How to calculate customer lifetime value in Google Analytics for Shopify subscription stores
Many of Littledata's subscription customers come to us with a similar problem: how to calculate return on advertising spend (ROAS), considering the varying customer lifetime value (LTV) 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'll break down what the problem is and walk through two proven solutions for getting consistent, reliable customer lifetime value reporting in Google Analytics. [tip]Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.[/tip] 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. Why? Because they expect the customer to subscribe for multiple 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 that 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 customer lifetime 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. [subscribe] As you can see below, 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: the first is a more difficult, manual solution. The other is an easier, automated solution that ties recurring payments back to their original campaigns. 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 LTV 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 to either have the customer number or transaction ID of the first payment (if this is stored in Google Analytics). 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 LTV 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 LTV 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... Calculating customer lifetime value Subscription ecommerce is huge, and continuing to grow around the world. But Shopify Plus stores (in particular) selling products by subscription have a unique problem: how do I link the recurring customer payments back to the marketing campaign or channel that led to them subscribing? Unlike standard ecommerce, it’s not enough to track the payment upon a first signup. It is the customer lifetime value (LTV) which counts in any marketing calculation. “The great thing about a subscription businesses is that you don’t have to rely on one-time purchases.”-- Rob Hoxie, co-founder of Tiege Hanley (read the full interview). I've already laid out the time-intensive manual solution for subscription tracking. But before we get into the automated solution, let's discuss why you need to track customer lifetime value in the first place (and the various problems with tracking it in Google Analytics). I'll also get into Littledata's solution, which will work for you whether you’re using Bold or ReCharge as your Shopify subscription app. [note]Check out my ReCharge talk in full from the ChargeX conference in September 2019, where I discussed a similar topic.[/note] Why you must track lifetime value Let’s imagine a simple store selling a single subscription product for $50 per month. On average, it takes them $70 to acquire a new subscriber via Google Ads. Now let’s think about 3 fictional customers of that store: Claire, Eric and Luke. These 3 offer very different values to the business, and differentiating them (or the customer segment they represent) in Google Analytics is critical to business success. In the graphic below, you’ll see that Claire is costing the business money, as her lifetime value is less than the cost of acquiring her as a customer. Eric pays something, possibly buying twice from the business, but still has a short ‘lifetime’. Only Luke continues for a reasonable time (and may continue subscribing). Which of them brings the company profit? The answer is only Luke. Many subscription businesses only make money on customers who subscribe for over 3 months — but the loyal customers are immensely valuable, and may go on to pay for years. This also speaks to the immense value of customer retention among Shopify Plus stores. The problem with subscription analytics Measuring and attributing this lifetime value is hard. The events happen in three different places, and need to be linked back to give a net value to be properly tracked: Unfortunately, by default, the customer who chooses a subscription in Shopify may not be linked to the user that actually commits to a payment in ReCharge. In other words, transactions are often left improperly tracked and attributed; in many cases, the refund or cancellation is not tracked at all. Take this Google Analytics screenshot from one of our customers (before fixing): Although 19% of the traffic comes from paid search, none of the ecommerce transactions are attributed to paid search. Instead, they are linked to a totally different group of users from ‘direct’ traffic. Littledata’s solution Littledata’s Shopify app combines the three steps in the customer lifecycle to bring together a unified view of the customer in Google Analytics. Once that customer has gone through the checkout, we can also track each subsequent recurring payment back to that same pre-checkout user journey (including the marketing campaign from which they came), along with other custom dimensions in Google Analytics to help you analyse lifetime value. How subscription stores can use data to optimise marketing campaigns Once you have recurring payments feeding into Google Analytics, you can begin segmenting your marketing channels by those that bring a higher quality customer — ones that nearly or exactly match your target personas. By using Littledata’s smart PPC connections for Facebook Ads and Google Ads, you can also pull in advertising costs to calculate Return on Advertising Spend (ROAS). So do you know which marketing channels bring you customers with the highest lifetime value? Maybe you have one stand-out channel that brings the majority of Lukes, and some that only bring you Claires. A better, automated 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 customer LTV 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 or Shopify Plus as their ecommerce platform and ReCharge for recurring billing, the smart connection (integration) ties every recurring payment back to the campaigns in GA. 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. [note]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/note] Do you have a unique way of tracking your marketing to maximize LTV? 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. Quick recap Customer Lifetime Value (LTV) is the one metric that matters for a subscription business To scale using metrics like Return on Advertising Spend (ROAS), you need to have accurate LTV calculations first Getting that data into Google Analytics allows you to segment by marketing channel or campaign Littledata’s advanced Google Analytics integration for ReCharge stores provides an easy way to stitch the data together
Do Google Analytics 4 properties work with Shopify?
The short answer is no: until these new properties come out of Beta testing, we can’t recommend you use them with your Shopify store. We expect that to be in early 2021. In July 2019 Google brought out a public beta for combining website and native mobile app tracking called ‘App + Web’ properties. These are technically a big step forward for Google Analytics (GA), combining some of the flexible, event-based tracking from Firebase Analytics for mobile with the deeper reporting and journey analysis tools in GA. This got rebranded as Google Analytics 4 in October 2020. However, we believe these are not yet suitable for use because the reporting and management APIs which enable Littledata (and many other tools) to access and configure the data in Google Analytics are still in private beta. Where’s this new reporting going? What Google appears to be doing is rebuilding Google Analytics from the ground up, so it’s fair to call it ‘GA v2’. Some of the long-term problems they are addressing include: Flexible ways of building funnels based on a series of events and page views (i.e. no more limitation on ONLY page views or event funnels) More powerful ways to build ‘audiences’ used in other Google tools (such as Google Ads), instead of the clunky and error-prone advanced segment builder True event-level views of the data with ‘stream view’ Enabling events to be sent with many properties, rather than just event ‘action’ and ‘label’ See Krista Seiden’s excellent post for more information on the features. What’s next with Google Analytics 4? We expect it to come our of beta and ready for prime time in 2021.
Black Friday discounting increases next season’s purchasing
Black Friday Cyber Monday appears to be big business for ecommerce merchants. But what happens after the promotions? I knew Black Friday had reached ‘late adopter’ stage when a company I’d bought fencing panels from – fencing panels – emailed me their holiday season promotions. But the real question is this: will all these promotions actually drive customer loyalty, or only attract bargain hunters? Looking at the data 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. 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. What sectors does Black Friday affect? The other interesting question is what sectors does Black Friday affect? 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 saw an average boost of 40% for the week. The graph below shows the difference with the average sales volumes in November & December 2016, by sector, for 3 selected weeks: 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. [subscribe] *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 an 18% probability that the two groups had the same mean, not allowing us to dismiss the null hypothesis. [note]This Black Friday ecommerce strategy post was originally published in November 2017 but has since been updated.[/note]
My ReCharge talk: which marketing channels bring you profitable customers?
In September 2019, our team attended #ChargeX in LA, an annual conference for the Shopify ReCharge community. There were agencies, app developers, and a ton of Shopify Plus stores using ReCharge to power their subscription ecommerce. Day 1 of the conference was mainly focused on partner agencies looking to build off the ReCharge platform, while day 2 was designed for Shopify merchant success. We saw plenty of familiar names and faces, but perhaps the highlight of the weekend was sharing my talk which orbited around lifetime value: which marketing channels bring you profitable customers? [note]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/note] Check out my full talk below. If you have questions, be sure to get in touch with support or our team of Google Analytics experts. If you have questions about our advanced Google Analytics connection for ReCharge stores, we're here to answer those too. Enjoy the talk! https://youtu.be/ubFDTY1M6HU Main points How agencies can measure which marketing channels bring in the most profitable customers Current fragmentation for marketing attribution – customer purchase data and browsing data in seperate silos Overview of the many channels that all funnel into calculating lifetime value from pre-checkout through subscription renewal How to predict which visitors will be high value, and experiment with what content you push to them Three levers that impact Customer Lifetime Value (LTV) [tip]Get accurate tracking for repeat orders with the ultimate ReCharge guide for Shopify and Shopify Plus.[/tip]
How Shopify Plus stores can set up multi-currency reporting in Google Analytics
An increasing number of ecommerce brands are using Shopify Plus to manage international stores and sell in multiple currencies. Since there are a few setups you may have, here are my recommendations in each case to get the most versatile reporting in Google Analytics (GA). For a single store accepting multi-currency Littledata’s enhanced Shopify tracking already handles multi-currencies at all stages of the shopping journey. We recommend you have just a single web property and single view in Google Analytics. Our audit checks will make sure the currency you have set up for this view matches your Shopify store currency. For multiple stores, with different default currencies (GA standard) I recommend you set up a single web property, but with different Google Analytics views for each country store. You can create one ‘All countries’ view in the same currency as your company’s default reporting, and then each country store would need filters set up to include traffic only from that country. Here's how to set up the filters: Go to the Admin section in Google Analytics, and click Filters under the View settings Then click to ADD Filter Then set up a filter to include traffic only from this store’s hostname Then Save the filter This could be tricky if you use a third-party checkout, where the hostname will be shared across stores (see below). Each country view in Google Analytics would have the same currency and timezone set as the Shopify store, so you can compare like-for-like orders. In Littledata, you would create different accounts for each country store and be able to audit and benchmark your stores' performances separately. Multiple stores, with different default currencies (GA 360) With GA 360, you have the added flexibility of being able to setup a roll-up property, combining ecommerce events from multiple properties. So you have two options: Go with the same solution as for GA Standard. The advantage here is that with a single web property, you can easily track visitors as they move between your country stores (i.e. if users are directed to a country after seeing a marketing campaign, you can still attribute the marketing campaign as they move to a different store). Set up a separate web property for each country store, and roll-up into a group property. The advantage here: your data is clean, but you can’t track cross-country visitors. Option 2 is going to work better if you leverage third party checkouts like ReCharge Payments or Bold Cashier, where it may be hard to filter out the traffic from only one country. If you're not sure what to think of this, don't fret — Littledata's analytics team can guide you in multi-site setup with an Enterprise plan, so please reach out if you're feeling confused. [subscribe] Multicurrency support for Shopify If your store presents prices in multiple currencies using Shopify Payment’s multi-currency feature, then Littledata’s app is 100% compatible with multi-currency. Here’s how it works for different parts of the data processing. We use Shopify’s definition of ‘presentment currency’ and ‘shop currency’. Storefront data layer All prices for products in the LittledataLayer and dataLayer variables will be in shop currency, regardless of the presentment currency. This includes the add-to-cart events handled by Littledata’s servers. Checkout steps Prices are sent in the presented currency and converted by Google Analytics (or Segment) to the target currency at current exchange rates. Orders & Refunds All orders and refunded items are sent to Google Analytics in the shop currency. Multiple country stores sending to one web property If you have multiple country stores, with different shop currencies, all sending data to a single web property in Google Analytics, this is also handled by our tracking script.
Does Littledata work with my ecommerce reporting tool?
We often get asked if Littledata works with certain reporting tools that are popular among merchants. Here's the short answer: if your tool can pull data from Google Analytics or Segment, then our smart connections will help you get accurate data to use with those reporting or data insight tools. Here’s exactly how we work with each platform. The Establishment These are the main ecommerce reporting tools. If you're using one of these tools, you're in luck. Littledata integrates with them automatically. These products include: Google Analytics Google Data Studio Tableau Segment Power BI Read on to see how Littledata works with these data insights tools to improve the accuracy of your data and the usefulness of your reporting. Google Analytics The world’s most popular analytics tool gets even better when paired with Littledata’s smart connections and full audit to enhance the ecommerce event data captured from your store. GA is the core tool to which Littledata connects, allowing you to connect to other dashboards below, such as Tableau and Data Studio. [subscribe] Segment Segment’s data pipeline is a trusted way to get analytics from one platform into dozens of others without complex engineering. Our source for Shopify and Shopify Plus helps you automatically send ecommerce events into any of Segment’s hundreds of destinations. Once the Segment connection is set up, you never lift a finger. Google Data Studio Data Studio is our dashboard tool of choice for more custom-designed reports. Because Data Studio integrates seamlessly with Google Analytics, Littledata’s connections can all be exported from Google Analytics into Data Studio, making our Shopify app the top Data Studio connector for Shopify stores. While it can be slow to generate reports at scale, Data Studio's unlimited free reporting makes it hard to beat for ad-hoc analysis. And they often add new report templates and visualizations. With Littledata's Data Studio connection, you get: Accurate sales data, including refunds and repeat purchases Custom dimensions for LTV reporting and cohort analysis Better marketing attribution, since our app stitches sessions together automatically [note]Are you looking for accurate Shopify sales data in Google Analytics and Google Analytics? Get the free ebook on Shopify tracking, including tips for tracking refunds and repeat purchases.[/note] Tableau Tableau, now part of the Salesforce family, was one of the first tools to provide a smart, easy setup dashboard. Their connection with Google Analytics is well established, and as with Data Studio you can access the Littledata events from there. Power BI Microsoft’s popular reporting tool can also import data from Google Analytics, so anything Littledata pushes to GA is available in Power BI. Power BI is especially useful if you want to visually explore your ecommerce data, as the platform offers interactive visualizations and a range of business intelligence (BI) insights. They also allow on-premises report deployment (behind a firewall), which is great for larger brands with large in-house teams. Newer solutions In addition to the 'establishment' above, Littledata seamlessly integrates with a number of newer reporting tools that offer Google Analytics insights and visualizations. These apps and reporting tools include: Glew Glow Yaguara These tools are especially popular with Shopify and Shopify Plus stores. Glew Glew provides some cleverly-curated ecommerce reports, but any of the underlying data on marketing attribution or customer behaviour pulled from Google Analytics will require Littledata’s improved tracking for full accuracy. Here’s a more detailed guide of the differences between Glew and Littledata. Grow Grow is a newer dashboard tool with hundreds of reporting sources, of which Google Analytics is their ‘most popular’. While some of the detail from Littledata’s connections may be lost in ‘basic reporting’ from GA, their multi-channel marketing reports are useful. Yaguara Yagura provides a series of templates to gain insights into your ecommerce business. One of their key integrations is with Google Analytics, and so the extra insights from Littledata’s tracking can be pulled into a Yaguara dashboard. Tools we don't work with directly The following tools don't connect with Littledata, and we aren't planning an integration. Conversific Conversific is an analytics tool for Shopify, with similar reporting to Littledata. While Conversific doesn’t offer the same smart connections as Littledata, it’s unlikely you’d need to use the two together. Metrilo Metrilo offers to optimize marketing channels for ecommerce. While their guide says Metrilo is a good alternative to Google Analytics, it won’t replace the reporting that Littledata provides. Zaius Zaius is an ecommerce CRM, allowing you to personalise and automate marketing based on customer interactions. As such, it needs its own event data capture, and can’t integrate with Littledata reporting. [note]Have you built custom reports using Littledata tracking? We'd love to hear about it. Give us a shout and let us know.[/note]
Why did Shopify delist Beeketing’s apps from their app store?
Shopify recently announced it will be delisting Beeketing apps from its store. Beeketing builds a popular range of marketing automation apps to improve on-site conversion on ecommerce stores. Shopify’s official statement says this was due to violations including “inadequate support for merchants and abuse of our marketing tools”. But was it also due to the apps' poor performance? [subscribe] To investigate, we looked at the July conversion rate for 115 stores using Beeketing’s apps versus 884 similar stores that did not use these plugins. We found that the median ecommerce conversion for stores using Beeketing apps was lower at 1.4% versus 1.6% for stores without their apps. At 10%, this confidence level is a significant differential. Although we found Beeketing apps increased add-to-cart rate (5.3% rate for Beeketing stores vs 4.2% without), this was not significant — it was based on a smaller sample of only 15 stores using Beeketing with add-to-cart rate tracked. What it means We can’t tell exactly which Beeketing apps these stores are using. However, we'd conclude that the seller urgency and intervening sales popups they are famous for might boost initial engagement, but don't help eventual purchasing. In delisting the apps, Shopify is likely not harming their merchants’ ability to sell. Speaking of ability to sell, did you know we've built a robust ecommerce benchmarking tool for merchants? Know where you stand with website benchmarks by industry and benchmark your own site with Littledata’s free optimisation tools.
Why Shopify is still the best ecommerce platform for larger merchants
It's no accident that Shopify is the cream of the crop in the world of enterprise ecommerce. But what do Shopify's major announcements last week mean for the platform's growth going forward? To remain on top, Shopify must continue investing in areas of opportunity and customer need. That's exactly what they're doing, including major investment in an independent fulfillment network, multi-currency and multiple-store/multi-site improvements for Shopify Plus, and a stunning new range of developer-friendly APIs. In this post, I'll look at: Which types of ecommerce merchants are using the major platforms Shopify's announcements at the Shopify Unite conference 2019 What these announcements mean for larger retailers, Shopify experts and agencies Who's using what: ecommerce platforms by size and use I've been crunching the numbers in several different ways these past few weeks, and my findings were consistent: Shopify is the platform of choice for mid-sized to large stores globally. Last week at the annual Shopify Unite partner event, Shopify announced the plans that will keep Shopify leading the pack (Magento, Salesforce Commerce Cloud, BigCommerce, etc.). Shopify's recent announcements confirm my research findings. Shopify will continue to be the ecommerce platform with the strongest growth in larger stores. At first I looked at trend data from BuiltWith that showed the number of net installs on each platform over the past year. Only the top 1 million websites were measured (as defined by BuiltWith.com). When it came to pure volume of installs, WooCommerce came out on top. However, the average WooCommerce store is much smaller and less active than the average Shopify store. I confirmed this by looking at our own data set of over 4,000 stores on these ecommerce platforms: The bars represent range from the bottom to top quartile of store sizes, with the purple marker representing median store size. While Magento 2 and Salesforce Commerce Cloud had higher median store sizes (32k and 107k monthly visits, respectively), Shopify had a very consistent interquartile range of 6,000 to 60,000 monthly visits. By contrast, WooCommerce only had one quarter of stores receiving over 10,000 monthly visits — and zero stores doing more than 2.5 million visits in our data set. In other words, if this trend continues, Shopify is positioned to take on a big share of the stores migrating from Magento 1 over the next year or so. And that's not all. What this means for merchants using Littledata These larger stores will need a range of robust apps to extend Shopify’s platform, especially when it comes to analytics. We've responded to this need in a many ways, including: Launching the only recommended Segment connection for Shopify and Shopify Plus Rebuilding our Shopify data layer and tracking script for speed and performance at scale Standardising Littledata's Enterprise Plans to provide account management and SLAs Working with select clients to build private connectors and apps to bridge legacy systems In other words, Littledata's commitment to Shopify's ecosystem has only continued to grow. We hope the pattern continues as we hone our popular Shopify integrations like ReCharge for subscription analytics, and continue to improve our better smart connections for other popular apps (CartHook, Refersion, Bold Cashier) over the coming months. [subscribe heading="Try Littledata free for 14 days" background_color="green" button_text="get started"] What this means for Shopify users Enterprise-grade features In the past, global brands running a network of stores in multiple countries have been frustrated by the simplicity of Shopify’s setup. The launch of features such as multi-currency, multi-language and multi-store login from a single Shopify Plus dashboard will go a long way in quelling those user frustrations — all while making Shopify Plus an attractive alternative for current users of Salesforce Commerce Cloud. Fulfillment network to compete head-to-head with Amazon (FBA) Fulfillment is the biggest headache for DTC brands selling globally, and FBA is currently the only game in town for end-to-end purchasing and logistics. However, as ecommerce brands scale, more and more are looking to "own the experience" from start to finish. This includes branded packaging and visibility of delivery on the customers' end. Both of these things may very well have a better solution in Shopify Fulfillment Network: Amazon vs Shopify. @aobtweetz says Shopify is like retail entertainment: consumers who want to read the blog, engage with the brand and then buy - not just buy a commodity on Amazon @debriefevent #ShopifyUnite — Edward Upton (@eUpton) June 21, 2019 The network will start in the US. While it will take time to scale, early looks indicate it will be a sensible way for Shopify to spend its large pile of cash while pulling itself away from the crowded pack of SaaS ecommerce. Developer-first attitude We developers love companies that don’t forget their product-first roots. Much of Shopify’s growth has been due to making the platform easy to extend while encouraging a vibrant yet curated app store. Shopify continues to exercise caution when offering its existing app partners access to new core features (subscription billing, opening up new APIs for partners to develop on). A staggering 11 new APIs were announced at this Unite alone. While Shopify clearly believes that core experiences like checkout and payment should be owned and developed by Shopify itself, many non-core features (including many types of reporting) are actively pushed to partners with a relevant app or service. A living example of Shopify's developer-first approach? Their new Shopify app CLI, which speeds up timetables for new app launches. Where does Shopify go next? After more than doubling its number of active stores over the last two years, Shopify's current haul of 820,000 active stores is in good position to surpass 1.5 million stores within the next two years. For many larger Shopify partners, perhaps the more important pattern of growth isn't Shopify's standard offerings — it's Shopify Plus. [subscribe heading="Try Littledata free for 14 days" background_color="green" button_text="get started"] At a recent Commerce Plus event in London (organised by Shopify Plus), the main "complaint" was that Shopify’s sales reps "can’t onboard shops fast enough". With a newly revamped, user-centered design, Shopify Plus is an exciting platform to be a part of right now. It's only going up from here. If you didn't get a chance to read about everything Shopify announced last week in Toronto, don't worry. We have you covered! Check out our full recap of announcements. Also, check out our award-winning Google Analytics Shopify app. With AI-based tech, the app fixes your Shopify analytics by providing: Website benchmarks by industry Ecommerce benchmarking Shopify reporting Customer lifetime value Average order value Other crucial data metrics Wondering how your site compares? Check out our list of essential benchmarks for Shopify stores.
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