Referral' channels, and you won't be able to see which emails really drive engagement or sales. Here are the links to set up some common email services: MailChimp Campaign Monitor ActiveCampaign Benchmark Email ConstantContact iContact Emma MadMimi GetResponse Mail Jet If your email provider is not in the list, or you send emails from your own platform, you'll need to manually paste in tagged up email links. Still need some help? Contact us and we'll be happy to answer any questions!

Only by using Google Analytics ecommerce tracking, can you match real sales data with website usage (including traffic source/medium). This sales analysis is required to understand the performance of your website landing pages and return-on-investment from marketing campaigns. The ecommerce reports allow you to analyse purchase activity on your site or app. You can see which products were bought, average order value, ecommerce conversion rate, time to purchase, discount vouchers used and checkout process funnels. Ecommerce tracking is useful not just for online shops but for all kinds of websites including event booking, courses / education, travel / hotels and so on. To see ecommerce data in Google Analytics, you need to: Enable ecommerce in Google Analytics Add the code to your site/app to collect ecommerce data. To complete this task, you'll need to be comfortable editing HTML and coding in JavaScript, or have help from an experienced web developer. Read how to Set up Ecommerce Tracking with Google Tag Manager. Based on this data, you can develop an understanding of: Which products sell well, and by inference, which products are best suited for your customer base. The revenue per transaction, and the number of products per transaction. For example, if the number of products per transaction is lower than you'd like, you might benefit from offering better quantity discounts, or offering free shipping if customers meet a minimum dollar amount. How long (in time and in the number of sessions) it takes customers to make the decision to purchase. If your sales cycle is stable or fluctuates predictably based on product or season, you can use this information (in conjunction with overall sales forecasts) to make reliable predictions about revenue. If customers routinely make numerous visits before they purchase, you might think about a site design that leads more easily to your purchase pages, or options that let users compare your products and prices to your competitors'. The difference between goals and ecommerce. A goal is only measured once in a visit. Think about it similar to pageviews vs. unique pageviews - once the goal has been 'triggered' to a visit, it can't be triggered again. On the other hand, there are no limitations on the number of transactions being measured during one session. Ecommerce is more powerful in that it allows you to analyse additional metrics.  For example, you can see how many visits occurred before the visitor decided to purchase. Many visitors on my site come back more than 7 times before they finally decide to purchase. Wow, interesting figures! Here is a list of the available metrics for ecommerce: If you have marketing campaigns and have no ecommerce tracking you are more likely struggling to calculate the return on your investment (ROI).  With both goals and ecommerce tracking, you will now have a full understanding of your customer journey and your customer life value (CLV). Analytics goals vs. ecommerce transactions, which to choose? Both of them!  If you have read my post carefully, you will understand that both of them have their strengths and limitations. We strongly advise to implement and configure goals and ecommerce. Need help configuring goals and/or ecommerce on Google Analytics? Get in touch with our experts!  

The script which triggers the tracking events to Google must be loaded once (and only once) on every page of your site. To set up Google Analytics tracking, you’ll usually need either your Analytics tracking ID or the entire Javascript tracking code snippet. This corresponds to your Analytics property. To find the tracking ID and code snippet: Sign in to your Analytics account. Select the Admin tab. Select an account from the drop-down menu in the ACCOUNT column. Select a property from the drop-down menu in the PROPERTY column. Under PROPERTY, click Tracking Info > Tracking Code. The snippet provided here must be implemented on every page, even the pages you are not interested in. If you chose to not include the code on every page then: you will not be able to see the full flow of a client on your website you will have inaccurate data about the time spent on site and actions taken visits to untracked pages will appear as 'referrals' and so will skew the volume of sessions marketing campaigns to the untracked pages will be lost The easy way for an established website to see if the tracking is complete is to go in Google Analytics -> Acquisition -> Referrals and search in the report after the name of your website, as shown below, or you can use Littledata's audit tool. Choose how to set up tracking There are several ways to collect data in Analytics, depending on whether you want to track a website, an app, or other Internet-connected devices. Select the best installation method for what you wish to track. Here is the complete guide from Google. Once you have successfully installed Analytics tracking, it may take up to 24 hours for data such as traffic referral information, user characteristics, and browsing information to appear in your reports. However, you can check your web tracking code setup immediately. If you don’t think it's working correctly Check your Real-Time reports or use Use Google Tag Assistant to verify your setup.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

On most websites, the conversion journey involves many different routes and across many sessions: few customers buy from the first advert. You may have heard of the ‘rule of 7’. In reality, it varies from maybe 2 or 3 touches for a $20 purchase and definitely more than 10 for an enterprise business service. Your company is buying prospects (or traffic) from a number of online channels, and in many cases, it will be the same potential customer coming from different sources. To be able to report on this in Google Analytics, we need to get the basic setup correct. Tagging campaigns for attribution The first step is to make sure that the different traffic sources can be compared in a multi-channel report are consistent and have complete inbound link tagging. Be sure to tag your campaign correct with our URL Builder. Some tools (such as Bing or Mailchimp) have options to turn on link tagging for GA - although it's buried in the settings. With many others, you will have to add the necessary ‘UTM’ parameters onto the link. Without this tagging, many sources will be misattributed. For example, affiliate networks could send referrals from any of thousands of websites which will appear under the ‘referrals’ channel by default. Facebook ads, since the majority come from the Facebook’s app, will appear under the ‘direct’ (or ‘unknown’) channel. From when full tagging is in effect, the channels report will start to reflect your genuine traffic acquisition source. But don’t expect a 100% match with other tracking tools – see our article on Facebook – GA discrepancies. Importing cost data The cost for any Google AdWords campaigns can be imported automatically, by linking the accounts, but for any third party campaigns, you will need to upload a spreadsheet with your costs on. The benefit is that now you can see the return on investment calculation update in real-time in the multi-channel reports. Model attribution The final step is to decide how you will attribute the value of a campaign if it forms part of a longer conversion pathway. The default for Google Analytics (and most others) is ‘last non-direct click’. That means that the most recent TAGGED campaign gets all the credit for the sale. If the user clicks on 5 Facebook ads, and then eventually buys after an abandoned basket email reminder, that email reminder will get all the sales (not Facebook). This attribution is what you’ll see in all the standard campaign and acquisition reports. You may feel that it is unfair on all the work done by the earlier campaigns, so ‘linear’ (sale equally credited to all tagged campaigns) or ‘time decay’ (more recent campaigns get more credit) may be a better fit with your businesses’ goals. Conclusion Multi-channel marketing performance attribution is not a luxury for the largest companies. It’s available to you now, with the free version of Google Analytics. It will require some setup effort to get meaningful reports (as with any measurement tool) but it has the power to transform how you allocate budget across a range of online marketing platforms. But if this still is not working for you then you may have a problem with cross domain tracking. Need a bit more advice or have any questions? Get in touch with our experts or leave a comment below!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Google has a strict policy prohibiting sending Personally Identifiable Information (PII) to Google Analytics. This is necessary to provide GA reports around the world, yet comply with country regulations about storing personal information.  Even if you send personal information accidentally, Google may be forced to delete all of your analytics data for the time range affected. This policy has recently tightened to state: You may not upload any data that allows Google to personally identify an individual (such as names and email addresses), even in hashed form. A number of our clients are using a hashed email as the unique identifier for logged in users, or those coming from email campaigns.  If so, this needs be a minimum of SHA256 hashing (not MD5 hashing), with a 'salt' to improve the security - check your implementation meets the required standard. If you want to check if personal information affects your analytics, we now include checking for PII in our complete Google Analytics audit. Google's best practice for avoiding this issue is to remove the PII at the source - on the page, before it is sent to Google Analytics.  But it may be hard to hunt down all the situations where you accidentally send personal data; for example, a form which sends the user's email in the postback URL, or a marketing campaign which add the postcode as a campaign tag. We have developed a tag manager variable that does this removal for you, to avoid having to change any forms or marketing campaigns which are currency breaking the rules. Steps to setup 1. Copy the script below into a new custom Javascript variable in GTM [code language="javascript"]function() { // Modify the object below to add additional regular expressions var piiRegex = { //matches emails, postcodes and phone numbers where they start or end with a space //or a comma, ampersand, backslash or equals "email": /[\s&amp;\/,=]([a-zA-Z0-9_.+-]+\@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+)($|[\s&amp;\/,])/, "postcode": /[\s&amp;\/,=]([A-Z]{1,2}[0-9][0-9A-Z]?(\s|%20)[0-9][A-Z]{2})($|[\s&amp;\/,])/, "phone number": /[\s&amp;\/,=](0[0-9]{3,5}(\s|%20)?[0-9]{5,8}|[0-9]{3}-[0-9]{4}-[0-9]{4})($|[\s&amp;\/,])/ }; // Ensure that {{Page URL}} is updated to match the Variable in your // GTM container to retrieve the full URL var dl = {{Page URL}} var dlRemoved = dl; for (key in piiRegex) { dlRemoved = dlRemoved.replace(piiRegex[key], 'REMOVED'); } return dlRemoved; }[/code]   2.Check {{Page URL}} is set up in your GTM container This is a built-in variable, but you'll need to check it under the variables tab.   3. Change the pageview tag to override the standard document location, and use the variable with PII removed   By default, Google Analytics takes the location to be whatever is in the URL bar (document.location in Javascript).  You will over-ride that with the PII-safe variable.  

What is cross-domain tracking and why do you need to implement in your Google Analytics account? Cross-domain tracking makes it possible for Analytics to see sessions on two related sites (such as an ecommerce site and a separate shopping cart site) as a single session. This is sometimes called site linking. Cross-domain literally means that you are able to see a user in a single Google Analytics account in his journey across multiple domains that you control (e.g. mysite.com and myshoppingcart.com). In the standard configuration of the Google Analytics script, every time a customer loads a page on a different domain a new session is generated, even if the branding looks seamless to the user and, unfortunately, the previous session has ended and this is even if the customer is still active and generates events and page views. Until you have implemented the cross-domain setting on your website you will not be able to have an accurate customer journey. Why? Let’s take, for example, a standard website, www.siteA.com, and it's blog, www.blogB.com. To track sessions, Analytics collects a client ID value in every hit. Client ID values are stored in 1st party cookies, and these cookies are only available to web pages on the same domain. When tracking sessions across multiple domains, the client ID value has to be transferred from one domain to the other. To do this, the Analytics tracking code has linking features that allow the source domain to place the client ID in the link URL, where the destination domain can access it. Fortunately, with the release of Universal Analytics cross-domain tracking, it is easier to implement, and especially so with Google Tag Manager. Setting up cross-domain tracking using Google Tag Manager Add (or edit your existing) a basic page tracking tag (i.e. Tag Type = Universal Analytics; Track Type = Page View). If you are using the same container for siteA.com and blogB.com, under More Settings → Fields to Set, enter the following: Field Name: allowLinker Value: true Under More settings → Cross-Domain Tracking → Auto Link Domains enter "blogB.com" (without the quotes). If you have multiple domains, separate them by commas: blogB.com, siteC.com Leave the 'Use hash as delimiter' and 'Decorate forms' unless you have an unusual web setup. Set the trigger to "All Pages". Save a version of the container and publish it. If you are using a separate container for blogB.com, repeat the steps above but in the Auto Link Domains field add: siteA.com Add both domains to the Referral Exclusion List When a user journey crosses from your first domain to your second domain, it will still appear as a new session in Google Analytics by default. If you want to be able to track a single session across multiple domains, you need to add your domains to the referral exclusion list. Here’s an example Tag Assistant Recordings report that shows what it looks like when cross-domain tracking is not setup properly. Setting up cross-domain tracking by directly modifying the tracking code To set up cross-domain tracking for multiple top-level domains, you need to modify the Google Analytics tracking code on each domain. You should have basic knowledge of HTML and JavaScript or work with a developer to set up cross-domain tracking. The examples in this article use the Universal Analytics tracking code snippet (analytics.js). Editing the tracking code for the primary domain ga('create', 'UA-XXXXXXX-Y', 'auto', {'allowLinker': true}); ga('require', 'linker'); ga('linker:autoLink', ['siteB.com'] ); Remember to replace the example tracking ID (UA-XXXXXX-Y) with your own tracking ID, and replace the example autoLink domain (siteB.com) with your own secondary domain name. Editing the tracking code on the secondary domain ga('create', 'UA-XXXXXXX-Y', 'auto', {'allowLinker': true}); ga('require', 'linker'); ga('linker:autoLink', ['siteA.com'] ); Remember to replace the example tracking ID (UA-XXXXXX-Y) with your own tracking ID, and replace the example autoLink domain (siteA.com) with your own primary domain name. Adding the domain to page URLs using filters By default, Google Analytics only includes the page path and page title in page reports - not the domains name. For example, you might see one page appear in the Site Content report like this: /contactUs.html Because the domain names aren’t listed, it might be hard to tell whether this is www.siteA.com/contactUs.html or www.blogB.com/contactUs.html. To get the domain names to appear in your reports you need to do two things: Create a copy of your reporting view that includes data from all your domains in it Add an advanced filter to that new view. The filter will tell Google Analytics to display domain names in your reports. Follow this example to set up a view filter that displays domain names in your reports when you have cross-domain tracking set up. For some fields, you need to select an item from the dropdown menu. For others, you need to input the characters here: Filter Type: Custom filter > Advanced Field A: Hostname Extract A: (.*) Field B: Request URI Extract: (.*) Output To: Request URI Constructor: $A1$B1 Click Save to create the filter. You can validate that filters are working as you expect using Google Tag Assistant Recordings. Tag Assistant Recordings can show you exactly how your filters change your traffic.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

In this article, you will learn why it is important to track the events that happen on your website, what the process of doing so is and how to read the information from your Google Analytics account. Every action that a customer makes on a website is generically called an “event”. An event can be the press of a button, the completion of a form or playing a video. Google Analytics defines events as “user interactions with content that can be tracked independently from a web page or a screen load. Downloads, mobile ad clicks, gadgets, Flash elements, AJAX embedded elements, and video plays are all examples of actions you might want to track as Events.” When recording an event on one of your website pages you must detail the following components to Google Analytics: Category, Action, Label (optional, but recommended), Value (optional). An event hit includes a value for each component, and these values are displayed in your reports. For example, you might set up a video "play" button on your site so that it sends an event hit with the following values: Category: "Videos" Action: "Play" Label: "Baby's First Birthday" Value: “2” Category A category is a name that you supply as a way to group objects that you want to track. Typically, you will use the same category name multiple times over relating to UI elements that you want to group under a given category. Actions Typically, you will use the action parameter to name the type of event or interaction you want to track for a particular web object. For example, with a single "videos" category, you can track a number of specific events with this parameter, such as: Time when the video completes load "Play" button clicks "Stop" button clicks "Pause" button clicks Label With labels, you can provide additional information for events that you want to track, such as the movie title in the video examples above, or the name of a file when tracking downloads. Value Value differs from the other components in that it is an integer rather than a string, so use it to assign a numerical value to a tracked page object. For example, you could use it to provide the time in seconds for a player to load, or you might trigger a dollar value when a specific playback marker is reached on a video player. If you start tracking the event on your page you can then create reports as this one: Action  Label:"Gone With the Wind" Label:"Mr Smith Goes to Washington" Totals Play 10 visits w/Event 5 visits w/Event 15 unique events "Play" Pause 2 visits w/Event 8 visits w/Event 10 unique events "Pause" Stop 2 visits w/Event 3 visits w/Event 5 unique events "Stop" Totals 14 unique events for GWTW 16 unique events for Mr Smith 30 unique events for category "videos"   Here is a list of the most common events we track for our clients: Scroll depth - this is very useful when you have a single page website or a lot of content on every page. It is important for you to know if the client notices the full page, and if not, to be sure to move the call-to-actions in the first part of the page or improve the user experience. Playing videos - when you have video content events, as shown above, you can see if the audience is engaging with your content. You can then see if the video has a good position or if it has a good and intuitive title and so on. Nowadays, Video content is king, you just need to find a way to get people see your videos. Hover on Product Order Button - if you are conducting serious research on what people want to buy from your website and what actions they do in correlations with a product you can see the numbers of mouseover on an add to cart button beside the usual add-to-cart action and remove-from-cart. How your client refines their search - you can find what are the most wanted colours of this season, if your clients are discount hunters or if most of your clients wear a shoe size 36 and you don't have any in stock. Find what client research on your website and provide a better experience for them. Affiliate link clicks - if you are in the affiliate business you already know that affiliation platforms don’t give you all the information you need. We have helped our clients to see exactly what call-to-action was the most pressed, what review was the most convincing and where your traffic go. Choosing the right call-to-action in affiliation is almost of the same importance as getting traffic. Nowadays, almost, every website has a carousel. If you are tracking the number of resources a carousel uses, then tracking the performance of your carousel is a big thing. You can track events with the banners your clients saw, what banners were pressed and see what banners have the lowest performance so you can make a decision to change them. Events are sent to Analytics, even the ecommerce interactions as product impressions, adds-to-cart, checkout steps, promotions click and more. All the events in the ecommerce section have these goals: find insights about the customer behaviour to make better acquisitions of stock, better discounts campaigns, a more user-friendly interface and provide a more relevant product listing for the client. When you start tracking the events people generate on your pages, the information you will gather will be, most likely, very far from what you imagined. The most important reason why you should start track the events that happen on your website is that all people are different, come on your page from different sources, with different technical skills or experiences with websites. If you want your products or ideas to perform be sure your audience get through all the nodes of your website. Start learning how to implement events on your website right now and start building your digital strategy today! Need some help doing so? Get in touch with our experts! Image: Courtesy of blogoscoped.com

Are your ecommerce landing pages suffering from poor conversion rate because people aren't engaging? First impressions are everything, and more so online, so your task is to figure out which on-site improvements will help you towards your goals. Once you start optimising, it's a continuous process of reviewing, changing, testing and refining - aiming to find out what is most appealing to your customers, what they like and care about, what makes them trust you, what encourages them to purchase. There is always room for refinements so here are some tips on what you should consider when reviewing your pages. What are you trying to achieve? Before starting testing and implementing the changes on your landing pages, you have to be clear about what you want to accomplish. Whilst the end goal for an online store is to increase sales, at times you might also want to get more sign ups, or improve views of or engagement with product pages. Think about what success will look like as that will help with planning your optimisation tests. How are you going to measure it? If you are clear about what you are trying to achieve, it will be easier to set measurable targets. Are you looking to increase your sales by 10% or pageviews of products by 15%? Or maybe you want your potential customers to browse further and spend more time reading content? Further engagement can also be demonstrated by the site visitor scrolling down the page if you have long product or category pages. In which case you'll want to track how far down the page they get to. I believe in keeping reporting straightforward so when testing focus on tracking important metrics only. Ideally just one if you can, or a few if you have to, but that will help focus on measuring what is most important for your business at the time. Assuming you are using Google Analytics, like most of people looking after digital performance, set up goals to monitor how customers are converting. Our web-based software also makes it easy to keep track of on-site changes are by reporting on changes in trends, goals, pages. Who are you targeting? User-focussed content is more effective at engaging your customers and improving your conversion rates. So you should write up your customer personas to be clear about who you are targeting with landing pages. This also applies to general look and feel of your ecommerce site. Most importantly, include with personas what problems your customers are trying to solve or what they are trying to achieve.  Once your team knows who your ideal or typical customers are, then it will be easier to focus on creating more relevant and engaging content on those pages. Do you have a clear value proposition? Value proposition explains why you’re better than or different from your competitors, and what you can deliver that they can’t. When writing it up, focus on benefits not features. It’s not always about the product looking top notch (unless you’re the industry or company where that matters of course) so it is more about how you can alleviate their problem. Check out how to write your value proposition by following Geoffrey Moore’s model. Does your copy reflect your value proposition? Once you have your customer personas and value proposition, review existing content on the site against how you describe what your clients are looking for. Check if it fits with what they are looking for, explains how you can solve their problems or fulfill their desires. The copy on your site has to reflect how you can improve your potential customers lives through what you offer. A great copy informs, compels, captivates, reflects what people search for and promotes key benefits. Econsultancy have compiled a great set of advice from experts on writing copy for product pages. Also, check out Copyblogger Demian Farnworth’s articles for superb advice on writing copy. Have you found your winning call to action? This is very important – test your call to action until you find the best performing one. Your call to action is like a visual sign that guides the buyer towards a specific action you want them to complete. Different things work for different sites. Start off with trying simple changes like different text, colour, shape, size or placement of the button to figure out what is most effective for your page. If small changes aren’t helping, then try a more drastic change of the button or page. Do your pages load fast? This is pretty self-explanatory. Slow page loading speed might drive your potential customers away from your online shop, so you should regularly check whether they can view your products within 3 seconds (Source: Radware). If you’re using Google Analytics, you can use Site Speed reports to check how you’re performing and get advice on where to improve. If you don’t have Google Analytics, you can use their online tool PageSpeed Insights. Other tool worth checking out is GTMetrix where you can grade your site's speed performance and get a list of recommendations. Do you need to optimise for mobile? It’s a very common fact that more and more people are using mobile devices to browse and buy online. But unless you have unlimited budget for ensuring that your ecommerce site is optimised for mobile, it is best to check in Google Analytics first whether you need to do it now. If you go to Google Analytics > Audience > Mobile > Overview report, you will get a breakdown of device categories that buyers are using to visit your online store. Here you can see that the majority of customers, almost 93% are using desktop so in this case (assuming you have a limited budget) you might want to make sure you have a responsive site at the very minimum, and leave a full optimisation for mobile device for later when there is a sufficient need. Now, if results were different and let’s say you had 60% of people visiting your site via mobile devices, then you would want to ensure that they’re getting the best experience on their device and don’t leave the site to buy from a competitor instead. Are your test results statistically significant? Evaluating your AB test results isn't quite as simple as looking at the highest conversion rate for each test, which would be an incorrect way to interpret the outcome. You want to be confident that results are conclusive and changes you tested will indeed improve your conversion rates (or not, depending on the outcome of testing). That's where statistical significance comes in. It gives you assurance about the results of your tests whilst taking into consideration your sample size and how confident you want to be about the importance of the results. By reaching over 95% statistical confidence in testing results, you can be sure that the winning variation performed better due to actually being an improved version, and not simply due to change. You can easily find a calculator online that tells you if your AB testing results were statistically significant and you should conclude the test or not - for example, try the calculator by Kissmetrics or Peakconversion. There is no one winning formula for how to make your pages more effective, but you have to be pro-active to figure out what they are  - so keep testing until you do. Have any questions? Leave a comment below or get in touch with our experts!   Image Credit: Stocksnap.io

Let’s say I am a retailer selling LEGO®. I have an offline store and I would really like to track my performance. This article will show you that online and offline have a lot in common. The KPI’s are almost the same. You just need to find the right tools to track each channel. I’m an online geek so I would like to track all my activity in my Google Analytics account. At this point, you might already think that it can't be done. But just this morning when I saw this quote it became clear: It always seems impossible until it’s done. So let’s dive in on how an offline store KPI’s can by tracked via Google Analytics. I chose LEGO for two reasons. One, I love LEGO, and second, I love the uniformity of a LEGO store. All LEGO stores have the same structure, philosophy, almost the same products (differs by approx 10% in each country) and the same management control. That made my example so easy to picture. A LEGO store has in it the following and it can be translated in an online store the following way: Offline Online Collections of products Category Main products Products Complementary products Complementary / Accessories products Every product comes in a box The main photo of the product Every shelf has only one collection The listing page The LEGO catalog The online catalog (newsletter) Facebook page / Find shop page Facebook page / Find shop page Tablets with video of the products Video on product page Giant statues Banners Marketing events Campaigns Marketing assets ( rollup, banners, mash) CPM campaigns Traffic sensors Google Analytics tracking code Cash register Checkout page VIP cards UserID tracking A tablet for surveys Exit survey or email survey A tablet for VIP registrations Register section Video cameras Hotjar :)   The first step to monitoring something is to choose which tool we are going to use. In my demo, we will use Google Analytics. We are going to create a Universal Google Analytics account with Enhanced Ecommerce tracking set up. In a normal website, we will implement this tracking code on each page of our website. In a retail store, we will have like a single page website because LEGO usually has only one room for the stores. Now comes the fun part. When a loyalty card means a UserID I mentioned above that we have a 'website' for the LEGO store with the new Universal Google Analytics script. We also have a VIP club because all LEGO stores have a program called LEGO VIP Club. This club is a program designed to engage customers and increase sales. With each sale, a customer is encouraged to become a part of the VIP Club. They will get a card, like a credit card design, and a unique ID. With this ID, we will be able to unify the customer's activity on online and in offline stores. Sessions: or “traffic” in retail For traffic control lots of retail stores have implemented sensors to track the amount of people coming in and walking out. Such a solution is usually called “counting visitors” or “footsteps counting”. A retail store can implement a "counting visitors system" in 2 parts of the stores for collecting the maximum amount of data: outside the store, and just inside the entrance / exit. This way you can measure the amount of people who saw your store and the amount of people who actually came in / left the store. You could then further divide the amount of people leaving the store in shoppers and visitors. Which in online translates to conversion rate. Here we will then add the amount of people that saw LEGO ads via marketing efforts. To make things interesting, we can put a contactless device by the entrance, to track the number of VIP customers that enter the store. Here you can extract data from your counting visitors system and send this information via the Measurement Protocol to Google Analytics. I will not get technical on this, due to the fact that it is just an idea and not a case study. But for more information feel free to contact us. At the entrance gate, you can send GA the information that a customer entered the LEGO store from Happy Street, give him a generic userID from the counter and if he taps the VIP card send the VIP Club ID also. Category and products Every brick and mortar store has an inventory of products. And every product in LEGO Store has a single category. If you've never seen a LEGO Store, let me show you what order means in products and category. [embed]https://youtu.be/lAaE-pxNB1w[/embed] The products and categories can be imported to Google Analytics using data import function in the admin section. In a LEGO store, you can track the On Shelf activity by using both traffic sensors and track events on digital assets. The sensors can track and send GA, the traffic on a specific section of the store. And since we are talking about LEGO this will be easy because the products are not mixed up. LEGO has implemented Digital Boxes in US stores. Digital Boxes are an emulator that takes the image of an object you have in your hand and projects a new image on top of it. This Digital Box can be seen in the video above, and could be treated like a view of a specific product page. Another cool asset LEGO has is the video player on the shelf. This video player shows the content of a product on a tablet (usually 7” wide). This tablet is put next to a selected product and the customer has the opportunity to virtually see the content of the LEGO box. We can now send to GA this interaction of a user with the video. Here we can use Google Tag Manager to catch the user interaction with this digital asset. For the products that have no video on the shelf or a digital box projection, we can use a smartphone along with an improved version of the LEGO app called LEGO 3D Catalog. This app can be downloaded from the Android store or Apple Store, and in the same manner, as the digital box, it will project an animation of the product on the image of the product box. To enter the app you must be logged in, so we can use the User ID, and we can make use of the GPS position to be certain that he is in our store. Online meets offline All online marketing activities are easy to send to Google Analytics if we use a system to track them. You can build your social campaign in a way that will be shown in Google Analytics in a very detailed way. Littledata provides a template to build powerful URL’s that can be used in your social campaigns. The role of this URL is to tag your traffic with the campaign information. Download Littledata's campaign tracking sheet with a URL builder. Online marketing activities mean Facebook, AdWords, mall website, PR communication, partners and mail exchange. You can connect the tablet, which you have in your store for surveys, to Google Analytics and get interesting reports based on that data and act quickly with the alerts from Google Intelligent Alerts. Impressions or proximity to marketing assets The easy part in offline marketing is to track the impressions. Two words: proximity sensors. By using these sensors you can track the amount of people that came close to your marketing asset and send it to GA (or, as we say, make it fire to GA). A marketing asset can be a banner, a statue, a mash or a roll up. And now let’s take the game to the next level. Track the promotions interactions. Let’s say you have a LEGO photo booth. Within the photo booth, you could place a QR code that will automatically share your customers' photo on social media and, in the same time, send a hit to GA or add a hashtag. Purchases The complex structure of a purchase in Google Analytics is this: 'id': 'P12345',                   // Product SKU 'name': 'Android Warhol T-Shirt', // Product name 'category': 'Apparel',            // Product category 'brand': 'Google',                // Product brand - in our case is super easy “LEGO” 'variant': 'black',     // Product variant - on LEGO we have products like mugs red, green, yellow 'price': '29.20',                 // Product price (currency). 'coupon': 'APPARELSALE',          // Product coupon - We can put here the coupon from our campaigns. And for the general campaigns like LEGO has a full month 30% off at City collection. Put the LEGO City sales that meet the conditions (like 1+1, or 2+1, or 2 +50%) a LEGO City identifier. 'quantity': 1                     // Product quantity (number). All of these can be sent to GA on the purchase. Also, we can add custom dimensions like payment method and we must not forget about the VIP Club ID. Incomes and outcomes all in one place Data import lets you upload data from external sources and combine it with data you collect in Google Analytics. You could then use GA to organise and analyse all of your data in ways that reflect your business better. Data imports join the offline data you've uploaded with the default hit data being collected by Google Analytics from your websites, mobile apps or other devices. Imported data can be used to enhance your reports, segments and re-marketing audiences in ways that reflect your own business needs and organisation. The result is a much fuller, more complete picture of your users' online and offline activity. You can import you banners costs, traffic data from mall reports or refunds that maybe you are not tracking in your accounting software connected to Google Analytics. Data imports let you manually do a few of the things I detailed in this article. Big DATA in useful reports At this point, you have a bunch of data. All you need is some simplification. As already Littledata showed you, the final reports are the ones that really matter. Now, you just need to take a seat, grab a pencil and draw the KPI’s that matter to your business. I have some retail KPI’s that can be relevant to your business as they are for a LEGO store: customer retention, cost of goods sold, customer satisfaction incremental sales, average purchase value sales per square foot, cross devices and offline/online, conversion rate in store, track sales target, track bundle performance, employee sales performance, VIP enrollment target. "Sky is the limit" when it comes to understanding your customers. Even if you are a big store or a little one, your company will be able to make adjustments to various strategies and budgets, improve your activity and bring customers better services. Want more information on this blog post? Contact one of our lovely experts for details!   Further reading: What is CRO, conversion optimisation, for ecommerce? Image Credit: Image courtesy of http://eveash.com

Google Analytics is a powerful tool when you know how to use it. In this article, we will show you how to use some of the hidden features of Google Analytics and how to empower the use of data in your business. It's often said that the only constant in life is change. Humans are build up to resist change and this resistance to change is now more important than ever. Napoleon once said, "You must change tactics every 10 years if you wish to maintain superiority." In today's society, the pace of change is immensely faster, and it will only continue to accelerate. We know our children are growing up in a technological age, but the ability they show in mastering the new and smart devices is truly amazing. The new age is coming, and online stores must be prepared to meet these kids’ expectations. If you have a website then answer these questions before continuing: Are you attributing new and returning customers to marketing campaigns? How do you make that data accessible, accurate and comprehensive? Do you understand how your customers are using multiple devices through numerous touch points? Are you prepared to measure this type of behaviour as shown in the video below? [embed]https://www.youtube.com/embed/qn7RfQU1MJg[/embed] Stats on ecommerce websites The Internet Retailer Top 500 Guide, published in 2016, mentions that the online sales for 39 publicly trading retail chains ranked at 10.4% while comparable-store sales growth was only 1.4%. Online customers are predicted to spend $414 billion by 2018. That’s more than 57% revenue growth since 2013, according to InternetRetailer.com. Shoppers are flocking to retailer websites with good content: annual product video views increased by 42% in 2015, according to a survey of retailer clients by Invodo Inc., an online video marketing firm. And shoppers who watch a video are 1.7 times more likely to buy something than those who don’t - but videos must be relevant, and those depicting how to assemble or use a product get the best results. If the video has a higher rating, then the consumers are more likely to purchase that product, Invodo found. A five-star rating correlates to a 3.76% conversion rate, while a one-star rating yields a 1% conversion rate only. And do your KPIs consider how the customer feels; does your website do better than this video? [embed]https://youtu.be/3Sk7cOqB9Dk?list=RDN5WurXNec7E[/embed] How can you collect data about your customers? Many powerful analytics tools, such as Google Analytics, are free and can help you analyse where your traffic comes from, what your site visitors search for to find you, and what your potential customers do once they get to your site. You can track visitor interactions with your site at a very detailed level, such as traffic sources associated with revenue and keywords associated with revenue amounts. Tracking your website activity will make sure that the efforts in the above categories, such as changes you’ve made to your website’s appearance and order process, product presentation, incentives and social media, are paying off. If these efforts are paying off, by how much, and which is the best performer? As you probably know, there are hundreds (if not thousands) of ways to drive traffic to your online store. The problem is that many of them are expensive and many of them do not convert. Before you test any type of traffic and spend even a dime on driving traffic to your site, it is imperative that you set up conversion tracking. This way you know exactly which sources are converting for your store and know where to reinvest advertising budget to bring in more sales. How can you use that data? Let me start off with showing you how you can centralise all your digital performance in one place: Google Analytics. If you use a variety of systems and tools to run your business, you can use Google Analytics to join and analyse that data in one place. For example, you can turn separate CRM data, ecommerce data, and Google Analytics data into a single comprehensive view of your business. Each business system you use generates its own data store. Your CRM might contain information like customer loyalty ratings, lifetime value and product preferences. If you are a web publisher, your content management tool probably stores the author name and article category. If you have an ecommerce business, you might create catalogues that describe your products according to prices, style, size, etc. And, since you're reading this, you most likely use Google Analytics to track traffic and performance for your websites, mobile apps or appliances. Typically this data exists in its own 'information silo,' unaffected and uninformed by the data in other silos. But with the data import function, you can merge the data generated by your offline business systems with the online data collected by Google Analytics. This can help you organise, analyse and act upon this unified data view in ways that are better aligned with your specific and unique business needs. For example, as a web publisher, you could unite the web hits collected by Google Analytics with the data dimensions exported from your CMS and CRM systems to analyse the relative contributions of authors to your site. You can use the Google Analytics API and Google Apps Script to access your Google Analytics data from Google Sheets. This is a powerful tool because it allows you to utilise all the great features of Google Sheets with your analytics data, such as easy sharing, collaboration, charting and visualisation tools. Not everyone has the ability to read the Google Analytics reports but with the right implementation and the right declaration of your KPI’s you can generate easy to read, comprehensive and reliable reports on your business. What if you could have a single place to enter and see at a glance what you are interested in? All your business KPI’s brought to you on a plate and with fresh data every day? You can view the most viewed product this week to see if you can supply accordingly, or view your goal funnel and see where your customers abandon the site and much more. Segmenting your clients Use the data to improve. You have a bunch of customers on your website every month. They are all the same but still so different. Do not communicate with them in the same way: segment your customer list. Google Analytics includes predefined segments (system segments) that you can use as provided, or that you can copy and edit to create new custom segments. You can also build your own segments from scratch. In addition, you can import segments from the Analytics Solutions Gallery, a free marketplace where Google Analytics users share segments and other solutions they’ve developed. A segment is a subset of your analytics data. For example, of your entire set of users, one segment might be users from a particular country or city. Another segment might be users who purchase a particular line of products or who visit a specific part of your site. Segments let you isolate and analyse those subsets of data so you can examine and respond to the component trends in your business. For example, if you find that users from a particular geographic region are no longer purchasing a line of products in the same volume as they normally have, you can see whether a competing business is offering the same types of products at lower prices. If that turned out to be the case, you could respond by offering a loyalty discount to those users that undercut your competitor's prices. You can also use segments as the basis for audiences. For example, you might create a segment of users who visit your menswear pages, and then target just those users (your audience) with a remarketing campaign that is focused on the new items that you are adding to those pages. Are your CTAs clickable and your PDFs downloadable? Event tracking is one of the best ways to understand the user actions on your website such as how many times a button was clicked, a form was submitted, or documents were downloaded. You can measure interactions on your site by either implementing the Google Tag Manager Data Layer Event code or leveraging Google Tag Manager's Auto-Event Tracking functionality. With Auto-Event Tracking in Google Tag Manager, capturing these actions is easy. You can create event tags directly within the Google Tag Manager interface and fire them with triggers based on predefined variables or on custom variables that you can build within the Google Tag Manager. Now it’s easy and you have no excuse to see if your business plans are on the right track. If you know what actions your clients do on your website, you have the ability to take actions in the right direction. Stop guessing and start counting numbers and actions. We've written a blog post previously on how to set up event tracking in Google Tag Manager. Track your social buttons I expect you already have social share buttons on your website, but do you track them? Like with the call to action buttons, the social media buttons can be tracked and you can find out the impact of your social presence. There’s a lot of value in both implementing these social buttons in a good and fast way and measuring all these interactions. Seeing which sort of social buttons work for which types of traffic can really help you find what you should be optimising how. Track your campaigns If you are running marketing campaigns on social media you can increase the value and quantity of the insight even on you social media platforms. The standard Facebook pixel is caching the conversion, but by adding some lines of code on the Facebook pixel with the Google Tag Manager you can track the value of a purchase, what searches were made on the website, how many times did the campaign result in items being added to cart and wishlist, how many clients started checkout, content views, adding payment info or completing a registration. Your social campaign will have more relevance and will be more documented when you will merge the force of your data with the data from your social media platforms. To take the problem from the other end, you can build your social campaign in a way that will be shown in Google Analytics in very detailed way. Littledata provides a template to build powerful URL’s that can be used in your social campaigns. The role of this URL is to tag your traffic with the campaign information. The URL builder makes it easy to tag your campaigns and track them in Google Analytics. Simply enter your campaign details, and it will generate a tagged uplink for you in 'Final campaign URL' field. All upper-case characters are converted to lowercase to avoid using a combination of both, which results in same campaigns showing up in different categories in Google Analytics. Download the Littledata campaign tracking sheet with a URL builder. We have detailed this before in this article on the Littledata blog: Why should you tag your campaigns? There’s always room for growth. You can track a client that enters the store, adds to cart, sees the delivery cost and exits; you can retarget a client that bought a product from you with additional products and can set personalisation of the store based on the customer’s behaviour. So when you think you’re done developing that, rethink and start again! Interested in getting help with any of these features? Get in touch with our experts and we'd be happy to help!     Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Are you running campaigns in AdWords, Facebook or on another advertising platform? Do you know whether your marketing efforts are paying off and which channels you should keep investing in to increase your product sales? As marketers face more and more pressure to demonstrate that their activities are contributing towards the profit, there is a bigger need for you to be able to show your decisions yield positive results. But if a particular channel or campaign is doing the opposite and causing your business losses, then the sooner you figure that out, the quicker you'll be able to adjust your further marketing plans. That’s where calculating and tracking your ROI becomes important. By being able to figure out how much you make from investing into a particular campaign or channel, you can figure out where to focus your budget. Whilst it’s difficult to compare the performance of specific marketing tactics across every single industry and company, there are interesting conclusions that have come out from market research. As reported by Web Strategies Inc., the top 3 channels that generated the best ROI were email marketing, SEO / organic search and content marketing. Email marketing has also been reported elsewhere to give the best ROI (source: Campaign Monitor), but you should focus on figuring out the correct ROI for your marketing activities and, based on that, decide which ones work for you best. To figure out how to calculate your ROI, see the video below where Edward explains the steps. *This video is part of ISDI online training courses for digital professionals. Video transcription so in this chapter we're going to talk about return on investment or return on marketing investment now this is a really powerful metric to let you understand whether a particular campaign is actually earning your company money or losing money, it's something that's really become only possible in a world of digital marketing when you can genuinely attribute particular revenue or particular customers to a particular online campaign so the calculation is pretty simple, what we have to do first is find out what is all the revenue that came from that campaign source, or is attributable to that campaign so let's take the example of AdWords that we're going to look at later in the chapter in AdWords you're going to pay for a search term in Google and when the customer clicks on the advert it appears in Google Analytics as being the source of that customer for that visitor so if that visitor goes on to buy something at that session or the next you can say that yes their revenue was attributed to AdWords, so that's your revenue - the revenue that's specific to that campaign then the next thing you're going to measure is what did that cost you, again with AdWords it’s very simple because Google Analytics pulls the cost data from AdWords so it’s really simple to see in the table of numbers what was your campaign cost but if you're not using AdWords and you have another campaign, that's okay, because you can actually import that cost data into Google Analytics, so let's say for example you paid to send out your message to a third party email list, typically you would rent that email list for a certain amount per recipient, and that campaign cost you can import in so let's put some real numbers into this - let's imagine that we get a thousand euros of revenue and our campaign cost us five hundred euros - so 1,000 over 500 is 2. that is a positive return on investment - anything better than one hundred percent is good, roughly for every euro we spent on the campaign we've got two euros back in revenue, so we’d run that campaign again now let’s imagine that actually our conversion rate wasn’t so good - we still spent 500 euros on the campaign but actually we only got 400 back in revenue now we can see that our return on investment has dropped to 0.8 so this time for every euro we spent on campaign cost, we actually lost money - we're burning money running this campaign and that's not even taking into account the margin contribution, so it's unlikely, whatever the product we sell for 400, that that is all profit it's highly likely that we only get maybe a hundred of that back as profit, in which case this marketing campaign is very expensive and it's not doing us any good so return on investment is a powerful way of measuring whether your campaign is positive ROI or negative ROI, and what you need to do is be able to attribute the revenue to the campaign and also to measure your costs, and use those two numbers together   Further reading: What is CRO, conversion optimisation, for ecommerce? Image Credit: Image courtesy of Maialisa at Pixabay

If you run or work in an ecommerce business, you will always be looking for ways to increase your sales. So CRO or conversion rate optimisation is one of the key metrics you should care about - review and improve it. Are potential buyers leaving your online store before purchasing products? Have you looked at the potential reasons why they may be leaving and ways to improve the number of visitors who end up buying? Increasing that number of people who complete the main action, or convert, is called conversion rate optimisation. Some of the reasons why more people are not buying your products could be: product pages are loading too slowly not enough information provided about the product your ecommerce site has poor navigation information about delivery and returns costs is too confusing/difficult to find need more time to think before committing to a purchase In the video below, Edward gives an overview of CRO and talks through some examples of tests you could be running to find out how to improve your conversion rate. *This video is part of ISDI online training courses for digital professionals. Video transcription so one of the important things, if you're going to increase your return on investment of marketing campaign, is to think about how users engage with your page and this is typically called conversion rate optimisation or increasing the percentage of people who land on the page or visit the page to those that do the main action let's look at this example which is a very generic e-commerce product page as you can see the very obvious call to action, which is highlighted, is to click the Buy button to add it to cart if we get a marketing campaign to push people to page let's say the product here is some pink shoes and our campaign says buy pink shoes we are wasting money that's never going to have a positive return on investment if people out on the page and don't even like the content they don't engage with it so we need to measure very carefully what is the bounce rate  of our landing page, and the bounce rate is the percent of people who land on the page and then go away with them without doing any further action and conversion rate optimisation is really the process through which you might go to get more people to convert - in this case to click Buy so we might look at the text on the page the heading could we change the copy to make it more engaging or to make it more fitting with the users expectations so if we advertise for pink shoes this better say pink shoes somewhere in the copy the next thing we'll optimise is the image - is it appealing, is it easy to see what the product is, maybe we might add a 3d visualisation animation of the product for them to get a better feel for it and then we might experiment with a Buy button itself - how about making it bigger or make it red this might seem really trivial but you'd be amazed the difference in conversion between let's say a blue button and a red button, so altogether we can run a series of tests in the next chapter, we're going to look at a series of tests you might run to test those things but the process of doing it is conversion rate optimisation and that's really going to help you boost that return investment from any given marketing campaign Have any questions? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Ecommerce reporting in Google Analytics is typically used to measure checkout performance or product revenue.  However, by analysing events at the top of the funnel, we can see which products need better images, descriptions or pricing to improve conversion. Space on product listing pages is a valuable commodity, and products which get users to click on them – but don’t then result in conversion – need to be removed or amended.  Equally, products that never get clicked within the list may need tweaking. Littledata ran this analysis for a UK retailer with Google Analytics Enhanced Ecommerce installed.  The result was a scatter plot of product list click-through-rate (CTR) – in this case, based on the ratio of product detail views to product listing views – versus product add-to-cart rate.  For this retailer, it was only possible to buy a product from the detail page. We identified three problem categories of product, away from the main cluster: Quick sellers: these had an excellent add-to-cart rate, but did not get enough list clicks.  Many of them were upsell items, and should be promoted as ‘you may also like this’. Poor converters: these had high click-through rates, but did not get added to cart. Either the product imaging, description or features need adjusting. Non-starters: never get clicked on within the list. Either there are incorrectly categorised, or the thumbnail/title doesn’t appeal to the audience.  They need to be amended or removed. How we did it Step 1 - Build a custom report in GA We need three metrics for each product name (or SKU) - product list views, product detail views and product add to carts - and then add 'product' as a dimension. Step 2 - Export the data into Excel Google Analytics can't do the statistical functional we need, so Excel is our favoured tool.  Pick a decent time series (we chose the last three months) and export. Step 3 - Calculate List > Detail click through This website is not capturing Product List CTR as a separate metric in GA, so we need to calculate as Product Detail Views divided by Product List Views.  However, our function will ignore products where there were less than 300 list views, where the rate is too subject to chance. Step 4 - Calculate Detail > Add to Cart rate Here we need to calculate Product Adds to Cart divided by Product Detail Views.  Again, our function will ignore products where there were less than 200 detail views. Step 5 - Exclude outliers We will use an upper and lower bound of the median +/- three standard deviations to remove improbable outliers (most likely from tracking glitches). First we calculate the median ( =MEDIAN(range) ) and the standard deviation for the population ( =STDEV.P(range) ).  Then we can write a formula to filter out all those outside of the range. Step 6 - Plot the data Using the scatter plot type, we specify List > Detail rate as the X axis and Detail > Add to Cart as the Y axis. The next step would be to weight this performance by margin contribution: some poor converters may be worth keeping because the few sales they generate are high margin. If you are interested in setting up Enhanced Ecommerce to get this kind of data or need help with marketing analytics then please get in contact.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

Setting up Google Analytics to collect data on your website visitors’ behaviour is step one. But are you getting the insights you need? Web analytics tools like Google Analytics can provide a wealth of information about what people do on your site, but it becomes powerful when you do more than just look at trends going up or down. It’s about measuring and improving. Here are some tips on how to use your data for informed marketing decisions for your company. Make analysis a regular habit Checking analytics to evaluate website and marketing performance varies from business to business. Some do it multiple times a day or only when it’s time to do their monthly reporting or end up getting hooked on real-time analytics. Make it a regular habit to analyse your Google Analytics metrics and before you know it, you won’t need the constant reminders to do so and it'll feel less like a chore. You can start off with doing it a few times a week and if you find that there aren’t enough changes to come to any conclusions, then do it less frequently. Whilst for smaller businesses the results won’t change much hour to hour or even day to day, for the bigger businesses changes can be significant on a daily basis. Form your questions Before sifting through your Google Analytics reports, come up with a set of questions that you are looking to answer with your data. You might want to know: What are users searching for? (requires site search to be set up) Which pages are they spending the most time on? Which pages have the highest bounce rate and might need further tweaking? How are my marketing campaigns performing? Is my spending on Adwords justified? Which traffic sources bring the best converting traffic and are worth investing into? Are my call to actions working? (this is where goals come in handy) Know where to measure Think about which reports and metrics will be most suitable to answer your questions. Knowing what you're looking for will minimise the amount you spend wandering aimlessly through numerous reports hoping that you'll find something interesting. It’s said that there are over 100 standard reports available in Google Analytics, so it’s handy to know where to look. The reports are split into 4 main categories: Audience is about the users – where are they, what devices are they using, Acquisition is about how users get to your site – how are your campaigns performing, where do they come from Behaviour is about user interaction with your site – which landing pages get the highest traffic, which pages have the highest bounce rate Conversions is about users completing certain actions (requires further setup to get the most out the reports) – which goals did they complete, what is their shopping and checkout behaviour Pages with high page views and bounces / exit rate Check how your individual pages are performing in All Pages and Landing Pages reports (under Behaviour > Site Content). If your page is getting a lot of page views and has a high bounce / exit rate, then whilst it might be a valuable or attractive piece of content it’s not doing a great job at getting your users to another page. Can you provide some other relevant content on that page? Link to them where appropriate. This will help improve the visitor journey through the site and reduce the bounce rate. Know your user journeys You can use Google Analytics flow reports to view which paths users take through your site and where they drop off. Evaluate the pages with the biggest drop offs  - can you improve these pages to encourage users continue their journey? You've put a lot of work into the pages that are meant to convert your site visitors, but it's a waste of all that effort if your journey to the converting page doesn't work. Goal flow report is especially handy for seeing users' paths towards the goals you have set up. Not sure how to set up a goal funnel? Here's how. Segment your users Use Google Analytics segments to view and analyse a separate subset of user data. You could view your reports for users from a specific location, eg Spain, or with a specific device, eg Apple iPad, or by certain behaviour, eg made a purchase. Check out Google's guidance on using segments. Evaluate your tagged campaigns Custom campaign tracking is important for organising your campaigns so you can review the performance effectively. If you're not tagging your campaigns yet, check out our blog post on how to tag your campaigns. Share findings with the team It’s great if you get into the habit of reviewing Google Analytics data on a regular basis to inform your actions. What's even better is if you create a team culture where you share findings with each other. You can email around individual reports, share insight at team meetings, set up custom alerts or sign up to our web-based tool to do that for you. For those less geeky or knowledgeable about data, make sure you translate the findings into plain English statements (PS. our tool already does that too). Continuos improvement When Dave Brailsford became the head of British Cycling, he implemented the concept of marginal gains within cycling. He believed that by breaking up the process of competing and improving every step by 1%, they would see a big improvement in their team. And he was right. All the small changes accumulated into a massive performance boost, and Team GB surpassed everyone’s expectations by going on to some big wins at Olympics and Tour de France.  This can apply to many other areas as well - customer satisfaction, improving service quality, doing minor updates to marketing campaigns. Rather than focussing on one big improvement and spending weeks or months on it, before even knowing if it'll work, look at the potential small changes you could make. You will spot much more quickly which of these changes are of benefit and which are not. There's a lot of information stored in your Google Analytics, when used correctly and regularly you will start getting the insight you need to guide your marketing efforts. Suggestions above will help you do just that. Something else on your mind? Let us know in the comments below or get in touch!   Images: Courtesy of Suriya Kankliang, pannawat at FreeDigitalPhotos.net

We released the last updates just a few weeks back, but we've done it again. The new improvements will help you get more out of your reports and make your analysis more efficient, but if you've got any other requests or feedback, don't hesitate to let us know. So here's what we've done. Report improvements Discover where you need to improve Tips reports identify the gaps in your analytics setup and suggest fixes or improvements to boost your tracking. We are working on bringing you more of these tailored tips but we need to know what you're trying to achieve to get these right. By updating your report preferences in the subscription settings, you will start getting personalised suggestions and we will use this information for other future tailored reports. You can get to your subscription settings by clicking on the cog icon in the header. See more detail on your referrals It's important to stay on top of your website traffic changes with minimum time waste. This is why we developed Littledata software in the first place. Now we have added extra information to your referrals reports so you can immediately see which sources had the biggest increase or decrease. You will also see the option to pick the type of reports you want to get. Just click on the 'Yes please' button at the bottom of the report to see your choices for customisation. New monthly report So far you've been getting reports that look at the changes in your Google Analytics data on a daily and weekly basis. We've had a lot of requests for monthly comparison reports instead, so we've added these to your feed. Just like your daily and weekly reports, you can spot the new monthly ones by the time tag. Benchmark your website performance It has always been difficult to get a hold of benchmark data to find out how you’re performing against others. You often have to spend a lot of time crawling through the internet to find anything remotely useful. With our new website performance benchmarks we are changing that. Now you can compare your engagement metrics to other websites. You’ll be able to tell whether you need to focus on improving your bounce rate from a particular source, or page load for example.   Feel free to ask questions or send us your comments either below or via the Intercom Messenger available when you're logged in.   Further reading: Under the hood of Littledata

A lookup table in Google Tag Manager makes it much simpler to manage lots of values in your tracking setup. It can drastically reduce the number of tags required and turn your messy GTM into a neat environment. It's especially useful with larger setups where you have multiple tracking requirements and flexible to accommodate new tracking needs as they arise. You can easily add or remove values from your lookup tables, and not worry about having to change any codes. The lookup table variable allows you to define a set of key-value pairs where the output variable (the value that you are sending to Google Analytics) is linked to the identifier (the key). It works like this: When [input variable] equals to  _______, set [this output variable] to_______. For example, you could use the lookup table for: Assigning different Google Analytics property IDs for various domains/hostnames, eg. when [website hostname] equals to littledata.co.uk, set [property ID] to UA-010101 (see example below) Setting different pixel or conversions IDs for different country websites, eg when [website country code] equals to 2, set [pixel ID] to 88779 (requires having website country code variable defined) Defining your event categories, actions and labels (see example below) Remember! There’s no limit to how many values you can have in the lookup table, but the fields are case sensitive. So if you have multiple capitalisations of some input, then include all of them in the lookup table and assign the same output for each. I have previously explained setting up the tracking of user actions as events in GTM, but when you need to track multiple events, one tag just doesn't cut it anymore. And instead of creating several tags to cover each event or action, here's how you would create the lookup table to cover multiple values in one place. Creating lookup table variable for event parameters In the Littledata software interface, you get an option to switch between different report types or view them all. I want to track when people click on different report types, so instead of creating 5 different tags for each user action, I will set up a lookup table to cover all of them in one place. But firstly I need to know which variable to use as the input. You can only have one type of input variable per the lookup table so you want to pick a variable type that applies to each (ideally). For this, I will check how each report type option has been set up in the code by inspecting the element (inspect/inspect element depending on the browser you're using and usually accessible via right click). Here's how each report type has been set up: <a href="/report-list/m2i4MnmXcewDSzZ3c/all" class="current" id="ga-all">All <span class="count">120</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/trends" class="" id="ga-trends">Trends <span class="count">80</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/pages" class="" id="ga-pages">Pages <span class="count">37</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/tips" class="" id="ga-tips">Tips <span class="count">3</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/benchmark" class="" id="ga-benchmark">Benchmark <span class="count">0</span></a> Looking at the above, I can see that each report type has a unique ID - here that's the best one to use. Now to set this up, go to Variables, click ‘New’ and select 'Lookup Table' as your variable type. For the input variable, I will use {{Click ID}} as explained above, but you, of course, use whatever unique identifier you have available. For your output, you want to define the event action you are going to send to the Events report in Google Analytics. Should you set the default value? You can set a default value for the output when there is no match found in your table. With the event tracking, I sometimes find it useful to enable to identify if I set up my tag correctly. If my trigger ends up being too broad, the default value option will pick up additional values not defined in the table. I will then see these values in Google Analytics reports and this way I can tidy up the trigger to be more accurate. So this is what your variable should look like now. Click ‘Create Variable’ and there you have it. In your GA event tag, the newly created variable would look like this. Other uses Multiple Google Analytics properties If you have a single GTM container installed on multiple domains but you're tracking them across different Google Analytics properties, you want to ensure that you're sending the data to the correct one. Instead of having multiple variables to store different property IDs, you can have them all neatly in the same table defined by the hostname. This way any tracking activity on each site will go to its own dedicated property. Excluding test or other data If you want to make sure that any data outside of your main site goes to a test or other Google Analytics property, you can do so by setting the default value. The default value is the output that is not found in the table. With this setup, any activity tracked on www.mainsite.com goes to property ID UA-121212. If the activity wasn't on www.mainsite.com, then it sent to property ID UA-121212-2. Use lookup tables for something else? Confused? Get in touch or comment below!

Events in Google Analytics are important for understanding how people interact with your website. They give you additional insight into their behaviour and how effective your pages are for leading users towards a conversion. With event tracking you could see how many users clicked on a button or played a video, scrolled down a page or clicked on your contact and social media icons. I mostly use Google Tag Manager (GTM) for analytics setup so I will show how to set up event tracking for clicks on buttons with GTM. Instead of hard coding events in the code, GTM allows you to create, test and amend tags within its interface. Before you go ahead creating your event tags, make sure your built-in pages and clicks variables are enabled. This will avoid you having to go back and forth between different sections. The setup below covers only one action - a click on a specific button - but if you have multiple actions to track, then look into implementing a lookup table variable. Tracking button clicks Here's my scenario. I want to track our BENCHMARK YOUR SITE button that allows users to sign up to our free software plan and get benchmarked against competitors.   And here's how to set it up. 1. Create a tag It will be a Universal Analytics tag type where tracking ID is a constant string variable (you need to create this variable before using it) and track type 'Event'. Think of your event tracking parameters as a way to organise the events into a hierarchy: Category – the main aim of the button or its placement Action – what the user clicked or the action Label – provides additional information like on what page the button was clicked or the outbound link they clicked on Value – if you have a numerical value to set for your click (not in my case tho) In my example, the category is ‘Get started’ because we have a number of similar buttons across the site with the same purpose to get the user started with the signup, so all of them have the same event category. For action, I specify the type of button that was clicked on so I can compare how these different buttons perform - 'Benchmark your site' in this case. My event label is the {{Page Path}} where they clicked on the button. The buttons take the user to the same place so I’m more interested in which pages these buttons were clicked on. Alternatively, if you have buttons that take people to different URLs you might want to track that instead. Is it a non-interaction hit? This is an important one to keep in mind. By default this is set to False. If you don’t want this event to impact your bounce rate, then change it to True, which you would do if the click or action didn’t take the user to the new page, or if you didn't want it to be included in your bounce rate calculations. Now click 'Continue' to go to the trigger setup. 2. Create a trigger Trigger is like a rule that allows you to tell the tag, ie specify the conditions, when it should fire. Under 'Fire On' select ‘Click’ as your trigger type and then ‘New’. For configuring the trigger, you have a choice between two types: Just Links – use this when the target is a link or anchor tag <a> All Elements – use this when the target is any other element that’s not a link To determine what’s best for your purposes you need to have a look at how your button is set up. You can do this by selecting ‘inspect element’ or simply ‘inspect’ depending on what browser you’re using. It’s usually available when you right click on the button or element.   Our button has been set up the following way: <a href="https://littledata.uk/signup" class="btn btn-ltd btn-green">benchmark your site</a> It has a link so I will use 'Just Links' for targets and I have a choice between three elements to use in further configuration: https://littledata.uk/signup as click url btn btn-ltd btn-green as click class benchmark your site as click text It is best to use a unique condition if you can. This way, if similar class or click url gets reused in other parts of the website you don't have to go back to this trigger to update it. With 'Just Links' you will get additional configuration options: Wait for tags - delays opening of links until all other tags have fired or the wait time has lapsed, whichever happens first Check validation - fires the tag only when opening the link was a valid action, without the tag will fire whenever the user clicks on the button/link Enable when - this options is shown only when either of the above is ticked so you can be specific about where you want the trigger to be active If you want the trigger to listen to the interactions on all pages, then set that section to be  URL or Page Path matches regex .*. (without that very last full stop - that one's for the sentence) In my case, I only want it to work on benchmark pages and all of them start with /benchmark/. The very last step in trigger setup is specifying on which actions or clicks the tag should fire. As said above, I'm using the button's click class here. All done? This is what your tag should now look like. Click 'Create Tag'. 3. Test Test your tag in GTM's preview mode by checking two things: the tag fires in the preview interface, and the tag is seen in Google Analytics real time view under 'Events' with the event parameters you specified   I hope you got on with the setup above just fine, but if you have questions or clarifications, feel free to ask below.   Further reading: Know who converts on your site with Google Analytics goals Using lookup table variable in Google Tag Manager Intro to Google Tag Manager's key concepts and terminology Image: Courtesy of suphakit73 at FreeDigitalPhotos.net  

Until recently I hadn't understood how generous the Seed Enterprise Investment Scheme is for investors in early-stage companies. Investors can put up to £100k in qualifying companies, as long as they don't control more than 30% of the SEIS company. There are three overlapping benefits which mean you can recoup over 100% of your investment in tax offset if the companies goes bust, and get a 5x boost to the value of your initial investment if all goes well.  It sounds too good to be true, so use your allowance while it is still open! Let's assume that you are an additional rate (45%) tax payer, and want to invest £10,000 of capital gains into an SEIS company. What happens if that company eventually goes bust? A. Reinvestment relief Firstly you get a 50% reduction in the capital gains tax bill from gain reinvested.  If you realised a gain of at least £10k over and above the capital gains tax allowance from selling shares or property, then you can reclaim the tax on the amount you reinvest in the SEIS company.  At the 2014/2015 higher rate of 28% that is: + £2,800 B. Income tax relief Next you can write 50% of your £10k investment off against your income tax bill from this year or last - even if you didn't directly use that income to invest in the SEIS company. +£5,000 C. Loss relief If the company goes bust, then you can write a further 45% (your marginal tax rate) in the year you claim against your income tax bill. 45% times the £5,000 of investment the tax payer didn't originally fund. +£2,250   So of that £10k you have already recouped £2,800 + £5,000 + £2,250 = £10,050 from HMRC. Leaving you with a small gain to cover the inconvenience. But look on the bright side! What if the company sells for double the value in a few years' time? This time you still get benefits A & B, but also keep the proceeds free of capital gains tax. So you put in £10k, but take £7,800 back off your tax bill, leaving you with £2,200 net exposure.  When you sell the shares for £20k, you have multiplied your capital at risk 9 times An investment in an equivalent non-SEIS company would have yielded £20k, less capital gains tax of £2,800 = £17,200 (1.7x your investment) So you get more than five times the net gain from the SEIS investment.  

As a consumer brand, is there a better way of getting customers to refer you business than offering excellent customer support? My inbox this afternoon showed two polar opposites of handling support by email and illustrated what great support looks like. I can sum up the differences: Ditch the "you're in a queue" email Really listen to the customer Offer further advice Ditch the "you're in a queue" email My depressing email exchange with Swiss Airlines starts when I tried to complain about the £4.50 credit card charge. I would normally never pay it, but their debit card payment route was broken, so to book the flight I had no choice. Dear customer, thank you for your message. We will get back to you as soon as possible. The response time may vary depending on the amount of research required. Please do not reply to this E-Mail. Use for your feedback our page: www.swiss.com/contacts We thank you for your understanding. Yours sincerely, Swiss International Air Lines Ltd. Let's unpack the sheer hostility of this: "thank you for your message" = we care so little we couldn't be bothered to add a capital letter "as soon as possible" = nor do we have enough staff to answer today "Please do not reply to this E-Mail" = we can't even be bothered to install a smart ticketing system Really it would be better not to send me an auto-response at all - just get back to me when a human is ready. Let's compare that with an email I get from TransferWise, which was my good experience of the day. At first glance, this looks like an automated response, but then I realise it's signed by a real person - and they actually want me to reply to the email. TransferWise are having to deal with genuinely onerous FCA anti-money laundering rules - and offering a helpful way to get around it. Really listen to the customer The Swiss conversation goes downhill from there. OK, I'm a bit smart Alec about the transaction fee - but it's a well known scam. On 24 Feb 2016, at 05:51, contactus@swiss.com wrote: Dear Mr. Upton, Thank you for writing to us with regards to your query and we apologizes for the inconvenience caused. We would like to inform you that GBP4.50 is the fee charged directly from the bank/bank fee. Therefore, we cannot grant a refund with regards to the above mentioned fees. We trust the above information will be of assistance and are available to assist you with any further questions at any time. Thank you for choosing SWISS and we wish you a pleasant day further. Kind regards, Miriama Consultant Customer Travel Services / R1S ----- From: Edward Upton [mailto:edward@edwardupton.com] Dear Miriama, That is absolutely untrue. MasterCard charges you 0.3% for the transaction, which in this case is 51p https://www.mastercard.us/en-us/about-mastercard/what-we-do/interchange.html So please can you refund me GBP 4? regards, Edward Upton ----- From: contactus@swiss.com Dear Mr. Upton, Thank you for writing to us. We have reviewed your request regarding your reservation. Please note that in regards to your request we will not be able ot refund the OPC. Please note this (GBP4.50) is a charge placed by the credit card company and it applies as per the point of commencement of your ticket. We hope this information is useful. Please do let us know if you need additional information. Thank you for choosing SWISS. Kind Regards, Alexander Consultant Customer Travel Services / R1S This feels like someone has cut and pasted from a standard response list. It's robotic. And given that the original issue was actually about their website being broken, there is a total lack of empathy for the issue - just some 'apologizes' (sic). Offer further advice Often companies have to say no to refunds and extra requests, but at least be gracious. And sometimes the company can offer you something that benefits both parties: a guide to how to avoid needing to email in the future. Here is the exemplary reply from Transferwise Hi Edward, I hope you’re doing well! Thank you for getting back to us, and confirming that we can change the name on the payment ###### to your personal. I shall quickly pass this on to my colleagues, who are able to make the change and proceed with the transfer. As soon as the payment is sent out from our end, we shall send you a confirmation e-mail, like always. All you need to do is check your inbox every now and then.:) Just in case, I will explain how you can choose to use both your personal and business profiles on TransferWise. Once you log in to your TransferWise account, on the upper right corner you should see a logo (like a man in a circle). When you click on the logo, you should see: Use as Edward Upton Use as Littledata Consulting Ltd Therefore, if you want to set up a personal payment, and you’re planning to send money from your personal bank account, please make sure that “Use as Edward Upton” is ticked. And if you’re planning to make a business payment and send money from your business bank account, please make sure to choose the second option. If anything was left unclear or you would need help with something else, please don’t hesitate to get back to us. We are always happy if we can help! I hope you have a lovely day, Eliisa, TransferWise Support Which company do you think I'll recommend in the future? Comment below!

We’ve just released a bunch of improvements for Littledata software to improve your data analysis and reporting. Grab yourself a cuppa and read on to learn what’s new, including the ability to choose which reports you want to get, updated spam filter, and more. Settings improvements We want to give you more control over your subscription so we've added further customisation options to your settings. Update subscription name You can now update your subscription name to be something more descriptive than the default property name we select. If you have multiple views for the same website or a very long property name, you can change the name to something more snappy and understandable. Select which reports you want So far you've been getting a set of standard reports without being able to pick which reports are important for you. That's changing! You can now select the metrics and segments you care about and want to get reports on, and turn off the ones you don't. You can do this by going to your subscription settings, and updating the Metrics & Segments sections. Report improvements We believe that analytics reporting should be simple, clear and unpolluted with unnecessary details so we've made your reports easier to understand. Simpler report titles With a lot of changes to the website traffic, the interface can get quite busy with numerous reports trying to get your attention. We made the titles much simpler by focussing on the main change that the reports are about, thus allowing you to skim your reports and see what's happened more quickly. Time tag Our trends reports look currently for daily and weekly changes in your website traffic, and previously you had to rely on the report title to see which time comparison the specific report is for. To make it clearer, we have taken this information out of the titles and added time tags instead. Now you can quickly see which reports are daily or weekly comparisons. Don't let spam referrals skew your data I have previously written a guide on how to remove spam referrals and I know from experience it can be time consuming and frustrating to set up. You have to identify these spammers in your data first, then check other more common ones to add to the list, write a regular expression, then create one filter, then another and so on. Did I say it can be frustrating? Our spam correction feature takes the exasperation out of this process by adding filters to your analytics view once you authorise the fix. Whilst we've had this feature for some time now and it's as popular as ever, we have updated the list with many more spam referrals. We'll send you a tip report if we find fake referrals in your traffic, and you can clean up your data by clicking on 'Fix this now'.   Feel free to ask questions or send us your comments either below or via the Intercom Messenger available when you're logged in.   Further reading: Under the hood of Littledata New in Littledata: tailored tips, new report and more (

Google Analytics is a powerful tool… when implemented correctly. I can’t even count the number of times we've had enquiries from and spoken to companies who don’t trust the data in their reports because it's incorrect or incomplete. And it all comes down to wrong configuration and setup. Checking and amending correctly the very basics of your analytics setup will provide you with data you can rely on and an accurate foundation for further more advanced configurations, like Enhanced Ecommerce tracking. So here's a list of questions you should be asking whilst checking your Google Analytics (GA) property and view settings. This is assuming you're on Universal Analytics (analytics.js) so not all setup options may apply if your site is on Classic analytics (ga.js). I'll also cover a few common setup issues at the end. GA property settings Go to Admin > Property > Property Settings. Is your default URL set up correctly? The default URL is used in Content and in-Page Analytics reports to display page previews. Do you have a correct default view picked? By default, this will be the first view created at the time of initial GA setup. If you're using AdWords Express or Google Play, then you want to check the view here is the one you want to connect to either of the services. The default view will also show you all the custom and advanced segments you've created in other views. Have you set your industry category? Pick whatever matches your property most closely if you want to be included in the benchmark reports. Have you enabled demographics reports? Demographics and interests reports give you additional insight into your users. Recently I explained how to set this up in Google Analytics and Google Tag Manager V2. Do you need enhanced link attribution? Enable this if you have pages with multiple links that take people to the same destination or a page element that has multiple destinations, eg internal search. This will help with identifying which particular elements or links were clicked. In addition to enabling this in the property settings, you also need to add a line of code to your GA tracking code, or, if using GTM, toggle Enhanced Link Attribution to true in your pageview tag under Advanced Configuration settings. Should you link with your Search Console? Link your Search Console site with your Google Analytics property to see Search Console data in your GA reports, and access GA reports directly from the Links to your site and Sitelinks sections in Search Console. GA view settings Property settings sorted? Great, now go to View > View Settings. Is your view name descriptive? Use easy to understand naming to describe what the view is for, eg excluding admin, domains included, ecommerce data only. Have you set your default URL? Similarly to the property settings, make sure you use the correct default URL here to improve your Content and in-Page Analytics reports. Have you set a correct time zone? The beginning and end of each day for your reports is calculated based on the time zone you have set. If you need to update this, you may see a flat spike in your data caused by the time shift. Do you need a default page? Setting a default page is useful when you have two separate URLs loading the same homepage. Here you can configure those pages to be considered as the same URL. This will affect your reports so make sure you do this correctly Should you exclude URL query parameters? Specify any parameters you don’t want to see in your reports. I've found a blog post from Lunametrics useful for understanding when and how to exclude URL query parameters. Is your currency correct? Especially relevant for sites with ecommerce tracking for making sure that the reports show your order values and revenues in the currency you operate in, and not in $ that it converts to by default. Have you ticked bot filtering option? Whilst this option doesn't help with eliminating all of the spam referrals, ticking this box will exclude at least a few of them. To get rid of all of your fake referrals, here's a thorough guide on how to exclude them with two filters. Get yourself a cuppa if you're going to clean up your data. Does your website have a search function? Enabling the site search is useful for understanding what your website visitors are looking for. It should be pretty painless to set up if you have a query included in the URL, and we've covered the steps to set up internal site search tracking in one of our blogs. Other common setup issues Here are also a few very common setup problems that I keep coming across again and again. Have you got an unfiltered view? It's good practice to have an unfiltered view that you keep clean from any filters and customisation. This way you can always double-check your data if anything goes wrong in another view. Is your bounce rate less than 10% whilst your pageviews have doubled? This may be happening due to pageviews firing multiple times. You can use Tag Assistant plugin for Chrome to check if that's true. Are you getting referrals from your own domain and your payment gateway? This is skewing your data so checkpoints 3 and 4 on how to exclude referrals from your domain and payment provider. Tracking multiple subdomains in the same view? By default, you see only request URI in your reports without a domain, which isn't very helpful if you are tracking more than one domain in the same GA view. You can improve this by adding a hostname to URLs with a custom filter. Check Google's guidance for how to do it. Are you filtering out internal traffic? To minimise your data being skewed by internal colleagues or partner companies you may be working with, exclude their IPs with the help of filters. Are you on top of website traffic changes? OK, so this one isn't quite about the problem with the setup but if data has an important role in your business, you can make your analysis more efficient. Google provides you with the ability to set up alerts for important changes in your data, but our software does the work for you. Instead of trawling your data for hours or spending further time on configurations, you can set up alerts and personalised reports within minutes.   Have you experienced other setup problems that aren't covered above? Let me know and I'll include them. Image Credit: Images courtesy of vectorolie and ratch0013 at FreeDigitalPhotos.net

You know marketing is essential but have you specified what makes you different and unique, your objectives and how you are going to achieve them? Recently I went to a workshop, organised by Innovate UK and Enterprise Europe Network, to do just that: learn about achieving business goals by using strategic marketing. Strategic marketing is essentially a structured plan that helps you achieve competitive advantage or other business goals through a set of defined activities that are most appropriate for your aims. We were taken through a number of exercises that helped us define how we position ourselves and what we are trying to accomplish, whilst aligning the marketing efforts and tactics with overall business goals. It was especially useful to bounce my ideas off others so if you’re going through similar exercises, I recommend you do the same. It really helps to sense-check your thoughts and how you describe your business with someone outside your company. Below I'll go through my top takeaways and methods that I found most useful when devising a strategic marketing plan. Define the purpose/mission of your business Think about what you are trying to achieve as a business – is it clear or does it need further refining? Why are your services and products needed or wanted, and who are your customers? If you have a clear purpose or a definition of what you’re trying to achieve, it will help you plan your marketing activities and inform other business activities. Having an easy to understand idea of your purpose also helps guide your resources and avoid spreading them too thinly, which is especially valuable if you’re a small business where resources are limited. Define your value proposition A value proposition is what you promise to deliver to your customers through your services or products. Here you need to think what makes you unique, better or different from your competitors. If you struggle to offer a reason why your offering is more valuable than your competitors, then you may get stuck competing on price only. I found the Geoffrey Moore’s model particularly useful for defining the value proposition. It goes like this: The  ____________ (product name) Is a ____________ (product category) for ____________ (users/customer segment) who ____________  (statement of desire/problem) that ____________  (compelling reason to use) unlike ____________  (the next best alternative) allows ____________  (the main difference). And here’s an example we were given: The iPod is a portable music player for music lovers who want to listen to their music anywhere, anytime unlike portable cd players or 
MP3s with less storage the iPod allows easy access to all your music Define your marketing goals We used SMART method to define 3-5 marketing goals for the next 12 months. Being specific about the number of goals you’re trying to achieve within a year helps to focus on specific outcomes you’re trying to achieve. It also helps to measure your success after 12 months or another timeframe you set for yourself. Specific - clearly defined 
and specific goal rather than a generic and vague one, eg increase signups Measurable 
 - quantifiable goal, eg how much or how many Achievable – realistic to complete within a set timeframe, eg a few months Relevant to you and your customers 
- choose what matters or matches needs Time-bound - that you have the time, money & resources to achieve your goals within a specific timeframe Define your segmentation, targeting and positioning Segmentation is an activity where you divide the broad market into specific customer segments by their common characteristics, and devise your tactics around targeting each segment. A few ways you could segment your customers are demographics, geography, psychographics, lifestyle, behaviour, etc. Once you have a clear idea of different customer groups, you will be better placed to pick the most attractive or suitable segment to target. When selecting your target segment, see if there are segments that are the easiest, cheapest or quickest to reach, whilst being realistic about your capabilities and resources to target those segments. Positioning your business gives you a distinct image of your benefit(s) to the target audience that you are going to communicate. If you have a number of segments you can target, then define your positioning for each segment. Same applies to the Geoffrey Moore’s value proposition model – write it out for each customer segment. Define your marketing tactics Once you have a clear idea of the customer segment(s) you’re targeting, why they would use your services or products, and what you’re going to communicate to them, you can pick specific marketing tactics that are going to help you do that. Some examples of tactics are producing ebooks, using online ads like PPC, sharing data findings via blog, and organising webinars. If you need inspiration or ideas, there are plenty of resources online when you search for marketing tactics, marketing strategies, growth tactics and similar. Define your marketing KPIs Decide on a set of metrics that you are going to use to measure the success of your marketing efforts. By having the right KPIs, you can evaluate if you’re on track towards your goals, and adjust your activities if necessary. To give you a few examples of what you could measure: Cost per lead or enquiry Average order value Landing page conversion rate Customer lifetime value Impressions / clicks / visits I hope this has helped you to start thinking about defining your business and marketing activities more strategically and in line with the over-all goals. There are lots of great templates online that you can use to assist with outlining your plan - for example, check out Smart Insights resources bank that has lots of useful PDFs for marketing planning and more. If you'd like to discuss further, comment below!

Wouldn't you want to know how well people convert on your site? Setting up basic conversion goals will enable you to measure site engagement – based on time on site, destination page or particular events - and what drives that. Below I’ll cover the reasons why you should set up goal tracking in your Google Analytics, different types of goals available, goal value, and then explain how to set them up. So why should you track goals? Goals are great for tracking important actions that are crucial for your business and understanding how people convert on your site. Once you set up goals, you will be able to analyse conversion rates in the Goals reports. Conversion data will also appear in other Google Analytics reports, like the Attribution and Acquisition reports. This will help you identify which marketing campaigns and channels get users to complete the goals you have previously defined. The destination goal also allows you to set up a funnel to visualise the path people take through your site towards completing a purchase, signing up or another conversion. Seeing how people navigate through your site in a visual way makes it easier to identify where they drop off. If you see a lot of exits on particular pages, then review those pages to see if you can improve them to minimise the exits and guide more people towards converting. If you see a lot of people skipping certain pages, then your path to conversion might be too long or contain unnecessary steps. For more info on flow visualisation reports, check Google’s help pages. What kind of goals can you set up? You can set up a destination goal to track how many users reached a certain page, eg thank you, purchase confirmation or pre-order request pages. Then there’s a duration goal that tracks how many users stayed for a specific amount of time, eg for at least 15 minutes. You can also set up a pages/screens per session goal to see how many users view a specific number of pages during a session. An event goal is for when a user triggered certain events on the site that you have already set up, eg clicked on an ad, submitted a form or saved a product. What else should you know about goals? Goals have a few limitations in Google Analytics: You can set up only 20 goals per view. If you need more, you can either create another view or repurpose existing goals. Goals apply to the data after you’ve created them. Goals can’t be deleted; but you can turn them off if you don’t need them. Use names that make sense so that anyone using your Google Analytics data can understand what the goals are for. Keep track of when you changed the goal by adding annotations to your reports. Do you need the goal value? Setting up a goal value is optional. You should set a monetary value for your goal when you want to track how much you earned from converting users and you’re able to calculate the worth of each lead. If you know that 5% of people who sign up on your site end up buying your service, and the average value of your service is £1000, then you can set £50 as your goal value (5% of 1000). When setting up a goal value, make sure the currency corresponds to what you use on the site or are familiar with. You can do this in Admin > View > View Settings. Are you an ecommerce site? If you’re an online retailer, then instead of using goal values you should be using Ecommerce or Enhanced Ecommerce tracking for Google Analytics. These reports will be much more insightful for tracking your store performance. So how do you set up goals? You need to set these up at the view level. Go to Admin > View > Goals, and click New Goal. Google has added some goal templates that you can choose from if you’re happy to use their naming. Alternatively, select 'Custom' at the end of the list and click ‘Continue’ to the goal description. For your goal name use something that is easily understood by others using your Google Analytics account, and the goal details will depend on the type of goal you're setting up. Setting up destination goal You can follow the blog I've previously written on setting up the destination goal and funnel. Setting up duration goal Click ‘Continue’ and specify the minimum amount of time you want to track. Setting up pages/screens per session goal Here you specify the number of pages someone viewed per session. Setting up event goal Set the event you want to track as a goal by using exactly the same category, action, label and value as in the event. If you want to use a goal value here, you have the option to use the event value you’ve already set. Verify your goal - click ‘Verify’ to check if it works. If the goal has been set up correctly, you should see an estimation of the conversion rate your goal would get. If you’re not getting anything, check each step carefully and Google's help pages on why your conversion tracking might not be working. Once you’re happy with the setup, click ‘Create goal’ and check the results in your analytics reports after a few days or weeks, depending on the amount of traffic you get.   If you need help with the setup above or have another way of using goals, I’d love to hear about it in the comments below.

UK-based websites are 5 percentage points better than their US peers at keeping mobile users engaged (with a lower bounce rate), and 2.5 percentage points better at keeping the users from desktop / laptop computers engaged. For bounce rate from email marketing, the difference was also 5 percentage points (a 14% better performance from UK websites). The comparison is based on the Google Analytics data from 209 UK companies and 95 US companies collated by Littledata. The British web industry has benefited from earlier smartphone adoption in the UK (81% vs 75% in the US; source: MarketingLand), and overall greater internet usage from UK consumers (source: Econsultancy). That should put UK-based developers in a great position to sell their experience to other countries with increasing internet adoption An example is MADE.com, a London-based furniture retailer which has used superior online customer acquisition to drive growth across the UK and continental Europe. Littledata founder, Edward Upton, explains: “It’s usually hard to get a hold of industry data to compare digital product performance against similar companies, but Littledata’s benchmarks provide a simple way for companies to find website features that are underperforming.” If your website beats those benchmarks that should not stop you improving. Whilst it’s great to know you’re doing well in a particular area, there are many comparative metrics you can check with our benchmarks to fully understand your performance overall. If your site is struggling with engaging users, then check out our suggestions on improving your bounce rate . Want to know how your site performs? Head over to Littledata Benchmark page and click 'Benchmark your site' to check your performance against others. How Littledata benchmarks work? We gather data from thousands of Google Analytics profiles, and anonymise them in a series of benchmarks, to give insight into how your marketing efforts are paying off. With this benchmark data, you can stop being in the dark about how your website performs and sign up to see how your site compares. Our customers also receive daily insight into site or app performance with our actionable trends reports. You can explore these and other benchmarks via Littledata Benchmark index page.   How would you use benchmarks in your daily work? Leave your comments below.

Google Analytics custom campaign tracking is essential for measuring the effectiveness of your marketing efforts. Let's say you were promoting your new ebook across social media and emails, how would you know which social post or email blast was the most effective? That’s where Google campaign parameters come in (also referred to as UTM). You simply add them to your URLs, which are then used in your web-based, email or ad promotions. When someone clicks on them, the custom information linked to these URLs via parameters is sent to your Google Analytics reports. If you don’t tell Google the specifics of your campaigns, then they will be rolled into existing buckets without the ability to identify them. This most commonly happens with emails and social posts that by default get classified as referrals. But once you start tagging your campaigns, you will see those social initiatives and email newsletters separated by campaign names and other information you provided. Tagged up links can also be used in email signatures, listings on other sites and social media profiles. By using campaign tagging you will understand better which URLs have been most effective in attracting users to your site or content, for example you'll see which: Email newsletter brought you the most traffic Ad was best at bringing you converting visitors Facebook post engaged the most users If you have goals set up, then you will also see how visitors from individual campaigns convert on your website. Using custom campaign data in reports You can access custom campaign data in Acquisition > Campaigns > All Campaigns report, where you will see your various campaigns based on the parameters used in URLs. You can also switch between viewing your campaigns by source and medium tags that you’ve used. Another report you can use is the Assisted Conversions (under Conversion > Multi-Channel Funnels) that summarises how your channels, or campaigns, contribute to your conversions. To see the campaigns, you need to click on 'Other', find 'Campaign' and select it. Now you will see data related to your campaigns only. Check Google's guidance on understanding the Assisted Conversions report. Be consistent Consistency is very important in campaign tagging so make sure that the parameters you use in your campaigns are exact. For example, if you use email, Email and E-mail, Google Analytics will record them as three different mediums in your reports. So, set your naming conventions and if you have a bigger team, then agree on what they are and make sure everyone is aware of them. What tags can you use in your campaigns? There are five types of information you can pass on with the tags/URLs. Three of them should always be used: Campaign source (utm_source) - identifies where the traffic comes from, eg newsletter, google. Campaign medium (utm_medium) – advertising or marketing medium, eg cpc, email. Campaign name (utm_campaign) – what the campaign is called whether it's a promo code or specific promotion, eg winter sale. The other two, whilst not required by Google, are useful for tracking additional information: Campaign term (utm_term) - identifies paid search keywords if you’re manually tagging your paid keyword campaigns, eg red shoes. Campaign content (utm_content) – helps differentiate between same type of content or links, useful when doing AB testing or using multiple calls to action, eg logo or text link. How to tag your campaigns? It’s easier than you might think. You can do it manually if you know how, but the available URL builder tools online make it super simple to tag your links correctly. But if you're using Adwords or Bing then you can enable auto-tagging so you don't have to worry about tagging them. For websites use the Google URL builder tool to append URL parameters. For Android, use the Google Play URL builder tool to append URL parameters. You also must have Google Play Campaign Attribution set up in your Android SDK. For iOS, use the iOS Campaign Tracking URL Builder to append URL parameters. You must use Google Analytics iOS SDK v3 or higher for this to work. For manual tagging, you need to enter a question mark after the URL and before adding your parameters. Then pair up the parameters with their values, eg utm_source=newsletter, and separate campaign parameters with an ampersand. After the question mark, parameters can be placed in any order. You'll end up with a link that'll look something like this: http://www.littledata.io/?utm_source=newsletter&utm_medium=email&utm_campaign=welcome, which is ready for use in your promo activities. Auto-tag your campaigns To make campaign tracking and tagging simpler, we have created a tool in Google Sheets that automatically creates a tagged up link. You'll need to fill the values for parameters and the formula will do the rest for you. To use it, you'll need to make a copy to store in your own Drive (via File option). Get campaign tracking sheet with URL builder   Got questions? Comment below or get in touch!

Demographics and interests reports in Google Analytics give you additional insight about your users, allowing you to do analysis based on age, gender and interest categories. You get a much better idea of who your users are and the setup is so quick to do, there's no reason not to. To get this information, you need to do minor tweaks to your Google Analytics and Google Tag Manager. Those changes will allow Google to share anonymised data about your site or app visitors, and once set up, you can use this information to understand the behaviour patterns of your users by different profiles. You will be able to see: If a particular age group converts more Whether you get more visits from males or females from a particular country or city If your users are more into travelling, movies or social media You'll also be able to: Build remarketing lists Build segments for more detailed information about your users Target your ads to specific users What reports will you get? Demographics Overview: snapshot view of your users by age and gender Age: Acquisition, Behaviour and Conversions metrics by age group (below 18 are not included) Gender: Acquisition, Behavior and Conversions metrics by gender Interests Overview: top 10 interests of your users in 3 areas: Affinity Categories, In-Market Segments and Other Categories Affinity Categories (reach): view of users by their lifestyle with Acquisition, Behaviour and Conversions metrics broken down by Affinity Categories In-Market Segments: view of users by their product-purchasing interests with Acquisition, Behaviour and Conversions metrics broken down by In-Market Segments Other Categories: more specific view of users with Acquisition, Behaviour and Conversions metrics broken down by Other Categories How does Google get this data? Google collects demographics and interests data from the third-party DoubleClick cookie for web traffic and anonymous identifiers for mobile app activity, like the Android Advertising ID and the iOS Identifier for Advertisers. But Google is unable to collect this data if the cookie or anonymous identifier isn't present, or if there's no profile information available. As a result, this data may only be available for a subset of your users. This will be shown on the report as a % of traffic the report represents. When is threshold applied? There are occasions when data is withheld from your reports to ensure the anonymity of users. For example, this might happen when you don’t have enough data for a particular age range or gender. When the threshold has been applied, you will see a notification below the report title. 3 simple steps to set this up 1. Enable the feature in Google Analytics Go to Admin > Property > Property Settings. Scroll down to Advertising Features, and set the option to Enable Demographics and Interests Reports to ON. Now save. 2. Enable the feature in Google Tag Manager Go to edit your GA pageview tag > Configure Tag. Under the tracking ID, tick the Enable Display Advertising Features box. Save the tag, and you've got one last step to do. 3. Enable the report in Google Analytics For this go to Audience > Demographics > Overview report. Click Enable, and you're all set. You should see your demographics and interests data within 24 hours of enabling the feature. We also provide consultancy services if you need help with more advanced setup.   Further reading: Tracking registered users with Google Analytics and GTM V2 How to use demographic targeting in AdWords  

Wondering why your bounce rate is so high and people are not sticking around? Here are some methods you should consider to improve user engagement with your content, conversion rates and sales. Bounce rate is the percentage of single page sessions or visits where the person didn’t engage further than the one page within your site. You shouldn't worry about the high bounce rate if your site visitors are meant to find what they were looking for on a single page. But if it's important for your site that users stick around for either reading more content or going through further pages that lead towards conversion, then you should review your options for reducing the bounce rate. By decreasing the bounce rate you can improve your ability to engage more users and eventually get them to convert. There are a few reasons why you would have a high bounce rate: Single page site or landing page Incorrect setup Wrong audience Design Usability User behaviour Low quality content You can identify your worst performing content by looking at the bounce rate in the Landing Pages report (under Behaviour > Site Content). If there is a high percentage of people leaving the pages without continuing their journey, then review those pages with the suggestions below. You should also check the average time spent on those pages. If users are leaving after a short amount of time, then you should look closely at what may be driving them away and if there are any improvements you can make to keep the visitor on the page for longer, or how to encourage them to visit other pages. Guide users through your website with additional links Users might leave your site after seeing a single page that contained the information they were looking for. If they got what they wanted and don’t care about actively exploring your website, then think about similar pages within your site that might be of interest to your users, and link to them within the content. You could link to: Another blog post covering similar topic from a different angle A case study to increase the credibility of your work Related blog post that the reader might like Best practices of using your product Case studies on how others have achieved results with your product Your product demo or webinar This can be applied to any pages from product and features to blog and about your team. Blog posts on Moz Blog are a great example of providing additional links that are useful and relevant. Improve your page load Your page loading time has a major impact on how quickly people will leave your site, which should be obvious to everyone. Slow site speed can be very discouraging to your potential customers and drive them away. How long would you wait for a page to load, before going elsewhere to a quicker website? 47% of users online expect the page to load in two seconds or less. The study cited in an article by Econsultancy is several years old so it is highly likely that people are even more impatient now, making the number of people abandoning the site even higher than the 40% it used to be. Check Google PageSpeed Insights for more detail. Make content readable It is difficult to read large chunks of text that consists of long paragraphs, too much jargon and bad formatting. With our shorter attention span and higher impatience, the more user friendly you can make the text, the better for your site performance. There are a number of ways you can improve the readability of your content: Large headings Bold subheadings Bullets and lists Shorter sentences and paragraphs Less or no jargon Write like you talk Use images Bold keywords where appropriate Add a relevant call to action on the landing page If you have a landing page for converting visitors, whether it is for getting them to enquire or sign up, you need a relevant and prominent call to action (CTA). At Littledata we use CTA in two places on the landing page - top and bottom - to help the user enquire about our services much quicker. I also like Intercom product pages, which have some awesome animations and illustrations, and a call to action that fits the theme. Your CTA could be focussed on getting your users to: Call the company to talk about the product Fill out a form Sign up for a trial Click on banner ad Watch video Subscribe to a newsletter Visit another page within your site or external site Econsultancy has collected examples of some awesome calls to action so check them out for inspiration. Check your landing pages meet visitor expectations If people expect to sign up for a free trial of your software product, but are instead taken to a homepage without a visible way of doing so, then expect a lot of bounces. Invision uses Adwords to promote its free platform plan. Once you click through, you see immediately the content you expect and the option to sign up. If you purchase some of your traffic, make sure you check what information visitors see on your partners’ site before clicking on the link. When we recently ran a number of tests to improve the bounce rate for our client, we were baffled by some of the improvements not having much effect. After further investigation it came out that the visitors on the partner sites were getting the wrong information about what they were clicking on. No surprise then that they were leaving the site so soon. For search engine results, review your page titles and meta descriptions, and make sure they match what the person will see on the page when they click on it. Set external links to open in a new window By providing an external link that opens within the same window, you are forcing your users to leave your site. This will not only affect your bounce rate, but you will also be increasing your exit rate. Instead of interrupting their journey this way, set any external links to open in a new tab. Avoid distracting users from the content Whilst some popups can be relevant to the content of the page and important for your aims, a badly timed popup can be very off-putting for your site users. Your landing page is there to convince the visitor to stay so if your popup displays instantly, you're not letting them see your content that they came for in the first place. Test different timings to see what works best for your users, but I'd be surprised if quickly displaying popups reduce your bounce rate. Autoplaying random songs can also be highly annoying. Especially when it's not the kind of song you listen to, on full blast, and hidden somewhere so it takes you ages to find the music to pause it. Just no.   There are no quick wins when it comes to improving your bounce rate. Keep making the improvements with your reader in mind and testing which changes work for you best. So I hope this has been helpful. If you have any experiences with methods mentioned above, do share in the comments below. Further reading: A win for the UK digital sector: UK sites perform better than US sites in benchmark 5 common Google Analytics setup problems to look out for How to accurately track time on site with Google Analytics or Google Tag Manager Stuck with reducing your bounce rate? Contact our certified Google Analytics specialists for help with your bounce rate or other advanced tracking.  

Analysis and reporting are the most time-consuming aspects of site or app performance tracking in Google Analytics. If you ever wished or thought if only it was quicker, then this post is for you. There are a number of techniques you can implement to speed up your data analysis and number crunching. Here I’ll cover 6 of them. Schedule email reports Google Analytics dashboards are a great way to monitor metrics that are important for your business. But instead of logging in every day or week, or however often you tend to check them, schedule automated email reports instead. At Littledata, we have a select few metrics that we keep track of on a weekly and monthly basis. The whole team gets an email report on a specified day, allowing everyone to get the latest stats without someone on the team having to get those numbers manually every time. To set this up, go to the dashboard that you want emailed to others (or yourself), click ‘Email’ and fill in the details. If you're scheduling the email to go to your team on a regular basis, why not add a nice message in the email body. To edit the scheduled emails you've set up previously, go to Admin > View > Scheduled Emails (towards the bottom of the list). Access your reports quickly Shortcuts in Google Analytics allow you to quickly view the reports you use most often. Even better, they remember the settings you applied to any report. So if you apply an advanced segment or another customisation to the report, saving it as a shortcut will remember your preferences. Except for the date range - that won't be remembered. You can find the shortcut option just below the report title, and once added, you'll find your shortcut reports at the top of the reports list in the left panel. Search for reports you can’t find If you find yourself wondering where a particular report is, use the search found at the very top. Instead of having to go through an extensive report list trying to find something you vaguely remember seeing last month, you get suggestions of what you might be looking for as you type. So you only need to remember or guess part of the report title that you're looking for. Use keyboard shortcuts Did you know Google Analytics has keyboard shortcuts? They allow you to move around the report much quicker and the date range keyboards make a big difference to a workflow. Picking date ranges can be tedious and annoying so I've found these to be the best. If you're already using keyboard shortcuts on your devices, you won't need convincing of their usefulness. To view this complete list of shortcuts in Google Analytics at any time, use a shortcut: ? Set up goals to understand your website visitors Goals are valuable in understanding how well your site or app helps you achieve your objectives. Unfortunately, we see a lot of businesses who either find it too complicated to set up or have done it incorrectly. Speaking from personal experience, it only takes a little practice to get the hang of it, and once setup, you get essential conversion data in your reports. You'll be able to evaluate your marketing efforts and campaigns much more effectively. Check out Google's guidance on goals and my guide on how to set up a destination goal funnel. See trends quickly with Littledata reports We have a clever tool that looks through all of your Google Analytics data and finds the most interesting changes to report on. There are over hundred of GA reports so getting automated summaries that you can act upon will save you hours of work. Littledata tool doesn't require installation and it's quick to set up - all you need is an existing Google Analytics account to sign up with for free. The reports you'll get are also great for presenting to colleagues in meetings, as other users have said. To get your reports, go to Littledata homepage, enter your website into the box and click 'Get started.' We're also working on bringing you benchmarking information, customised tips on how to improve your Analytics setup and what you should be tracking. Pro tip: Manage complex data with query explorer tool Whilst, not the quickest to get used to, Google's query explorer tool can be powerful for those working with large and complex datasets. Some of our biggest clients' websites get millions of hits a month, which can cause discrepancies in data analysis (especially when data is sampled). So I use the query explorer tool to verify the data that clients ask for. To use this tool, you will need to know your metrics from dimensions and learn more about how to use segments, filters and query building.   If you've got questions on any of the above, don't hesitate to comment below or get in touch!  

Wondering if Samsung Galaxy is more popular than iPhone when engaging with your content? Then set up the User-ID view to see your logged in users’ activity and evaluate behaviour by the device. With the activity data you collect in the registered users view, you can improve the analysis of your customers' behaviour by seeing which devices are used to sign up and access your website. To summarise the benefits: You get access to the Cross-Device reports, which allow you to analyse which devices your users use to engage with your content. See what the Cross-Device reports look like. You improve your understanding of logged in users who often engage with the site's content differently than those who aren't registered. You get a more accurate user count. In your standard analytics view, a new user is counted every time your site visitor switches to a new device or starts a new session. With the registered user view, you give each user a unique ID, which helps to stitch together various activities carried out by the user. You can find out which devices users prefer for different engagement activities across multiple sessions. This helps with tailoring your campaign and content to different devices and activities. To set this up, you need to have the user ID stored in the data layer. If you don't have it set up, scroll to the bottom for an advanced hack. Now let’s look at how to set up the tracking by using Google Analytics and Google Tag Manager V2. Looking to implement the User-ID in your tracking code? Check Google’s guidance. Enable the feature in Google Analytics Firstly, enable the User-ID feature by going to  Admin > Property > Tracking info > User-ID. Read through the short policy on what you’re allowed to track and not. Google is very strict about tracking personally identifiable information so you are not allowed to send any personally identifiable information, such as names and email addresses. But numbered IDs or hashed emails are fine to use. To agree to the terms, follow the steps and click ‘create.’ Create the variable in Google Tag Manager Now go to GTM variables and click 'new'. Select Data Layer Variable type and use the name stored in your data layer, e.g. uid or user ID Add the variable to your pageview tag Go to edit your pageview tag and click on More settings > Fields to set. Click Add field, enter the field name as &uid and select the variable you’ve just created - eg {{uid}} or {{userID}}. Test you're seeing activity in the newly created registered users view with your login, or a test one if you have it. Don't forget to publish your GTM container for tracking to work. Advanced hack If for some reason you can't get your developer to store a user ID in the data layer, there is a way around it. We've created a javascript variable to get a username off the page and hash it prior to sending it to GA. For this, you need to pick a custom Javascript type variable and enter the script below into the custom javascript field. This javascript requires either your developer or you to customise it to work on your page (see the notes in the second and third lines). function() { //dependent on using Jquery selectors //replace '.menuTitle small a' with the selector for your username var name = $('.menuTitle small a').text(); var hash = 0, i, chr, len; if (name.length == 0) return hash; for (i = 0, len = name.length; i < len; i++) { chr = name.charCodeAt(i); hash = ((hash << 5) - hash) + chr; hash |= 0; // Convert to 32bit integer } return hash; }; If you need help with any of the above, don't hesitate to comment below or get in touch!

This is a quick follow-up to my guide on how to exclude referral spam from your Google Analytics data. Filters exclude or modify the data from the time you add them and don't have any effect on previous traffic. This is where segments are very useful. Not only can you use a segment to view a cleaner version of your historical data but you can also test the setup of your filters. I've also found the Google's filter verification option quite unreliable but with the segment, you can verify the results yourself and see results straight away. Here I am going to show how to add segments to include valid hostnames and exclude spam referrals from your data. Add a segment to include valid hostnames Creating a filter to include visits from valid hostnames only is the first step you need to take to exclude spam referrals from your Google Analytics data. Test your valid hostnames regex by firstly going to Audience > Technology > Network > Hostname. Create a filter by clicking on ‘Add segment’ and then ‘New Segment’. Now select the conditions tab on the left, under advanced. Set up your filter with the following conditions: Sessions Include Hostname Matches regex (and your regex, eg yoursite|googleusercontent, in our case it's littledata|googleusercontent) Click on ‘Preview’ button on at the top to check which hostnames you are left with. Your list should look much cleaner and only display domains you used in regex. Add a segment to exclude referral spam Like before, you want to test this trigger when viewing a relevant report so go to Acquisitions > All Traffic > Referrals. Create a segment with the following details: Sessions Exclude Medium exactly matches referral AND Source matches regex (and your regex) Whilst filters have a limit of 255 characters, the advanced segment has much more character space to use. I've bundled all spam referrals into one long regex of 900 characters. But as explained in the guide on removing spam traffic you might have to break it up into multiple expressions or filters to fit them all in. By adding those two segments you can not only test that your filter setup is accurate but also view your historical data without fake traffic. If you need help with any of the above, leave a comment below or get in touch!

Do you know how many people start completing forms on your website, but don't complete them? Do you know which fields cause them difficulties? This is a guide to field-by-field form tracking using GTM. By tracking each element of the form separately, you will see how many people start filling out the form but then decide not to submit it. Once you understand where people drop off you will be able to identify any parts of the form that may need improving. The enquiry form on our website has four elements that I am going to track: the name, email and subject fields, and the button to submit the query. In summary, the set up will work like this: Create a trigger that will act as the firing rule for the tag Create a tag to track clicks on the field Repeat for each field So to set up the tracking of form fields and submits in GTM V2, follow these steps. Enable built in variables Firstly, you will need to enable built in variables. You will need Form ID variable and if similarly to our site you have the same enquiry form placed on several pages, then Page Path variable as well. These variables will allow you to track clicks on the form and on which pages the form was clicked on. The page path variable returns the URL part that comes after your main domain, eg /blog. Create the trigger For your trigger, you will need to find out the field ID you want to track. To find out the ID, if you are using Chrome browser, right-click on the field and select ‘Inspect Element’ It will look something like id=”name” so name here is the unique ID that you need to use with the trigger. If you do not have a unique ID associated with the field you want to track, ask your developers to add it in. This will make the tracking much easier. Now in GTM, go to Triggers tab on the left and click 'New'. You are creating a 'click' trigger, which you want to fire on 'all elements'. Save the trigger. Create the tag Go to Tags tab and click 'New'. Select Google Analytics and tag type 'Universal Analytics'. I send the following event tracking parameters to GA: Category: Enquiry form Action: Click on name Label: {{Page Path}} Now select 'Click' to select the trigger ‘Click on name’ as your firing rule. If there are any pages where you don’t want this tracked, then you will need to create a separate blocking trigger. Here is an example of a trigger for a contact us page that I want to exclude from tracking here. You can create your blocking trigger in a pop up window without leaving the tag. Repeat Follow the steps above to create the trigger and tag for each following field, and amend form ID’s and event field values for each. Test your tags in GTM debug mode and GA real time to make sure the details sent through are what you want. Once tested, publish your container and if you need any further help with any of the above, leave a comment below.   Further reading: How to track file downloads in Google Tag Manager V2 Tracking registered users with Google Analytics and GTM V2

The issue with the referral spam in Google Analytics exploded in May when we saw an average of 620 spam sessions per GA property and just the other week, I saw an account where spam accounted for 95% of the traffic! Spam referrals are greatly skewing your Google Analytics traffic and becoming a headache for a larger number of people. Why are these spam sessions appearing in your Google Analytics traffic? To get you click through to their site and ads (never ever do that, by the way). By targeting thousands of GA accounts like this, you can imagine how much traffic they get from those more curious about their new source of visits. There are two different types of spam referrals you are getting: Ghost referrals send fake traffic to your GA account by “attacking” random GA property IDs. Crawler referrals crawl your website to leave a mark in your traffic. The spam referrals are getting more persistent and clever by targeting other non-referral reports, like www.event-tracking.com appearing in events. How can you tell it's spam? By seeing unusual activity, odd referral sources, substantial changes in your metrics, and lots of (not set) values in various dimensions, eg hostname and language. So how do you remove spam referrals from your Google Analytics traffic? There are two filters you need to set up to remove both ghost and crawler spam referrals. Filters change your traffic permanently so if you don't have an unfiltered view of your data, then create one now. It's a good practice to have an unfiltered view that you don't modify and it allows you to check your filters are working correctly. We are also working on our own spam filter tool to help people get rid of pesky spam referrals with just a few clicks of a button. We have already released a beta version via our Littledata analytics reporting tool and are developing it further to make it more robust and comprehensive. But if you'd rather do it yourself, keep reading. Create a filter to include valid hostnames Since ghost referrals never actually visit the site, the best way to get rid of them is by creating a valid hostname filter. This filter will allow visits from “approved” websites that you consider valid. First, you will need to identify your valid hostnames by going to the report in Audience > Technology > Network > Hostname. Hostnames report shows domains where your GA tracking code was fired and helps to troubleshoot unusual traffic sources. Valid hostnames on the list will be the websites where you inserted the GA tracking code, use additional services, eg transactions, or reliable sites used by people to access your site, eg Google Translate. Your reliable hostnames could look like this: www.yoursite.com yoursite.com blog.yoursite.com translate.googleusercontent.com (user accessing your site via Google Translate) ecommercepartnersite.com webcache.googleusercontent.com (user accessing translated cached version of your site) Any other website that you do not recognise or looks suspicious, you can safely assume to be a hostname you want to exclude. Beware of any domains that appear as “credible sources", eg Google, Amazon and HuffingtonPost. They are used to mask the spammers. If you see (not set) hostname on your list, this could be because you're sending events to GA that don't have pageviews, for example tracking email opens and clicks. If you are sure you are not sending any such events to GA, you can also exclude any (not set) hostnames. Now that you have got your valid hostnames, you need a regular expression for a filter that will include your valid hostnames (and thus, exclude all other fake ones). It'll look like this: yoursite|googleusercontent|ecommercepartnersite In the regex above, the vertical bar | separating each domain means OR.  This will match any part of the string, so 'yoursite' will match 'blog.yoursite.com' as well as 'www.yoursite.com'. You can test your regex at http://regexpal.com/ by inserting your expression at the top and all the URLs at the bottom. All matches will be highlighted so you can see straightaway whether you have included all your valid hostnames correctly. Before adding the valid hostname filter in the settings, test it with an advanced segment. The results on the screen should now be only of your valid hostnames and without all the spammers. If all looks good, create a filter by going to Admin > View > Filters > New Filter. This will add a filter for that specific view only. If you want to add the same filter to more than one view, then check the details below. Select 'Include', pick a custom filter and select 'hostname' from the filter field menu. Now enter your regex into filter pattern field and click save.   Want to apply a filter to multiple views? Then go to Admin > Account > All Filters > New Filter.   The setup is exactly the same as above, except now you will see a section at the bottom titled 'Apply Filter to Views'. Select views you want to apply the filter to and move them to the right hand side box by clicking button 'add' in the middle. You're all set so click save. Add a filter to exclude campaign source Some of the known spam referrals are free-social-buttons, guardlink.org, 4webmasters.org and, most recently, the ironically named howtostopreferralspam.eu. Excluding spam referrals with campaign source filter is one of the most commonly mentioned methods online. This filter will exclude any referrer spam from the moment you add the filter (not from your historical data). The downside is that every time you have a new spam referral appear in your Google Analytics data you will have to add them to the existing filter, or create a new one if you’ve ran out of character space (allows only 255 characters). You can identify your spam referrals by going to referrals report found in Acquisition > All Traffic > Referrals. To save you some time, I have included the regex's we use below so you can copy them. Make sure you double check your referrals report against our list to see if there are any that haven't appeared in our reports yet. If you find a source not listed below, simply add it to the end and let us know in the comments. Similarly to setting up the filter to include valid hostnames only, now you need to add a filter to exclude spam referrals. We use the following regular expressions to filter out spam (yes, that's four filters): guardlink|event-tracking|vitaly rules|pornhub-forum|youporn-forum|theguardlan|hulfingtonpost|buy-cheap-online|Get-Free-Traffic-Now|adviceforum.com|aliexpress.com|ranksonic kabbalah-reg-bracelets|webmaster-tools|free-share-buttons|ilovevitaly|cenoval|bestwebsitesawards|o-o-6-o-o|humanorightswatch|best-seo-offer|4webmasters|forum69.info|webmaster-traffic|torture.ml|amanda-porn|generalporn depositfiles-porn|meendo-free-traffic|googlsucks|o-o-8-o-o|darodar|buttons-for-your-website|resellerclub|blackhatworth|iphone4simulator.com|sashagreyblog|buttons-for-website|best-seo-solution|searchgol|howtostopreferralspam 100dollars-seo|free-social-buttons|success-seo.com|videos-for-your-business.com The reason majority of the websites above do not have org/com/etc is that for these sites I have concluded that there are no other genuine sites with similar site names (or none that I could find) that would send our site traffic. So it is safe to exclude these sites by name only.  For example, there are many sites with adviceforum in their name so to avoid excluding any potentially genuine sites that are called adviceforum, I only exclude the one spam referral I saw in my traffic - adviceforum.com. If you notice that you have referral traffic from addons.mozilla.org but don't actually have an addon on Mozilla, then you should add addons.mozilla.org (more commonly known as ilovevitaly) to the list above in this format - addons.mozilla.org Select Campaign Source in the filter field menu and enter your regex into the filter pattern field. Repeat the process until you have got all four (or more) filters created.   This will help to clean up your Google Analytics data but you have to keep checking for any new spam referrals to add to the exclude filter. You can use advanced segments to view your historical reports without spam referrals. If you need help with any of the above or have further questions, don't hesitate to let me know in the comments.   Further reading: 5 common Google Analytics setup problems How to remove referral spam from historical data

Setting up tracking of file downloads in GTM V2 is much easier thanks to the new configuration wizard. It is more intuitive and takes you through the set up step-by-step. Let’s have a look at the basic configuration for sending tracking of file downloads from Google Tag Manager to Google Analytics as events. To set up this events tag you need to firstly create a trigger. Create a trigger This trigger will recognise every time someone clicks to download the file you want to track. In the given example I am using a simple regular expression to capture a number of file types I want to track -.(zip|exe|pdf|doc*|xls*|ppt*|mp3)$ Here the * means it will capture any repetitions of the file types it is next to, ie it will include file types doc and docx for Word documents, xls and xlsx for Excel spreadsheets, ppt and pptx for PowerPoint presentations. Save the trigger and create a new tag. Create a new tag Give your tag a meaningful name so you can easily recognise what the tag is for. We have previously created a variable (formerly known as macro) that stores our GA tracking code, which I use in the configuration settings. This way I do not have to re-enter the GA property ID every time I need it. This variable does all the work. Select your track type as 'Event' and insert your tracking parameters. Here I use the following but modify the fields based on what works for your business: Category is Download Action is Click Label is {{element url} Element url in the label field will store the URL of the file that was downloaded. Advanced tracking For advanced tracking, you can create a custom javascript variable with a code that will strip out the title of the downloaded file and store it in your GA. Have a look at Simo's example of returning file name. Set your tag to fire Last step is to add a firing rule, ie select a trigger that will fire your tag. Select the previously created trigger 'Click to Download' and you're all set. Test For extra care, test the tag both in GTM debug mode and GA real time. Publish Now publish the container with your newly created tag. If you need any further help, do leave a comment below.   Further reading: Tracking registered users with Google Analytics and GTM V2 Tracking web forms in Google Tag Manager V2

Google Analytics referral spam is a growing problem, and since Littledata has launched a feature to set up spam filters for you with one click, we’d like to correct a few myths circulating. 1. Google has got spam all under control Our research shows the problem exploded in May – and is likely to get worse as the tactics get copied. From January to April this year, there were only a handful of spammers, generally sending one or two hits to each web property, just to get on their reports. In May, this stepped up over one thousand-fold, and over a sample of 700 websites, we counted 430,000 spam referrals – an average of 620 sessions per web property, and enough to skew even a higher traffic website. The number of spammers using this tactic has also multiplied, with sites such as ‘4webmasters.org’ and ‘best-seo-offer.com’ especially prolific. Unfortunately, due to the inherently open nature of Google Analytics, where anyone can start sending tracking events without authentication, this is really hard for Google to fix. 2. Blocking the spam domains from your server will remove them from your reports A few articles have suggested changing your server settings to exclude certain referral sources or IP addresses will help clear us the problem. But this misunderstands how many of these ‘ghost referrals’ work: they are not actual hits on your website, but rather tracking events sent directly to Google’s servers via the Measurement Protocol. In this case, blocking the referrer from your own servers won’t do a thing – since the spammers can just go directly to Google Analytics.  It's also dangerous to amend the htaccess file (or equivalent on other servers), as it could prevent a whole lot of genuine visitors seeing your site. 3. Adding a filter will remove all historic spam Filters in Google Analytics are applied at the point that the data is first received, so they only apply to hits received AFTER the filter is added. They are the right solution to preventing future spam, but won’t clean up your historic reports. To do that you also need to set up a custom segment, with the same source exclusions are the filter. You can set up an exclusion segment by clicking 'Add Segment' and then red 'New Segment' button on the reporting pages and setting up a list of filters similar to this screenshot. 4. Adding the spammers to the referral exclusion list will remove them from reports This is especially dangerous, as it will hide the problem, without actually removing the spam from your reports. The referral exclusion list was set up to prevent visitors who went to a different domain as part of a normal journey on your website being counted as a new session when they returned. e.g. If the visitor is directed to PayPal to pay, and then returns to your site for confirmation, then adding 'paypal.com' to the referral exclusion list would be correct. However, if you add a spam domain to that list then the visit will disappear from your referral reports... but  still, be included under Direct traffic. 5. Selecting the exclude known bots and spiders in the view setting will fix it Google released a feature in 2014 to exclude known bots and spiders from reports. Unfortunately, this is mainly based on an IP address - and the spammers, in this case, are not using consistent IP addresses, because they don't want to be excluded. So we do recommend opting into the bot exclusion, but you shouldn't rely on it to fix your issue Need more help? Comment below or get in touch!

Destination goal funnels in Google Analytics track how well certain actions on your website contribute to the success of your business. By setting up a goal for each crucial activity you will get more focused reports on how visitors are using your website, and at what stage they are dropping out of the conversion funnel. The first time I tried to set up a destination goal was daunting, but after some practice, I am now seeing valuable information on how well visitors are interacting with our clients' websites. If like Teachable you have different subscription packages, then you might want to track how each subscription is converting. For this, set up the purchase confirmation page of each subscription plan as a goal, with a funnel to get additional insight into where people drop off. Step 1: Create a new goal To set up a destination goal go to Google Analytics Admin settings > View > Goals. Click ‘new goal.’ Step 2: Fill in destination goal details Google has some goal templates that provide set-up suggestions. They will only display if you have set your industry category in property settings. Selecting any of the given templates will only populate the name and type of the goal, but not the conversion details, which are more complicated for some. This is not very useful for me so I will ignore this: select ‘custom’ and click ‘next.’ Goal name Give your goal a descriptive name. You will later see it in various reports in Google Analytics so use whatever makes sense for you. Here I am going to use the name of the subscription plan I am tracking - Basic Subscription. Goal slot ID Goal slot ID is set automatically and you might want to change it if you want to categorise your goals. Select ‘Destination’ and click ‘next step.’ Step 3: define your destination goal Destination type You have a choice between 3 different match types. If you have an exact URL that does not change for different customers (without '?=XXX'), then use ‘Equals to’ for an exact match. If the beginning of your converting URL is the same, but there are different numbers or characters at the end of the URL for various customers, then choose ‘Begins with.’ Use ‘Regular expression’ to match a block of text within the URL. For example, if all your subscriber URLs have 'subscriber_id=XXX' somewhere then type 'subscriber_id=' into the text field. You can also use 'regular expression' if you need to match multiple URLs and know how to use special characters to build regex. One of our favourite tools to test regular expressions is Regex Tester. The match type you select here will also apply to the URLs in the funnel, if you choose to create one. Destination page Destination page is the URL where the conversion occurs. For Teachable, and most other websites that sell something online, the destination is usually a ‘thank you' page that is displayed after successful purchase. You might also have a thank you page for contact forms and newsletter signups, which you would track the same way as a payment thank you page. Here you insert the request URI, which is the URL part that comes after the domain address. It would look something like this: /invoice/paid /thank you.html /payment/success Step 4: Should you set a goal value? (optional) You can set a monetary value to your goal if you want to track how much it contributes. e.g. If the goal is visitors completing a contact form, and you know the average lead generates you £100, then you can put the value at 100. If you are an ecommerce site and want to track exact purchases, then set up enhanced ecommerce tracking instead. Step 5: Should you set up a funnel? (optional) If you have several steps leading up to the conversion, you should set up a funnel to see how many people move through each defined step and where they fall out. If you do not set the first step as 'required', Google Analytics will also track people coming into funnel halfway through. i.e. If the first stage of your funnel is the homepage, then it will still include visitors who land straight on your contact page. Verify Now that you have set up your destination goal, click ‘verify the goal’ to check it works. If all is set up correctly, you should see an estimation of the conversion rate your goal would get. If you do not get anything, then check each step carefully. Once all is well, click ‘create goal’ and check it is working after a few days or a week, depending on how much traffic you get. If you set up a funnel, you will see it in Conversions > Goals > Funnel Visualisation. This is what a typical funnel would look like. Because I did not set the first step as 'required' you can see people entering the funnel at various steps.   Need more help? Get in touch or comment below!

I see a two tier economy opening up in England, and it’s not as simple as the haves and have-nots. It’s between those that build machines, and those that will be replaced by them: between those that can code, and those that can’t. We’ve seen the massive social effects that declining heavy manufacturing jobs since 1970s have had on much of the North of England and Scotland, and I believe we’re at the start of a similar long-term decimation of service industry jobs – not due to outsourcing to China, but due to automation by computers.  Lots of my professional friends in London would feel they’re beyond the reach of this automation: their job involves being smart and creative, not doing production-line tasks. But it is these jobs, which currently involve staring at numbers on a screen, which are most at risk from computer substitution. If your job involves processing a load of data into a more presentable format (analysts, accountants, consultants and some types of traders) then a computer will eventually - within the next 20 years - be able to do your job better than you. In fact, within 20 years computers will be much better than humans at almost every kind of data processing, as the relentless extension of Moore’s law means pound-for-pound computer processing will be 1 million times cheaper than it is now. As Marc Andreessen put it, ‘Software is eating the world’, and we’re only just beginning to work through the implications.  This worries me. With the greater and greater levels of automation of the working world, what happens to employment? Last year we saw an incredible event in the sale of WhatsApp to Facebook: massive wealth creation ($17bn) accompanied by almost no job creation (33 employees at the time of sale). If a tiny number of highly skilled people can create a service with 300m paying customers, why do companies need to hire lots of people? In the utopian view of future work we give up all boring admin tasks to the machines, and focus on face-to-face interaction and making strategic decisions based on selected knowledge fed to us by our personal digital agents (like Google search on steroids). Lots more thinking space leads us to be more productive, and more leisure time makes us happier. But 30 years ago they thought computers would evolve into very capable personal assistants, when in fact office workers are chained to the screen for longer hours by the tyranny of email and real-time information flow. Look at Apple’s forecast from 1987 of what computing might look like in 2006: the professor is freed from the tedium of typing or travelling to the library. Yet they didn’t consider whether the professor himself might be needed in a world where students could get their lectures as pre-recorded videos. So the cynical view is that more volume of data will require more humans to interpret, and the technology will always need fixing. As companies become more automated there will be more and more jobs shifting into analysis and IT support; analogous to how, as postal mail has been replaced by email, jobs in the company post room have shifted into IT support. The problem is that there really are a limited number of humans that can set up and maintain the computers. I’d love to see society grappling with that limitation (see grass-roots initiative like CoderDojo) but there are some big barriers to retraining adults to code: limited maths skills, limited tolerance for the boredom of wading through code, and limited opportunities for people to test their skills (i.e. companies don’t trust this most critical of job roles to new apprentices). So those that have commercial experience in programming can command escalating day rates for their skills – and this is most apparent in London and San Francisco, while pay in other skilled areas is not even keeping up with core inflation. That leads us to the dystopian view: that the generation starting their working lives now (those 10 years younger than me) will see their prospects hugely diverge, based on which side of the ‘replace’ or ‘be replaced’ divide they are. If companies akin to Google and Facebook become the mainstay of the global economy, then they’ll be a tiny number of silicon sultans whose every whim is catered for – and a vast mass of technology consumers with little viable contribution to the workplace. Let’s hope our politicians start grasping the implications before they too are replaced by ‘democracy producing’ software!

Most companies will see a discrepancy between the transaction volumes recorded via web analytics and those recorded via internal sales or financial database. This article focuses on how to find and reduce that discrepancy, to give greater credibility to your web analytics data. Following on from our article on common Google Analytics setup problems, we are often asked why Google Analytics ecommerce tracking is not a 100% match with other records, and what is an acceptable level of difference. Inspired by a talk from Richard Pickett at Ensighten, here is a checklist to run through to reduce the sources of mismatch. The focus here is Google Analytics Ecommerce tracking, but it could apply to other systems. In summary, you wouldn’t ever expect there to be a 1:1 match, due to the different paths the two events take over the internet. The general consensus is that anything less than 4% of difference in transaction volumes is good, but could sometimes persist up to 10%. Factors that affect this target rate include how many users have got ad blockers or disable Google Analytics (popular in Germany, for example), what proportion are on mobile devices (which suffer from more network interruptions) and how the purchase thank you / confirmation page is built. So on to the list. 1. Are other Javascript errors on the page blocking the ecommerce event in certain situations? The most common reason for the tracking script not executing in the browser is that another bug on your page has blocked it (see GDS research). The bug may only be affecting certain older browsers (like Internet Explorer 7), and have missed your own QA process, so the best approach is to use Google Tag Manager to listen for any Javascript error events on the confirmation page and send these to Google Analytics as custom events. That way your users do the testing for you, and you can drill into exactly which browsers and versions the bugs are affecting. 2. Is the tracking code as far up the page as it could be? If the user drops their internet connection before the whole page loads then the ecommerce event data won’t get a chance to fire. The best approach is to load the script at the bottom of the <head> element or top of the <body>.  The Google Analytics script itself won't block the page load, and arguably in this one purchase confirmation page, the tracking is more important than the user experience. 3. Is the tracking code firing before all the page data has loaded? The inverse of the previous problem: you may need to delay firing the tracking code until the data is ready. This is particularly an issue if your ecommerce transaction data is ‘scraped’ from the HTML elements via Google Tag Manager. If the page elements in question have not loaded before the ecommerce tracking script runs, then the product names, SKUs and prices will be empty – or returning an error. 4. Is the problem only your ecommerce tracking script or just page tracking is general? It could be that the way you are sending the transaction data (e.g. product name, price, quantity) is the problem, or that the page tracking overall is failing in some cases. You can pinpoint where the problem lies by comparing the pageviews of the confirmation page, with the number of ecommerce events tracked. Caveat: on many sites, there’s another route to seeing the purchase confirmation page, which doesn’t involve purchasing (for example as a receipt of a historic purchase). In that case, you may need to capture a unique purchase event, which only fires when a new purchase is confirmed – but without any information on the transaction or products. 5. Are events from your test site excluded? Most companies will have a development, staging or user acceptance testing server to where the website is tested, and test users can purchase.  Are you blocking the tracking from these test sites? Some possible ways to block the test site(s) would be: Set up sub-domain specific blocking rules in Google Tag Manager (or better) Divert the tracking from your test subdomains to a test Google Analytics account, using a lookup macro/variable Set up filters in the Google Analytics view to exclude 6. Is your tag set with a high priority? Tag manager only. If you use Google Tag Manager and have multiple tags firing on the tracking page it’s possible that other tags are blocking your ecommerce data tag from firing. Under ‘Advanced settings’ in the tag editor, you can set a higher priority number for tag firing; I assume the ecommerce data to Google Analytics is always the first priority. 7. Are any strings in the product name properly escaped? A common problem is apostrophes: if your product name contains a quote mark character, then it will break the following Javascript. See Pete’s bunnies – the strings in yellow are valid, and everything after the stray apostrophe will be misinterpreted. The solution is to run a script across any text field to either strip out the quotation marks or replace any quotes with their HTML equivalent (eg &quot;). 8. Are your quantities all integers? One of our clients was selling time slots, and so had the ‘quantity’ of the ecommerce tracking data equivalent to a number of hours. Timeslots sold in half-hours (e.g. 1.5 hours) were not tracking… because Google Analytics only recognises a quantity which is a whole number, so sending ‘1.05’ will not be recognised as 1. 9. Are any possible ‘undefined’ values handled? It may be that the data on your products is incomplete, and some products that people buy do not have a name, price or SKU. The safest approach is to have some fall-back values in your Javascript tracking code to look for undefined or non-text variables and post a default value to Google Analytics. E.g. If ‘product name’ is undefined then post ‘No product name’, or for price, the default should be ‘0.00’. These will then clearly show up in your Ecommerce Product performance reports and the data can be cleaned up. 10. Are users reloading the page and firing duplicate tracking events? Check whether this is a problem for your site by using our duplicate transactions custom report to see multiple events with the same transaction ID. A solution is to set a ‘has tracked’ cookie after the ecommerce tracking has been sent the first time, and then check whether the cookie is set before sending again. 11. Are users going back to the page and firing the tracking at a later date? The sessions column in the transactionID report in step 9 should give you an idea of whether the problem is repeat page loads in one session, or users revisiting the page in another session. If you see duplicate transaction IDs appearing in other sessions there are a couple of possibilities to investigate: Could users be seeing the page again by clicking on a link to an email, or from a list of historic orders? Are there any back-end admin pages that might link to the confirmation page as a receipt? In both cases, the solution is to have a different URL for the receipt that the one where the ecommerce tracking is fired. If there are any other troubleshooting steps you have found helpful, please let us know in the comments or get in touch!  

Can you rely on the data you are seeing in Google Analytics? If you use it daily in your business you should really give some time to auditing how the data is captured, and what glitches could be lurking unseen. The notifications feature in Google Analytics now alerts you to some common setup problems, but there are more simple ones you could check today. Here are 5 aspects of your Google Analytics account to check now. Are you running the latest Universal Analytics tracking code? Is your overall bounce rate below 10%? Are you getting referrals from your own website? Are you getting ‘referrals’ from your payment gateway? Have you got the correct website default URL set in GA? Are you getting full referring URL in reports? 1. Are you running the latest Universal Analytics tracking code? You may have clicked upgrade in the Google Analytics admin console, but have your developers successfully transferred over to the new tracker code? Use our handy tool to test for universal analytics (make sure you copy your URL as it appears in the browser bar). 2. Is your overall bounce rate below 10%? The 'bounce rate' is defined as sessions of only one page. It’s highly unlikely to be in single digits unless you have a very unique source of engaged traffic. However, it is possible that the tracking code is firing twice on a single page. This double counting would mean Google Analytics sees every single page view as two pages – i.e. not a bounce This is more common on template-driven sites like Wordpress or Joomla, where you may have one tracking script loaded by a plugin – and another pasted onto the main template page. You can check if you have multiple pageviews firing by using the Google Tag Assistant plugin for Chrome. 3. Are you getting referrals from your own website? A self-referral is traffic coming from your own domain – so if you are www.acme.com, then a self-referrals would be appearing as ‘acme.com’. Have a look at the (recently moved) referrals list and see if that is happening for you. This is usually caused by having pages on your website which are missing the GA tracking code, or have it misconfigured. You can see exactly which pages are causing the problem by clicking on your domain name in the list and seeing the referring path. If you are on universal analytics (please use our tool to check) you can exclude these referrals in one step with the Referral Exclusion list.  For a fuller explanation, see the self-referral guide provided by Google. 4. Are you getting ‘referrals’ from your payment gateway? Similar to point 3: if you have a 3rd party payment service where customers enter their payment details, after they redirect to your site – if you are on Universal analytics – they will show up as a new visit… but originating from ‘paypal.com’ or ‘worldpay.com’. You need to add any payment gateway or similar 3rd party services to that referral exclusion list.  Just add the domain name - so PayPal would be 'paypal.com' 5. Have you got the correct website default URL set in GA? When Google Analytics was first set up for your website you