Category : Google Analytics
Shopify Analytics: Everything You Need to Know
Every good business runs on good data. It doesn’t matter if you’re choosing a store design, analyzing your marketing, or setting revenue targets, it all comes back to what the data tells you. On the flip side, running on bad data can lead to your store whiffing on those big decisions. That’s where, if you’re a Shopify store, Shopify Analytics (and other analytics options) come into play. In this post, we’re going to: Break down what Shopify Analytics does Discuss Shopify Analytics’ limitations Share tools that can give you deep, accurate data and drive revenue Show you how to add powerful data tools to your ecommerce store What does Shopify Analytics do? Built within its platform, Shopify has an analytics tracker that allows you to generate data based on your store’s performance. This data includes high-level metrics like your total store sessions, number of sales, returning customers, and the average value of orders placed. [caption id="attachment_13280" align="aligncenter" width="600"] Shopify Analytics' overview dashboard gives you a snapshot of your store's high-level metrics.[/caption] Metrics like these help you get a snapshot of how visitors are interacting with your store. That way, you can pinpoint elements of your website to tweak or update based on what the data is telling you and continue to improve your metrics overall. Let’s take a closer look at some of the more popular metrics that Shopify Analytics displays within its overview dashboard: Total Sales: This metric displays the total revenue your store has generated over a specific date range minus costs like shipping and taxes. Online Store Sessions: The online store sessions metric counts the total number of customers who visited your site in a given date range, including repeat visitors. Returning Customer Rate: Returning customer rate shows the percentage of customers who have purchased from your store more than once. These customers are valuable due to their loyalty and subsequent higher lifetime value. Online Store Conversion Rate: Conversion rate tracks the number of visits that led to a purchase. Average Order Value (AOV): Average order value is calculated by taking your total order revenue and dividing it by the number of orders. The first step to using these metrics to improve your store is knowing where to find them. How to use Shopify Analytics Shopify displays data and reports about your store’s performance within its “Overview Dashboard.” The Overview Dashboard also allows you to carry out a range of basic data analyses. This includes: Comparing the value of your current sales to a previous date range Tracking how many sales you receive from a variety of marketing channels Generating your AOV Tracking your site trends over time To access this Overview Dashboard, start from your Shopify admin page and go to Analytics > Dashboards. The dashboard will display data generated from today and compare it to the day before. You can change this date range by selecting the date menu. You can also change the comparison period for this data by clicking compare to previous dates, then Apply and your data will be generated. You can then select “View report,” which gives you a more detailed analysis of your chosen metric. Be aware, however, that not all metrics will generate in your report. The metrics you can see will depend on the Shopify plan you are currently on. What analytics are in Shopify If your store uses Shopify Lite, your analytics report will show you a basic range of metrics, including the overview dashboard, finance reports, and analytics about your products. To access detailed reports like visitor behavior analysis or marketing and sales reports, you will need to upgrade to the Basic Shopify plan or higher. Shopify Analytics can generate a few other metrics beyond the most high-level ones mentioned above. Incorporating these into your data strategy is also important to maximize marketing attribution and revenue. Sales Metrics Some of the most valuable sales metrics generated through Shopify Analytics include: Total sales - the amount of revenue that was generated through your online store or your Point Of Sale if you have a physical storefront. Sales Source - this lists the sources from which your sales generated (i.e. social media channels, ads, or direct traffic.) Total orders - this metric displays the total number of orders generated through both your ecommerce store and your physical store. Customer Metrics Top products by units sold - This metric shows the items in your store which sold the most by volume, helping you identify your most popular offerings. Top site landing pages - This indentifies the most frequent landing pages on your site where visitors started a session. Returning customer rate - This gives the percentage of customers who have bought from you repeatedly in a selected time period. Shopify Behavior Reports Shopify also provides behavior reports which record customer actions on your site and allow you to: Track how your online store conversions have changed over time. Determine the top online searches for your product. Track how your product recommendations change over a given period. [caption id="attachment_13295" align="aligncenter" width="600"] Shopify Analytics' behavior reports help you drill down into how key metrics have changed over time.[/caption] All these metrics can play a key part in your overall marketing strategy and help you improve marketing attribution. But to make the best decisions for your business, you need truly accurate data — something Shopify Analytics has a spotty record with. Is Shopify Analytics good? Shopify Analytics is a good tool overall for what it is: an out-of-the-box solution for basic analytics tracking on your ecommerce store. Shopify Analytics provides the top-level metrics to give you a broad snapshot of your store’s health and customer behavior. But it lacks the detailed reports of a more robust analytics service like Google Analytics. What is Shopify analytics lacking? Unfortunately, Shopify Analytics also has a poor history when it comes to accuracy. Shopify Analytics’ tracking has shown to be both unreliable and incomplete. In fact, an analysis conducted of Shopify Analytics found that for every 100 orders tracked in Shopify Analytics, 12 go missing. There are a handful of other shortcomings those who rely on Shopify Analytics as their main data source face, as well. These include: Cross-domain tracking being setup incorrectly Server-side tracking is missing Sales data doesn't segment between first-time purchases and recurring transactions (subscriptions) Refunds not included in Google Analytics Many of Shopify Analytics’ shortcomings obscure traffic sources and disrupt attribution tracking. As an example, when customers check out on your Shopify store they’re redirected to a Shopify domain, causing the visitor’s session to end suddenly — even if they are in the process of buying an item. This affects what Shopify Analytics shows as their last click and takes away from the power of the data you’re collecting. So, is there a better way to track referrals sources, collect customer behavior metrics, and ensure accurate analytics? Yes: using a more powerful analytics tool like Google Analytics. Shopify Analytics vs. Google Analytics Google Analytics (GA) is a household name for analytics reporting across nearly every industry. In fact, it’s the world’s most popular marketing analytics platform, used by 98% of online stores. While both Shopify Analytics and GA offer unique benefits, store owners who opt for GA get more data for their dollar. We can see this first hand on a metric like sales by traffic source. [tip]Read our full ebook on why Shopify Analytics and Google Analytics don't match, plus how to fix it for your store.[/tip] Littledata looked at 180,000 orders from 10 Shopify stores, and the marketing channels in Shopify Analytics were as follows: Direct 83.5% Social 9% Search 4.5% Unknown (other websites, not social or search) 3% Email ~0.1% The Direct channel sticks out like a sore thumb, mainly because it dwarfs every other source of traffic. Compare this with the last-click attribution of sales from GA, and the difference in accuracy becomes clear: To put it simply, Shopify Analytics lacks both the accuracy and specificity of data that a tool like GA provides. How to add Google Analytics to Shopify While GA doesn’t work automatically with Shopify, it’s not difficult to set up for your store. There are multiple ways you can add Google Analytics to Shopify, and the method you choose will depend both on your technical skill and the time you have to dedicate to set up. Once you’ve created a Google Analytics property for Shopify, you can follow your preferred method to add GA to your store and start getting full, accurate data. Read on to discover which method will work best for adding GA to your store. For Universal Analytics Before 2020, Universal Analytics was the Google Analytics default. To find out if your store has Universal Analytics, check your web property ID. A universal analytics web property ID will start with ‘UA’. If you’re using Universal Analytics, the two options we’d recommend to connect GA to your Shopify store are: Using Shopify’s built-in tracking, found in-store preferences Using Littledata’s advanced Shopify to Google Analytics app For Google Analytics 4 Since late 2020, GA4 has operated as the default Google Analytics property. There are a handful of benefits to using GA4, not least of which being that it provides more thorough reports delivered within a faster timeline. Shopify does not yet support Google Analytics 4, so the built-in tracking feature is not an option here. However, you can try using GA4 and Shopify Analytics in parallel to test the performance of both and see the differences yourself. The “least hassle” option If you want to add GA to your store and you’re looking to save time and get things done correctly, implementing Littledata is likely your best bet. Littledata provides a Getting Started guide to help you add Google Analytics to your Shopify store. Once connected, the Littledata app gives you a thorough data overview and sends weekly updates as Google and Shopify add new features. [tip]Try Littledata's Google Analytics connection free for 30 days to see how it can fix your tracking while integrating with your other Shopify apps.[/tip] Using Google Analytics with Shopify Analytics GA and Shopify Analytics can be used in conjunction with one another, as each have their uses. As an example, you could use Shopify Analytics as a quick overview dashboard for store performance while relying on GA for a complete analysis of sales and marketing efforts. In depth data decisionmaking will still most likely be coming from what you see in GA, but you can still rely on Shopify Analytics to capture big picture metrics. Connecting dashboards and reporting tools The most successful modern DTC stores operate not with GA alone, but with a full data stack that helps them cover each step of the customer journey. They increase the scope of their data coverage by connecting other data dashboards and tools. ReCharge A great tool to connect to your store, especially if you offer subscriptions, is the ReCharge Connection. This connection is an advanced GA integration that helps you to track subscription ecommerce behavior. Connecting Shopify and ReCharge with Google Analytics allows you to obtain accurate sales data, including first-time orders, recurring payments, and subscription lifecycle events. It also allows you to obtain accurate marketing attribution for first-time orders, recurring payments, and subscription lifecycle events. Segment A further tool you could use to track your Shopify data is the Segment app connection, which allows you to track each customer touchpoint within your website, including the checkout steps taken by customers, sales information, and the lifetime value of a specific customer. Segment is a Customer Data Platform (CDP) that makes it easy to combine customer data with marketing data, then send that data to other platforms you use, whether that’s a data warehouse or an email marketing tool. As such, Segment isn’t just for analysis. It’s also a popular way to build new marketing audiences, such as building lookalike audiences in Facebook from your highest-spending Shopify customers. Google Ads and Facebook Ads Online advertising is a major source of traffic for modern DTC brands. To ensure your making the best decisions in your advertising strategy, you need accurate data. That’s where the Facebook Ads and Google Ads connections can play a key part in your overall analytics stack. The Facebook Ads connection fixes campaign tagging and allows for importing ad costs so you can drill down marketing attribution costs. The Google Ads connection is ideal for tracking sales expenses in reports and connecting marketing data with ecommerce performance. Wrapping it all up Now that you know exactly what Shopify Analytics can provide for you, what analytics strategy will you implement to ensure you’re making smart business decisions for your store? Using Google Analytics with your Shopify store gives you: a thorough view of the data a complete snapshot of the entire customer journey advanced metrics you need to improve attribution and boost revenue Using these, you can plan changes to your store and product offerings based on accurate data while improving your visibility by taking control of your analytics tracking. And once you’ve connected other powerful reporting tools and dashboards like Littledata’s ReCharge and Segment apps, you’ll have all the information you need to dial up your store’s growth. Take the first step by getting a free data audit when you start your 30-day free trial with Littledata. [subscribe]
Is it possible to track headless Shopify setups?
Headless commerce is not a new concept, but it's an increasingly popular solution. As larger brands continue to move to streamlined ecommerce checkouts such as Shopify and BigCommerce, they look to headless setups as a way to maintain speed or flexibility. An increasing number of those bigger DTC brands are going headless, whether that means a collection of landing pages leading directly to a Shopify checkout, or a full-on headless architecture implementation with a dynamic CMS. The question today is less whether you should consider headless in the first place (everyone is at least considering it), but more about your overall tech stack. When looking at the details of your stack (cost, functionality, maintenance, etc), it's important to consider headless pros and cons in general. But it's often even more useful to highlight specific use cases. We've previously written about how it's now possible to maintain your favorite Shopify Plus tech stack with a headless Shopify architecture. But what about your data stack? Does headless mean that your analysts will be dealing with a snow storm of anonymous IDs? Are there sacrifices to data accuracy, such as marketing attribution for recurring orders? With the right tools and plug-ins, you can still capture the complete headless journey on your headless site. In this post we look at headless Shopify tracking from several different angles and share resources for further reading. Why headless? DTC brands with a headless Shopify Plus setup now include Inkbox, Rothy's, Verishop, Allbirds, Recess, and many more. So why do merchants go headless? [caption id="attachment_10778" align="aligncenter" width="419"] Headless commerce overview from Shopify Plus[/caption] The main reason is speed, or site speed to be precise. When built the right way, modern headless sites are insanely fast. Ballsy increased conversion rates by 28% after going headless, thanks to dramatically faster page load times. (The average Shopify site sees around 4 seconds to full page load). At the same time, as our agency partner We Make Websites has noted, "extreme performance" isn't for everybody. Sometimes it can be like "the difference between buying a BMW or Audi, versus buying a Ferrari". Additional reasons for going headless include flexibility of controlling and customizing the complete frontend (with a CMS or other content framework). Of course, there are also limitations. When it comes to headless Shopify sites specifically, some trade-offs are the need to maintain multiple technologies or platforms, and the fact that Shopify's Storefront API uses GraphQL (there's currently no REST API for Storefront). Without the right tools, the other limitation is data accuracy and completeness. That can include: Marketing channels (paid channels, organic social communities, SEO) Browsing behavior (landing pages, product lists, website, mobile apps) Sales data (checkout behavior; one-off, first-time and repeat purchases) Ecommerce data from additional checkout apps (subscriptions and upsell flows) Headless tracking in Google Analytics / GTM It's no secret that Shopify and GA need some help to play well together. For every 10,000 orders processed on Shopify, 1,200 go missing in Google Analytics. For your average headless site, the stats are even worse. By default, different customer interactions with your brand — ppc campaigns, product lists, adds-to-cart, checkouts, refunds, recurring orders and subscriptions, email campaigns — are often either not tracked at all or not linked to the original user or session. In that way, you can end up with siloed data in different apps and platforms. Or even worse, everything could show up as anonymous activity or "Direct" traffic, even for repeat purchases. This isn't Las Vegas; what happens in the checkout should definitely not stay in the checkout! We have solved this problem by extending Littledata's server-side tracking to stitch sessions together from the client-side events captured on headless frontends . . . which is a rather technical way of saying that our Google Analytics app for Shopify now tracks headless sites automatically, from browsing behavior through the checkout funnel and beyond (we even capture subscriptions such as ReCharge payments!) This guarantees accurate sales and marketing data for any headless Shopify site. Check out Littledata's headless demo to see how our headless Shopify tracking works for Google Analytics. [tip]Using Google Tag Manager? Read more about our GTM / Data Layer spec.[/tip] Headless tracking in Segment As mentioned, we have offered server-side tracking for Shopify since the beginning, and automatically linked this with client-side events. Now this is available for any headless setup as well. In theory, it should be easy to send data from additional cloud sources to Segment. Each part of your headless frontend stack can just plug right in. But in practice this means manually adding a hodgepodge of client-side and server-side event tracking, and maintaining this as you scale. If you're using Segment as your CDP — or considering using Segment — rest assured that Littledata's headless tracking now fully supports Segment as a data destination. You can try to set this up yourself, but it's much easier (not to mention cheaper and more reliable) to just use our Shopify source for Segment to track your checkout. With Littledata, you can automatically send sales and marketing data from a headless Shopify site to your Segment workspace. We also recently added more flexibility around which fields to send as the userId for known customers. Check out our headless tracking demo to see how our headless Shopify tracking works for Segment. Tracking landing page builders Not every headless site is using a Content Management System (CMS). For those who do, Contentful is the most popular with straightforward headless Shopify builds. There are also "soft headless" sites that rely on a series of landing pages or similar flows, which then lead to the main Shopify site or even directly to the checkout. In the first case, where the landing pages are truly landing pages and lead to your main site, you can use the default settings in Littledata's Shopify app and generally do not need to take the headless install route. For cases where landing pages go directly to the checkout, see the headless tracking demo linked above. We also need to take landing pages seriously. It can actually be just as difficult to get complete marketing attribution or even to link sessions together and track the purchases customers make after landing on one of these pages. To solve this problem, Littledata's automated tracking now tracks landing pages as "additional apps" on top of our main Shopify connections for Segment and Google Analytics. As long as the Littledata script is loading on those landing pages, everything will link together automatically. We have tested this functionality with three of the most popular landing page builders for Shopify stores: Shogun Pages Zipify Pages Gem Pages Drop us a line if you have any questions about additional apps or special requests for landing page tracking. Preferred headless tech partner: Nacelle Our merchants looking for a complete headless Shopify solution often choose our tech partner Nacelle. Nacelle powers storefronts that stand out from the competition, offering headless website builds backed by a robust data stack. Focused on Progressive Web App (PWA) technology, they build lightning-fast, responsive sites for modern DTC brands. We've been working closely with Nacelle on tracking setup for some initial merchants (many brands you would recognize...) and are excited to now be able to offer headless tracking for any Nacelle customer. Read our shared ebook on going headless Explore our headless tracking demo Check out our NPM package for grabbing client IDs [or forward this to your developer!] Littledata's Nacelle tracking works automatically once you follow a few simple setup steps. Plus, the data can be sent to Segment, Google Analytics, or any connected data warehouse or reporting tool. [subscribe heading="Learn more about headless tracking" button_text="book a demo" button_link="https://www.littledata.io/app/get-free-trial"]
Shopify Analytics vs. Google Analytics: Why don't they match?
If you're a Shopify store owner using both Shopify analytics and Google Analytics, you're probably familiar with the often large discrepancies between the two tracking systems. What you might not know is that this happens in part because Shopify's default analytics misses tracking on 12 out of every 100 orders. That leaves you unaware of your true sales performance and marketing attribution, and what actions your customers are taking at key touchpoints along their buying journey. Layering expensive data dashboards and connectors on top of this, as many stores often do, just compounds the problem and leads to more wasted marketing spend. It's never a good idea to make decisions based on bad data. An insider's guide to fixing your Shopify store analytics The first step to fixing your Shopify tracking is understanding where it fails. You know the data is missing, but what's going on behind the scenes to cause it? And is there a better way? Fortunately, there is. Our free guide on why Google Analytics doesn't match Shopify analytics dives into: The main reasons why transactions go missing in GA How a data mismatch affects your bottom line A comparison of different tracking methods What you can do to fix Shopify analytics Read the ebook >>> Adding Google Analytics to Shopify If you're not already using Google Analytics with your Shopify store, getting it set up should be your first step toward improved data accuracy. Though Shopify does have a default GA integration, it misses tracking many key metrics. We have a full walkthrough on setting up Google Analytics on your Shopify store, which covers what to look out for after you've set up GA as well. Using the methods in our guide will help you ensure you get a full and accurate picture of your data in GA. For a fast way to connect them automatically, try out Littledata's GA to Shopify connection for free. The trial allows you to get an accurate snapshot of your key metrics, and you'll still own that data in GA whether you continue using our advanced data connections or not. [subscribe]
Littledata announces Google Analytics integration for BigCommerce
We are excited to announce that Littledata will soon be available to BigCommerce merchants. Like our popular Shopify app for Google Analytics, our BigCommerce connection for Google Analytics will ensure accurate sales and marketing data across the user journey. BigCommerce will be Littledata's first ecommerce platform integration outside of Shopify. With brands like Superdry, Skull Candy and 5-hour Energy now on BigCommerce, the timing couldn't be better. Read on to see what we've been working on, the benefits for ecommerce marketers and data scientists, and how to get early access. Why BigCommerce? Founded in 2009, BigCommerce has seen remarkable growth over the last couple of years, especially in North America. A year ago when they went public, BigCommerce was already powering over 60,000 online stores in 120 countries. They have focused on additional sales channels such as Amazon since early on, and recently announced a major partnership with Amazon for fulfillment, and another with Mercado Libre for extension into the Latin American market. Everyone needs accurate data to make data-driven decisions. We're excited to be extending our ecommerce data platform to work with BigCommerce. We chose BC because it's a great fit with our customer base which are typically successful DTC brands looking to scale faster and smarter. In addition, there's a growing amount of overlap with our technology partners and agency partners around the world. Advanced Google Analytics integration Accurate data is essential for ecommerce growth, but ecommerce tracking is notoriously difficult. As the top data platform specifically designed for ecommerce, our upcoming release in the BigCommerce app store will change the game. Littledata's advanced Google Analytics connector for BigCommerce stores will give you accurate data, automatically. Whether you are an ecommerce manager looking for accurate data to drive decision making, or a CTO or web developer looking for a seamless tracking solution, we're here to make your job easier. Benefits include: Complete sales dataAccurate marketing attributionCheckout funnel trackingOwn the data in Google Analytics As with all Littledata connections, Littledata's BigCommerce Google Analytics integration has the added benefit of enabling accurate data in any connected BI dashboard or reporting tool. What's more, the integration will work with custom themes and headless BigCommerce setups! Subscription analytics Tracking recurring orders is one of Littledata's key benefits and one of the most-cited features in our five-star reviews. We are especially excited about extending our subscription analytics to BC stores, enabling accurate data about recurring transactions and customer lifetime value (LTV). Our first subscription analytics integration will be with our longtime integration partner ReCharge, who also recently launched on BigCommerce. Sign up here for early access. How to get early access Are you doing at least $1M in annual online revenue? If so, you can apply for early access to Littledata's BigCommerce integration for Google Analytics. Early adopters will not only get access to our data connector - they will also have a key role to play in shaping additional features and integrations. Note: if you are interested in connecting BigCommerce with GA4 (the newest version of Google Analytics), reach out to us about our beta program.
How to add Google Analytics to Shopify
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Learn more about your ecommerce customers' behavior with advanced checkout funnel analysis [VIDEO]
Ecommerce analytics are tricky to begin with. Add tracking your subscription services on top of that and you’re dealing with a whole other animal! Do you use Google Analytics to report on your Shopify store’s one-off purchases AND recurring orders? Check out our video on Littledata’s advanced checkout funnel analysis to find out how we’ve made subscription analytics easy. https://youtu.be/EU3Cj2Z6AII Traditional ecommerce stores typically track one checkout funnel per property. The benefit is that this makes it easy to analyze the drop-off at each point. But, if you have multiple checkouts to track one-time orders and subscription purchases, important insights might go unnoticed when GA aggregates your data. Littledata automatically differentiates between your checkout funnels to show whether they’re subscription or one-time purchases. That way you know exactly what each funnel’s checkout completion rate is for different order types. This gives you the power to tailor your remarketing strategies for specific checkouts or products, further increasing your ads’ relevance to possible customers. Note: Do you trust your subscription tracking? Get accurate subscription tracking with the ultimate ReCharge guide for Shopify Littledata integrates with the top subscription ecommerce apps—including ReCharge Payments, Bold Commerce, and Ordergroove—and automatically tracks both Shopify and subscription checkouts. “Littledata is a must-have if you’re running Recharge and Shopify; it helped us figure out what channels were getting us our future subscribers and what helped convert them.” —Better Way Health To access your checkout reports in Google Analytics, go to your ecommerce analysis reports. From there, you can view your checkout behavior reports to get a general understanding of when users are dropping off throughout the checkout process. Find out how to segment your data between Shopify and subscription checkouts to measure the exact drop-off rate at each stage of the checkout process for each checkout funnel in our latest learning video. Capture data at every turn In addition to tracking your checkout funnel completion rates for subscription checkouts, Littledata tracks crucial sales and marketing metrics, so you can: Get accurate marketing attribution data for subscription revenue, including first-time payments and recurring chargesUse custom dimensions to measure customer lifetime value (LTV)Track performance by payment source, subscription plan type, and product categoryView complete sales and marketing data with combined server-side and client-side trackingMake better, informed decisions for your Shopify store Resources Watch a quick demo video on how Littledata worksFind out how to calculate LTV with Google AnalyticsDownload the ultimate guide to subscription trackingCheck out our ReCharge FAQSubscribe to our YouTube Channel for more videos about analytics
Two ways to calculate customer lifetime value for ecommerce using Google Analytics data
Many of our customers come to us with a similar question: "how do I measure ecommerce lifetime value (LTV)?" The latest episode in our Learning Videos series shows you how to do just that for both your one-off purchasers and subscription customers. Our step-by-step tutorial covers two methods of calculating customer LTV using your Google Analytics (GA) data. You'll get to know Littledata’s custom dimensions in GA and learn how to visualize your calculations in Google Data Studio. During installation, Littledata automatically creates several custom dimensions in your connected Google Analytics property. These custom dimensions include: Lifetime Revenue, the sum total a customer has spent in your Shopify store (including one-time purchases and subscription orders) Shopify Customer ID, the unique identifier Shopify assigns to each customer Last Transaction Date Payment Gateway Purchase Count They offer better data to help you understand your customers' buying behavior, then calculate and visualize their LTV. To kick things off, you'll first need to export your data from GA to Google Sheets or another spreadsheet tool via CSV. Once you’ve enabled the GA add-on in Google Sheets, you're ready to get started. Method 1: Calculate LTV by Lifetime Revenue, Shopify Customer ID, and Transaction Count In the first method of calculating lifetime value, we’ll use Transactions as the metric. The dimensions we'll use—Shopify Customer ID and Lifetime Revenue—correspond with ga:dimension5 and ga:dimension3, respectively. Use the image below as a guide to set up your report: Next, set your Metrics Reference as Transactions and your Dimensions Reference as Custom Dimensions. After you run the report, Google Sheets should look something like this: Finally, use Google Sheets' built-in functions to calculate the average or median LTV of your customers. Method 2: Calculate LTV by Source/Medium, Transaction ID, Shopify Customer ID, and Transaction Revenue This second LTV calculation method helps you track which marketing channels bring in your most valuable customers: the ones who spend the most over time. In this method, use Transaction Revenue as the metric and Source/Medium, Transaction ID, and Shopify Customer ID as the metrics. These correspond with ga:sourceMedium, ga:transactionId, and ga:dimension1 respectively. This method requires the widest date range possible to capture the most transactional data possible—preferably since you started using Littledata. Before running the report, your Google Sheet should appear as follows: After exporting your data, your result will look like this—a list of transactions with source/medium and revenue data: Next, select all the data in your report to create a pivot table, aggregating by source/medium per customer. The result will reveal the total revenue per customer, per source. After completing the pivot table, you're ready to visualize your data in Data Studio. Build Reports in Google Data Studio Google Data Studio is one of our recommended reporting tools for ecommerce sites. Why? Because it's free, powerful, and works really well with Google Analytics. The first step in visualizing your data is to import your data into Google Data Studio by setting Google Sheets as your source. To do this, select your Google Sheets file followed by the pivot table you created in the previous method, and add it to your report in Google Data Studio. Change the data source by setting the aggregation to median so results yield the median lifetime revenue per traffic source. Your report dimension should be set to ga:sourceMedium and your metrics should be set to ga:transactionrevenue and ga:dimension1. Modify Shopify Customer ID from sum to count distinct to reveal the total unique customer IDs, which we'll use to sort our data. Sort by Shopify Customer ID to see the traffic source that brings the most customers to your site. The resulting report shows you the median lifetime revenue per traffic source, sorted by the total customers per source. References Quick Tips for Subscription Stores Using Custom Dimensions in GA 3 Deep Dives into Customer Lifetime Value for Ecommerce Sites LTV from GA vs LTV provided by Littledata How to Calculate Customer Lifetime Value in GA for Shopify Stores Custom Dimensions for Calculating Customer Lifetime Value Subscription Analytics Does Littledata work with my ecommerce reporting tool?
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