Tips on how to improve your conversion rate optimisation (CRO)

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.

2017-01-04

3 reasons why you should use Google Tag Manager

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.

2016-12-13

Online reporting: turning information into knowledge

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.

2016-12-12

Top 6 pitfalls of Shopify analytics

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.

2016-12-08

Why do I need Google Analytics with Shopify?

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.

2016-12-07

Tracking customers in Google Analytics

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.

2016-12-06

Comparing 3 time ranges in Google Analytics

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.

2016-12-01

Top 5 Google Analytics metrics Shopify stores can use to improve conversion

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.

2016-11-30

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