What's new for ReCharge tracking
Are you ready for ReCharge v2.3? The latest version of Littledata's popular ReCharge connection is more powerful and extensible than ever. Subscription ecommerce is booming right now, especially for consumables like wine and coffee. Many Shopify stores are even seeing Black Friday-level traffic. But there's also more competition than ever. ShipBob has noted that subscription discounts are especially popular right now, during the seemingly endless days of COVID-19, as a way to bring new subscribers to your brand. This is a major opportunity -- but it also means that there's a lot more competition. Data is more important than ever to understanding your store performance and benchmarking your site, choosing the best marketing channels for your products and targeting the best customers with a higher lifetime value (LTV). Data is more important than ever to understanding your store performance So what exactly can you track with Littledata's ReCharge integration? ReCharge integration for Google Analytics Our ReCharge connection has gone through a lot of updates over the years, based on feedback from our customers, including smaller Shopify merchants, larger DTC brands on Shopify Plus, and our agency partners around the world. Earlier this year, ReCharge v2 saw the addition of subscription lifecycle events. ReCharge v2.3 is now available to all merchants, with the addition of events to track the ReCharge checkout funnel -- and segment by product and marketing channel. So what's new? Clearer segmentation of first time vs recurring orders When you add Littledata's ReCharge connection we now add three Views in Google Analytics to help segment the data: One-time orders and first-time subscriptions - A good way to track initial purchases. We automatically filter out duplicate and recurring orders from this view. All orders - All orders placed on your store, including one-time orders, first-time subscriptions, recurring orders, and prepaid orders. Raw backup - A raw data backup with no filters! This separation enables stores to easily calculate Customer Acquisition Cost (CAC) on one-time orders and first-time subscriptions. Furthermore, for all the subscriptions that started after you installed Littledata’s ReCharge connection, you can group them by subscriber (Shopify customer ID) or by marketing channel or campaign for insightful Return on Investment (ROI) calculations. Read more about how Littledata works with Views and Filters. Checkout funnel events Starting from June 2020, stores on ReCharge v2.3 can see checkout step events to match the checkout events sent from the Shopify checkout. Littledata’s checkout tracking works without the need to add Google Tag Manager or other tracking scripts to the ReCharge checkout, simplifying implementation -- and reducing the risk that 3rd party script interrupt or intercept the sensitive payment details. Excluding prepaid subscriptions Stores generating prepaid subscriptions were seeing duplicate orders when that subscription eventually got processed. In the new One-time orders and first-time subscriptions view, we filter these duplicates out automatically. Custom dimensions for LTV and more Our ReCharge customers benefit from the same user-scope custom dimensions in Google Analytics that we have for all Shopify stores, allowing you to segment and retarget audiences based on data such as their lifetime spend, date of first subscription, or number of subscription payments. Marketing attribution All of these ReCharge v2.3 updates work with our smart tech for accurate marketing attribution. What's the real ROI on your Facebook Ads? Do customers who pick higher-value subscription bundles come from a particular channel? See how Littledata fixes marketing attribution automatically for Shopify stores, with a combination of client-side (browser) and server-side tracking. [tip]Read our reviews to see what ReCharge customers are saying about Littledata! [/tip] ReCharge integration for Segment Our ReCharge integration is now fully compatible with our Shopify to Segment connection, so if you want to send Shopify and ReCharge events to Segment, we've got you covered. This is a seamless way for ReCharge stores to get revenue and customer information into Segment's hundreds of destinations. Headless Shopify tracking for ReCharge ReCharge Connection v2.3 is fully compatible with Littledata's headless tracking solution. Stores using ReCharge's new Checkout API can use Littledata's headless demo to show you how to get the same seamless customer journey from storefront, through checkout to purchasing. Littledata is the only tracking solution compatible with headless ReCharge setups, including those built by our amazing tech partners like Nacelle. ReCharge in-app analytics ReCharge has also launched a powerful in-app analytics feature available to all users. ReCharge launched Enhanced Analytics for Pro customers in 2019 to allow cohort and metric tracking. This is a powerful feature, but it’s different from what Littledata does. The most successful brands are using both tools. ReCharge’s analytics feature offers easy ways to visualize your ReCharge data in the app, while Littledata fixes sales and marketing tracking and sends that data to Segment or Google Analytics. What you can do ReCharge Enhanced Analytics Littledata + Google Analytics Littledata + Segment Look at trends in subscription sign-ups and cancellations ✔ ✔ ✔ Analyze churn rate by cohort or product ✔ ✔ * ✔ * Visualize cohort retention ✔ Fetch last-click source and medium (UTM parameters) from subscription API ✔ Analyze multi-channel marketing contributions to subscription sales ✔ ✔ ✔ Attribute recurring orders back to marketing campaigns ✔ ✔ ✔ Analyze Customer Lifetime Value including non-ReCharge spend ✔ ✔ Track charge failures by any customer attribute ✔ ✔ Track subscription cancellations or upgrades by any customer attribute ✔ ✔ Track customer updates by any customer attribute ✔ ✔ Track usage of the customer portal on our site by any customer attribute ✔ ✔ See how any ReCharge customer event connects to the pre-checkout behaviour of the user ✔ ✔ Look at cancelation rate by marketing channel ✔ ✔ ✔ Trigger transactional emails based on changes to subscriptions ** ✔ Retarget segments of ReCharge audience in common marketing destinations ✔ * Requires additional analysis in a spreadsheet** In Segment destinations such as Iterable How do you get all this? If you're already a Littledata customer, you can update to ReCharge v2 directly in the app (just login and you'll be prompted to upgrade if you haven't already). New to Littledata? We now offer a 30-day free trial on all plans, and setup only take a few minutes. If you are looking for more support, like account management or analytics training, please contact us about enterprise plans.
Updated Facebook Ad Costs to Google Analytics connection
As part of Littledata’s focus on Facebook Ads data this year, we have rebuilt our Facebook Ad Costs connection to be more dynamic and more robust. If you've been asking how to track Facebook Ads or Instagram Ads in Google Analytics -- or doing cost imports manually with Google Sheets and other tools -- your life just got a whole lot easier. Littledata's new and improved Facebook Ad Costs connection automatically imports cost and campaign data from Facebook Ads to Google Analytics, giving Shopify merchants an unbiased view of multi-channel marketing attribution, user journeys and real ROI on PPC campaigns. The Facebook Ads to Google Analytics connection now has added functionality including: Handles up to 100,000 active Facebook Ads, imported daily to Google Analytics Interprets dynamic campaign parameters Imports up to 90 days of campaign history on the first import Works for both Facebook Ads and Instagram Ads Import multiple Facebook Ad accounts to one Google Analytics property Import one Facebook Ad account to one multiple Google Analytics properties Recommends improved campaign URL parameters when none are given Of course the core functionality remains the same: easily pull campaign details and cost data into GA from your FB Ad accounts. Thank you to our customers who gave feedback to help improve the connection -- we couldn't have done it without you. The updated Facebook Ad Costs connection is available on all paid plans at no additional cost. Start a free trial today and start analyzing your campaigns more accurately.
How Google Analytics dropping Service Provider & Network Domain info affects your Shopify tracking
On February 4th, Google Analytics removed two standard dimensions from reporting – Service Provider and Network Domain – and replaced them with the dreaded (not set) label. Although there’s been cries of anguish from some analytics companies, my view is that Google has sound reasons to remove the dimensions – and there are ways around many of the limitations. Shortly after Google added the above alert to the hover tip within the Google Analytics interface, data in reports stopped reporting the information. Moving forward (and unless Google reverses course on this decision in the coming days), you’re going to start seeing (not set) under the Service Provider and Network Domain dimensions: What are Service Provider and Network Domain? Every time a visitor is tracked on your website, Google captures the IP address in order to geolocate the user (generating Country, State and City dimensions). It also does a reverse DNS lookup to see which networks this IP address is linked with. Service Provider is either the ISP (for a consumer) or the corporate network (for a business internet user). Network Domain is the main domain by which the traffic was routed (e.g. Verizon, Amazon AWS etc.) So why did Google drop them? There’s been no official announcement from Google, but it’s likely to be a combination of three factors. CCPA Storing of any California consumer’s network details is a violation of the California Consumer Protection Act (CCPA). This is much more specific than previous regulations, and as a California-headquarted company, Google wants to stay safely within the law. [tip]Here's everything Shopify merchants need to know about CCPA compliance[/tip] Fingerprinting Even if the Service Provider itself is not identifiable to any individual, it may well be used to generate a unique fingerprint for an individual user, in combination with other dimensions in Google Analytics (browser version, operating system, screen size, pages visited, etc.). Fingerprinting is user identification by covert means, and as such Google also wants to clamp down on in. Lack of usage In ten years of advising high-growth businesses on Google Analytics setup, I've never seen a good use for these reports. Google tracks what are the most common reports used, and apparently they were already flagged for deprecation based on lack of usage. How the change affects your Shopify tracking Some analytics companies (and agencies) are worried about this change for a few reasons : Reason 1: Service Provider and Network Domain dimensions helped filter out spam and bot traffic, which meant less legwork for those doing the reporting. It was easier to sniff out bounce rates that looked too high (or low) to be "real". Take the screenshot below — which Service Provider do you think is probably legitimate and which one is probably a bot/spam? In short, most analytics companies would say before this change, it was easy to uncover bots/spam, and now it's not. Reason 2: Some larger stores used Server Provider and Network Domain dimensions as a quick & easy way to filter out internal traffic from monthly reports. And unfortunately, this change has killed these dimensions' ability to filter. Reason 3: Companies such as Leadfeeder and Leadberry used the Network Domain, plus a database of which companies and people used that domain, to offer a list of sales leads who visited your site. They can mostly work around the limitations by getting their clients to push another tracking script on the site, and looking up IP address themselves — which is OK, providing your website visitors are aware you are doing this in your terms and conditions. In other words, if you're filtering your GA views by network provider, it's possible you'll see internal traffic in your reporting this month. And it might not be obvious, since it's mixed in with all of your site traffic. That is, unless you look at the GA data with better tracking. How can you work around this? For those that really need the lost dimensions there are two solutions: Use Google Tag Manager and an IP lookup service to pass network onto Google Analytics as a custom dimension. Use the recently launched ipmeta.io service to do this.* What now? For some stores using Google Analytics, this sudden change will go unnoticed and won't really impact reporting. For stores that rely on these dimensions to filter out bots/spam and internal traffic for more accurate reporting, the loss of these dimensions will have somewhat of a negative impact. Of course, we'll continue to monitor these changes (and any other surprises that Google may have in store). Don't pay too much attention to the initial outcry — every change has a solution. Littledata users can rest easy — with our Google Analytics app for Shopify, your tracking won't be impacted by these dimensions. You'll continue to see accurate data for better reporting. 🚀 *The current version of ipmeta.io is free and will remain free. The premium version will add more custom dimensions with data on the company behind the visit (if its not an ISP or spider). For example, adding dimensions such as industry codes, company size, revenue, etc. In comparison to similar services, ipmeta.io will be much (about 10x) more affordable to cater to the SMB segment.
What's new in our Shopify apps for Google Analytics and Segment
Littledata is always improving. Over the last 6 months, we’ve worked on numerous features to enhance the accuracy and availability of our ecommerce data analysis for Shopify merchants. Littledata's smart connections make it easy to get accurate data in Google Analytics or Segment. The changes below affect both of our Shopify apps (Segment and Google Analytics for Shopify), marking the biggest major update to our Shopify tracking script and server-side tracking since we released V8 last year. [tip]Check out our release notes for regular updates![/tip] Attribution for email marketing signups In order to provide enhanced email attribution, we've linked 'customer created' and 'customer updated' events back to the original source. Stores building a customer email list can now analyze where those email signups originally came from. By linking customer creation or update events on Shopify’s servers to the original campaign or referrer to the store, Littledata customers can now accurately track the source of email signups. Merchants can now also segment these signup events by whether or not the customer opted into marketing. Checkout steps Tracking checkout steps is essential for ecommerce analytics, but Shopify's native tracking is incomplete and inaccurate. Littledata's Shopify connections solve checkout tracking issues automatically. With recent updates, we’ve made the tracking of checkout steps even more reliable, coping with situations where a user is already logged in, or abandons the cart and then returns later. [note]Did you know by sending the data to Google Analytics, you can easily track your Shopify payments gateway during checkout?[/note] With the help of the full Enhanced Ecommerce specification, you can: track exactly which products follow in each step calculate the value of opportunities to improve each step [subscribe] ReCharge connection, recharged As subscription ecommerce sites continue to scale, they need even more detailed data about the user journey, especially lifecycle events. [tip]Do you trust your subscription tracking in Shopify? Learn how to get accurate tracking for repeat orders[/tip] With our new ReCharge v2 connection, subscription stores can now track the full subscription lifecycle including: subscription updates cancellations failed payments product edits customer profile / information edits [note]See the full slate of ecommerce events you can now track with ReCharge v2[/note] Geolocation of server-side events Stores need accurate information on the location of their customers to retarget campaigns around top-performing regions or cities. The extra events above, plus all the standard order data, are sent from our servers in Virginia, US. But, of course, in your analytics, you want to see them linked to the customers' real location. We now have a belt-and-braces solution for correctly geolocating customer events, passing on the browser's IP address where known, or else sending the shipping address (default customer address) to Google Analytics as a 'Geographical Criteria ID'. CartHook and Bold Cashier We've always supported other checkouts for Shopify, as we know some stores need flexibility with payment, upsell and recurring billing options. And for the most popular checkout solutions, we're always looking at ways to provide advanced tracking automatically. So in the past 6 months Littledata has launched more robust integrations with CartHook and Bold Cashier. New Google Optimize connection Google Optimize is a powerful A/B testing and personalization platform used within and beyond ecommerce. [note]Connect your Shopify store to Google Optimize to test your product pages, store content and messaging with 100% accuracy.[/note] Now, we have an out-of-the-box setup for Shopify, including an anti-flicker snippet. And coming soon... In Q1 2020, we're working on connections for Iterable's email marketing platform, plus a more consistent way of handling Segment's anonymous ID for stores which don't use Google Analytics. Is there something you're eager to see in Littledata? We're always happy to hear feature suggestions — get in touch with our team today!
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, 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'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 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 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 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... 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 (CLV) 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 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 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 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. Quick recap Customer Lifetime Value (CLV) 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 CLV 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 App + Web Google Analytics properties work with Shopify?
The short answer is no: until these new properties come out of Beta testing and support Enhanced Ecommerce reporting, we can’t recommend you use them with your Shopify store. This past July, Google brought out a public beta forcombining 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. However, we believe these are not yet suitable for use with ecommerce stores because they miss the Enhanced Ecommerce reporting that makes GA so powerful for Shopify analysis. 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 App + Web? We hope that (eventually) ecommerce events are added to that list, but it might be in a more flexible way to how GA v1 copes with events. We’ll keep watching the progress, as this ‘App + Web’ setup is going to be the future it seems.
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]
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