How to calculate customer lifetime value (CLV) for subscription ecommerce in Google Analytics
Many of Littledata's subscription customers come to us with a similar problem: how to calculate return on advertising spend, considering the varying customer lifetime value (CLV) of subscription signups. Calculating marketing ROI for subscription ecommerce is a big problem with a number of potential solutions, but even the initial problem is often misunderstood. In this post I break down what the problem is, and walk through two proven solutions for getting consistent, reliable CLV reporting in Google Analytics. What is customer lifetime value? I work with all kinds of subscription ecommerce businesses: beauty boxes, nutritional supplements, training courses and even sunglasses-by-the-month. All of them want to optimise customer acquisition costs. The common factor is they are all willing to pay way MORE than the value of the customers' first subscription payment... because they expect the customer to subscribe for many months. But for how many months exactly? That's the big question. Paying for a marketing campaign which bring trial customers who cancel after one payment - or worse, before the first payment - is very different from paying to attract sticky subscribers. A marketing director of a subscription business should be willing to pay WAY more to attract customers than stay 12 months than customers who only stay one month. 12 times more, to be precise. So how do we measure the different contribution of marketing campaigns to lifetime customer value? In Google Analytics you may be using ecommerce tracking to measure the first order value, but this misses the crucial detail of how long those shoppers will remain subscribers. With lifetime customer value segments we can make more efficient use of media, tailor adverts to different segments, find new customers with lookalike audiences and target loyalty campaigns. There are two ways for a marketing manager to see this data in Google Analytics: one is a more difficult, manual solution; the other is an easier, automated solution that ties recurring payments back to the original campaigns. A manual solution: segment orders and assign a lifetime value to each channel It's possible to see the required data in GA by manually segmenting orders and assigning a lifetime value to each channel. For this solution you'll need to join together: (a) the source of a sample of first orders from more than a year ago, by customer number or transaction ID and (b) the CLV of these customers The accuracy of the data set for A is limited by how your Google Analytics is set up: if your ecommerce marketing attribution is not accurate (e.g. using Shopify's out-the-box GA scripts) then any analysis is flawed. You can get B from your subscription billing solution, exporting a list of customer payments (and anonymising the name or email before you share the file internally). To link B to A, you'll need either to have the customer number or transaction ID of the first payment (if this is stored in Google Analytics). [subscribe] Then you can join the two data sets in Excel (using VLOOKUP or similar function), and average out the lifetime value by channel. Even though it's only a sample, if you have more than 100 customers in each major channel it should give you enough data to extrapolate from. Now you've got that CLV by channel, and assuming that is steady over time, you could import that back into Google Analytics by sending a custom event when a new customer subscribes with the 'event value' set as the lifetime value. The caveat is that CLV by channel will likely change over time, so you'll need to repeat the analysis every month. If you're looking to get away from manual solutions and excessive spreadsheets, read on... A better solution: tie recurring payments back to the original campaign(s) What if you could import the recurring payments into Google Analytics directly, as they are paid, so the CLV is constantly updated and can be segmented by campaign, country, device or any other standard GA dimension? This is what our Google Analytics connection for ReCharge does. Available for any store using Shopify as their ecommerce platform and ReCharge for recurring billing, the smart connection (integration) ties every recurring payment back to the campaigns in GA. Here's how the connector works The only drawback is that you'll need to wait a few months for enough customer purchase history (which feeds into CLV) to be gathered. We think it's worth the wait, as you then have accurate data going forward without needing to do any manual imports or exports. Then, if you also import your campaign costs automatically, you can do the Return on Investment (ROI) calculations directly in Google Analytics, using GA's new ROI Analysis report (under Conversions > Attribution), or in your favourite reporting tool. Do you have a unique way of tracking your marketing to maximise CLV? Are there other metrics you think are more important for subscription retailers? Littledata's connections are growing. We'll be launching integrations for other payment solutions later this year, so let us know if there's a particular one you'd like to see next.
Littledata's Shopify connection is now using gtag and GTM data layer
Shopify's 'sales by traffic source' report is broken
If you're a Shopify store manager, one of your biggest questions should be 'which campaigns lead to sales?'. We looked at data from 10 Shopify Plus customers to see whether the sales by traffic source report can be trusted. Under the Shopify store admin, and Analytics > Reports tab, you can (in theory) see which sessions and sales came from which traffic sources. BUT this sales by traffic source report is broken. Looking at 180,000 orders for 10 stores in Q4 2018, here are the marketing channels which Shopify Analytics says brought the traffic: Direct 83.5%Social 9%Search 4.5%Unknown (other websites, not social or search) 3%Email ~0.1% And using comparative data from Google Analytics we know this is all wrong. Here's a comparison of Shopify's attribution to Google Analytics last-click attribution of sales for one of these customers: Marketing attribution comparison for 700 orders Shopify Google Analytics Direct 99% 43% Search (Paid + Organic) 0.6% 7% Social 0.4% 10% Email - 25% Affiliates - 15% Here's why it's broken 'Direct' traffic is when the source is unknown. But for Shopify's report this means where the source of the last session is unknown - the user most probably visited a search ad or product review previously. Having only 1% visibility on your marketing performance is just not acceptable!We know that tagged Facebook traffic alone represents 7% of traffic for the average store, so 10% of sales from Social is more normal. Social also brings more than the actual sales in terms of visibility and influencers.Google generates billions of pageviews a month for ecommerce stores. If your site gets only 1% of its traffic from search, we'd be very surprised! Including paid search this site is still well below the 40% average. (Check out our 6 essential benchmarks for Shopify stores.)Monthly emails and personalised retargeting emails are now a staple of online marketing, and we know all the customers in this analysis use email marketing of some form - including for new product launches, discounts and cart abandonment campaigns. The problem is, it's unlikely to be the only campaign which brought customers, so it gets drowned out by other 'last click' channels. The solution: multi-channel attribution.Affiliates are a really important channel to get right, as they are paid based on the sales attributed to them. Why should you rely solely on the report the affiliate marketer gives you, and not see the same numbers in Google Analytics? So don't leave your marketing analytics to guess-work! Try the Littledata app to connect Shopify with Google Analytics on a free trial today. All paid plans include unlimited connections, to ensure accurate marketing attribution for sales via ReCharge (subscriptions), CartHook (one-page checkout), Refersion (affiliates) and more.
The year in data: 2018 in ecommerce statistics
How did ecommerce change in 2018? Let's take a look at the data. Littledata benchmarks online retail performance in Google Analytics, and with over 12,000 sites categorised across 500 industry sectors we have a unique insight into ecommerce trends in 2018. The pattern we're seeing is that web sessions are becoming ever shorter as users split their attention across many ads, sites and devices. Marketers need get visibility across a range of platforms, and accept that a customer purchase journey will involve an ever greater number of online touch points. In the following analysis, we look at how performance changed across 149 ecommerce sites in 2018, and how these trends might continue in 2019. Ecommerce conversion rate is down Ecommerce conversion rate has dropped by an average of 6 basis points, not because of a drop of online sales - but rather because the number of sessions for considering and browsing (i.e. not converting) has risen. This is partly an increase in low-quality sessions (e.g. SnapChat ads preloading pages without ever showing them to users), and partly an increase in users from platforms like Facebook (see below) which bring less engagement with landing pages. See our mission to Increase Ecommerce Conversion Rate for more details. Revenue per customer is up Revenue per customer is the total sales divided by the total number of users which purchased online. The increase of $16 USD per customer per month shows that many stores are doing better with segmentation - ignoring all those sessions which don't convert, and retargeting and reselling to those that buy lots. The growth in subscription business models is also fuelling this trend. Getting a customer to commit to a regular payment plan is the most effective way of increasing revenue per user. See our mission to Increase Average Order Value for more details. Reliance on the homepage is down Content marketing became mainstream in 2018, and no self-respecting brand would now rely on the homepage alone to drive interest in the brand. The percentage of traffic coming 'through the front door' will continue to fall. In building out a range of keyword-specific landing pages, stores are harnessing a wider range of Google search queries, and providing more engaging landing pages from Google Ad and Facebook Ad clicks. Usage of internal site search is up Along with fewer visitors coming through the homepage, we are seeing fewer browsers use traditional category navigation over internal search. We think this is partly to do with younger consumers preference for search, but also probably reflects the increasing sophistication and relevance of internal search tools used by ecommerce. Referrals from Facebook are up Even after Facebook's data security and privacy embarrassments in 2018, it continues to grow as the 2nd major global marketing platform. Although few sites in our benchmark rely on Facebook for more than 10% of their traffic, it is a significant driver of revenue. As merchants continue to come to Littledata to find out the real ROI on their Facebook Ads, check back next year for a new round of analysis! How did your site perform? If you're interested in benchmarking your ecommerce site, Littledata offers a free trial to connect with Google Analytics and audit your tracking. You can see ecommerce benchmarks directly in the app, including 'ecommerce conversion rate', 'referrals from Facebook' and 'reliance on the homepage', to know exactly how your site's performing. Sign up today to benchmark your site and import Facebook Ads data directly into Google Analytics. [subscribe] For this article we looked at Littledata's private, anonymized benchmark data set, selecting ecommerce sites that had a majority of their traffic from the US and more than 20,000 sessions per month. We measured the change from 1st December 2017 to 31st December 2017 to the same month in 2018.
What is the average Add To Cart rate for ecommerce? (INFOGRAPHIC)
Add-to-cart (ATC) rate is a great indicator of your ability to turn visitors into buyers. When people click the Add To Cart (aka 'Add To Basket') button they are showing real intent to purchase. There are lots of different things that influence this metric, from user experience factors to product selection, pricing, and merchandising. So what is a good Add To Cart rate? As ever there tends to be quite a lot of variation from sector to sector. Some ecommerce stores might be more prone to window shopping, whereas others are geared up for impulse purchases. For example, home furnishings sites have an average add-to-cart rate of less than 3%, whereas beauty sites achieve almost 7%. The average for ecommerce in general hovers around the 4% mark, so if your site is wildly below that number then this is an area worth spending some time on. After all, increasing add-to-cart rate is almost certain to increase sales. I've analysed data from Littledata's ecommerce benchmarks, which tracks more than 12,000 ecommerce sites. The infographic below highlights Add To Cart performance data for a number of sectors. How does your site compare? Download our Add To Cart rate infographic Are you on track to beat the benchmark in 2019? If you don't see your sector listed above - or even if you do - then sign up to Littledata for full access to ecommerce benchmarking data for more than 150 sectors. Joining is simple. It's just a case of connecting Google Analytics and then diving into the good stuff. We have dashboards for monitoring your key metrics, as well as ecommerce benchmarks and hundreds of optimisation tips via Littledata Missions, to help you improve your performance.
Our top 5 posts from 2018
Happy new year! With a lot of big things on the way for Littledata this year, including new Connections to automate analytics for an even wider range of popular ecommerce apps and platforms, we wanted to take a moment to look back on the posts you found most useful with our current feature set. Last year we reviewed our top posts from 2017 and found that the focus -- not surprisingly -- was on Shopify and Google Analytics. This time around, our most-read and most-shared posts have really honed in on individual features and connections, especially for larger stores using one of our enterprise plans for full account management and unlimited automation. Interestingly, 4 out of the 5 top posts have a title in the form of a question. Perhaps a sign of 'plugged-in' (ie distracted) readers looking for a sense of engagement? 1. What's the real ROI on your Facebook Ads? 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? 2. Why don't my transactions in Google Analytics match those in Shopify? If we had a nickel for every time we hear this question! In this popular post, our partner manager breaks down common reasons for ecommerce data inaccuracy between Shopify and GA, and takes a look at how to fix those issues automatically. Find out the top 6 reasons for inaccuracy, including some orders never being recorded in Google Analytics! 3. New help center articles on Shopify tracking and ReCharge integration With detailed new articles on Shopify tracking and how our ReCharge integration works, the new Littledata Help Center quickly became a go-to resource for current customers and ecommerce managers this past year. Even before they become customers, many ecommerce industry folks are using the help center to get a clearer view of how to use Google Analytics effectively. We're happy to help! 4. Are you looking at the wrong Black Friday metrics? 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 in this post our CEO recommends looking instead at longer-term benchmarks. 5. Average order value benchmarks 2018: how do you compare? 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. The holiday shopping period in 2018 had us obsessed with one of our favourite ecommerce metrics: average order value (AOV). How does your site compare? This popular post includes a new infographic that breaks down the stats, using our set of private benchmark data about the ecommerce industry.
How to increase Add To Cart rate on your ecommerce store
Add-to-cart rate is a pivotal indicator of your ability to efficiently monetise your website. But are you doing everything you can to optimise your add-to-cart (ATC) rate? When a visitor adds items to the cart (or ‘basket’), they are revealing a high level of buying intent. As such it is a critical step in the purchase process, and is something that you should try to optimise. So what affects add to cart rate? And how might you go about improving it? Let’s explore why this is a crucial ecommerce metrics and take a look at what affects it. How to calculate ATC rate The formula is straightforward: you just need to figure out the percentage of visitors who have added an item to the cart / basket. You can track this via Google Analytics, if you’re using the enhanced ecommerce plugin, or directly via your Littledata dashboard, if you want to cut through the noise. Why is ATC rate important? Add to cart rate is one of the main metrics to keep an eye on if you manage an ecommerce site. It tells you so much about your product selection, pricing strategy, traffic acquisition tactics, merchandising, and user experience. For example, a sudden decline in ATC rate following an increase in marketing spend may be the result of targeting the wrong type of visitors after launching a new ad campaign. Or, it may be that your pricing is out of sync with the market. Likewise, if you’re charging for delivery then shoppers may look elsewhere to save on shipping costs. These things can be quickly adjusted, but only if you’re keeping an eye on ATC rate, and can figure out what is affecting any decline in click rates. How do I know if my ATC rate is good or bad? The average ATC rate is around 4%, though beauty, travel and retail sites tend to perform better than that. You can compare your own performance vs your peers via Littledata Benchmarks, which tracks performance data from a sample of more than 12,000 ecommerce websites. If you connect Google Analytics you'll be able to see your own data alongside the market average. We use AI to determine your category, though you can manually override our selection should you wish to do so. The key things to get right Your inventory is probably the first thing you should analyse. If your visitors are looking to purchase something that you don’t sell, then it’s game over. You can’t expect these people to click the add to cart button. After that, look at the specifics of your product offering. Are you pricing products competitively? Some competitor research will help you to bring your pricing into line with the market average. You should also review perceptions of trust. If your site isn’t trustworthy then people won’t want to buy from it. Conduct some user testing to find out whether you’re sending out the right trust signals. Merchandising also plays a huge part in driving up ATC rates. You need to do a good job of selling, and not just the product in question but also related products and add-ons. Up-selling and cross-selling strategies can improve ATC rates, as well as a bunch of other ecommerce metrics. I’ve already mentioned visitor intent, and that’s something that is going to play a big part in whether people add items to the cart. Are you targeting people who are ready to buy, or people who are not so far along the purchase path? There are of course very good reasons for targeting both, and it’s important to think about ATC rate in the context of multiple sessions and an elongated buying journey. Finally, there are a whole host of user experience pitfalls to dodge, and some optimisation tactics to test... How does the user experience affect ATC rate? If we put the product / pricing / people challenges to one side, we can focus on some of the onsite areas to address. So how might a poor user experience cause problems for prospective shoppers? Well firstly, there’s the simple matter of findability. Being able to easily find products is absolutely essential. That means providing shoppers with intuitive navigation, strong scent trails, excellent onsite search tools, and the ability to sort and filter items. Then, when it comes to clicking buttons, there are all sorts of basic things to get right. Button optimisation is the science of enticing clicks through good practice and persuasion, but it’s also about making sure that buttons can actually be clicked (especially for mobile users). There’s also the gentle art of copywriting, which is a proven winner when it comes to the things you can easily test. Words are incredibly powerful and tiny changes can have a dramatic impact on click rates, and all sorts of other metrics. [subscribe] So what can I actually do to increase my ATC rate? You can work your way through the above areas when conducting an ATC rate audit. Let’s also narrow our focus towards the onsite experience, as I have some specific ideas to help you optimise your buttons. I will outline these below. These ideas are taken from our button optimisation basics mission, which is aimed at improving ATC rate. So then, here are some simple ways to quickly optimise your add to cart buttons. Be sure to check out Littledata Missions for more proven ideas to help you increase the key ecommerce metrics… and online sales. Test, test, test! 1. Add some 'bonus text' within or below the CTA Spicing up your CTA with an extra message around it can work really well. ShipStation uses this tactic with their landing page, as shown below: If you weren’t already tempted to start your trial, you might become more willing after taking the 'no credit card required' message into account. 2. Allow shoppers to add items to cart on product list pages On product listing pages the primary objective is to get the user to buy, not to read information. As such, you should allow shoppers to be able to buy directly from list pages. It will provide a fast-track to the checkout for anyone in a rush to buy. Make your list pages scannable and use contrasting colours for ATC buttons to improve visibility. 3. Create great micro-copy Optimise your micro-copy and CTAs to ensure they never fall on deaf ears. Use of power words in every CTA and super descriptive headlines. 4. Design a button big enough to touch Fitt’s Law states that the bigger a button is, the easier it is to click on. Simple, really. And it usually pays off: studies have shown that increasing a button size by 20% lead to a jump in conversions. Optimising for a mobile platform is a key part of this, as a comScore study found that consumers spend 69% of time shopping on mobile devices. Buttons need to fit inside the screen and be easy to read, before they can be touched. Buttons should be large enough to be clickable, without distracting from the value proposition. 5. Leave enough space between tappable links Mis-pressing is common on mobile devices, as evidenced by all of your embarrassing typos. You don’t want your customers getting frustrated that their finger keeps pressing an unwanted button or link, so ensure that they're a) big enough and b) there is enough space is left between them. 6. Keep conversion elements above the fold Peep Laja has stated that content placed above the fold grabs 80% of our attention. As such this is the obvious place to start when optimising the key conversion elements on your website. Meanwhile, an eyetracking study by Nielsen Norman group found that 102% more attention is paid to information above the fold, compared to that placed below the fold. Things to optimise at the top of the page include your primary call to action, buttons, navigation, basket, personalised content, and merchandising. 6. Lower the commitment (‘shop now’ vs. ‘buy now’) One A/B test compared conversions between three versions of a CTA, which were: “buy now”, “order now” and “add to cart”. The latter saw a significantly increased conversion rate (approximately 11%) in all three sites tested. “Add to cart” does not imply the act of kissing goodbye to your cash quite as much as the other variations do. A shopper may feel much more inclined to react positively to this lower level of commitment. 7. Place risk-reducing messaging next to buttons and CTAs The only way a customer is going to purchase your product is by making them feel comfortable enough to click on all the buttons that stand in their way. Copyblogger emphasises the importance of risk-reducing messages around buttons. It found that one small variation in text produced 34% more conversions than a version that didn't provide any reassurance. 8. Use "click triggers" adjacent to buttons and CTAs It would be great if every visitor to your site would follow your well-intentioned CTA and add things to their carts. Fortunately, it has been shown that this could happen more often if you provide a nudge or two. Nudges can be as simple as declaring potential savings should a customer buy your product during a sale. Other click triggers which can boost your site’s performance include ones which eliminate doubt, simplify the purchase process or provide some kind of guarantee. 9. Use a text call to action for your ‘add to cart’ button Many studies have shown that it’s better to use text within the button as a call-to-action, as opposed to an icon (though you can use both). One such test was undertaken by Fab, which replaced a small, icon-focused button with a larger, text-focused button. This simple test increased ‘add to cart’ clickthroughs by a seriously impressive 49%. 10. Use action words for button labels The language you choose for your CTA can have a real impact on its performance. Words like ‘get’, ‘try’, ‘go’ and ‘add’ are all well worth testing. Start your button optimisation mission today Littledata has a range of Missions to help optimise things like ATC rate. You can launch the button optimisation basics mission directly in the app! We’ll measure the results in your personalised dashboard, and will suggest a bunch of other optimisation ideas to help you improve overall ecommerce performance. In doing so you will also get access to all of the other lovely Littledata features and tools. What’s not to like?
Introducing Shopify Flow connectors for Google Analytics
Littledata has launched the first Shopify Flow connector for Google Analytics, enabling Shopify Plus stores to analyse customer journey using a custom event in Google Analytics. In addition to Littledata's native connections with Shopify, Shopify Plus, Facebook Ads, ReCharge, etc., we have now launched a beta version of a Flow connector for Google Analytics. What is Shopify Flow? Flow is an app included with Shopify Plus, which enables stores to define automation pathways for marketing and merchandising. Think of it as an ‘If This Then That’ generator just for Shopify. For example, after an order is marked as fulfilled in Shopify’s admin you might want to trigger an email to ask for a review of the product. This would involve setting a ‘trigger’ for when an order is fulfilled and an ‘action’ to send an email to this customer. How do you use Littledata Flow actions? You install Littledata's Shopify app along with Shopify Flow Every time an order is created in your store we send it to Google Analytics, along with information about which customer ID made the order (nothing personally identifiable) You add Littledata's actions to your Flow Every time the order or customer event is triggered, even for offline events, the event is linked back to Google Analytics In Google Analytics you can then: Segment the customer base to see if these actions influence purchasing behaviour Visualise when these events occurred Analyse the customers making these actions: which geography, which browser, which marketing channel (in GA 360) Export the audience to retarget in Google Ads (in GA 360) Export the audience to run a website personalisation for using Google Optimize How do you set the actions up in Flow? Google Analytics customer event – can be used with any customer triggers, such as Customer Created Google Analytics order event – can be used with any order triggers such as Order Fulfilled, Order Paid, How else could I use the events? You can now link any of your favourite Shopify Apps with Flow connectors into Google Analytics. Some examples would be: Analyse if adding a product review leads to higher lifetime value Retarget in Google Ads after a customer's order is fulfilled Set up a landing-page personalisation for loyal customers (using Loyalty Lion connector) How much does this cost? The Flow connectors are included as part of Littledata’s standard subscription plans. You’ll need Littledata’s app to be installed and connected to link the events back to a customer – and to get reliable data for pre-order customer behaviour. [subscribe] Can Littledata set up a flow for a specific app? Our Enterprise Plans offer account management to help you configure the Littledata Shopify connection, including the Shopify Flow connectors. Get in touch if you have a specific app you'll like to make this work with.
Why don't my transactions in Google Analytics match those in Shopify?
Subscribe to our blog
Get the latest posts in your email
Get the Littledata analytics app
Complete picture of your ecommerce business. Free Google Analytics connection, audit and benchmarks.Sign up