Littledata at Codess
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).
The end of the ecommerce 'thank you' page
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. [subscribe] 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.
Custom reporting for marketing agencies
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 [subscribe] 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 :)
How to add tracking for multiple websites or apps (VIDEO)
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. [embed]https://www.youtube.com/watch?v=xoISTTx1zlw[/embed] 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. [subscribe] 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!
TechHub London demo roundup
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. [subscribe] 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.
Introducing Buyer Personas
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. [subscribe] 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.
Is Google Analytics accurate? 6 common issues and how to resolve them
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). [subscribe] 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.
Why are all my transactions coming from Direct or Referral in Google Analytics, with no marketing attribution?
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. [subscribe] 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.
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