One of the challenges subscription businesses face is differentiating between order types.  The problem For Shopify merchants, offering single purchase options complicates things even more — with single purchase options, order data will show in two places (Shopify and ReCharge). This leads to a major disconnect between user behaviour and orders, unable to leverage the full potential of Google Analytics.  At this point, you probably have a multitude of “known unknowns”, such as: Which traffic sources drive more first time subscription orders? What's my conversion rate on one time purchases? What's my average customer lifetime value (CLV or LTV)? Do my one time purchasers end up converting to subscribers? What's my churn rate month over month? [tip]Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.[/tip] The solution Bridging the gap with Littledata Littledata helps bridge different platforms by linking orders betweenShopify, ReCharge and Google Analytics.  [subscribe] Differentiating between order types With Littledata’s improved tracker, merchants can differentiate between order types. For this, we use the Affiliation dimension.  In the Google Analytics report, it will look something like this:  Right away, this information answers a few questions: What is the distribution between my order types? Are my recurring subscription orders growing month over month? Is the average order value (AOV) of subscribers higher than that of one time purchasers?  Both of these can be viewed in this custom report. What traffic sources drive the most sales?  One of the questions our team is asked most often is what sources of traffic drive the most subscription orders?  Short answer: the Affiliation dimension can be used as a secondary dimension in the source/medium reports, or use this custom report.  By using filters to single out an order type, you can easily determine what traffic sources drive the most first time subscription orders. Segment more Segmentation opens up new ways to look at the data as well. Creating two segments for one time purchases and first subscription purchases, you can see how the two types of purchases differ.  Look for behavioural differences like:  Do One Time purchasers AOV higher or lower compared to First Subscription orders? Are users testing the product first and then committing to a subscription?  Littledata custom dimensions Google Analytics custom dimensions are an excellent way to expand your data collection and reporting power. With our Shopify app, Littledata adds these custom dimensions: Littledata - Shopify Customer ID Littledata - Last Transaction Date Littledata - Purchase Count Littledata - Lifetime Revenue Littledata - Payment Gateway With the help of these custom dimensions, we can answer the following questions:  What's my median customer lifetime value (CLV)? How many purchases do customers make in their lifetime? What's my churn rate month over month? Since these are custom dimensions, they cannot be aggregated on Google Analytics, meaning the data will need to be displayed using a different method. For this, we’ll use Google Sheets with the Google Analytics add-on to query the data and pivot tables.  Step 1 - Query all the data you need Metrics Avg. Order Value Revenue Dimensions Littledata - Shopify Customer ID  Littledata - Lifetime Revenue Littledata - Purchase Count Affiliation - to differentiate between the order types.  It should look something like this:  In this case, the custom dimensions are at index 4, 6 and 8. This may differ depending on your setup.  Step 2 - Run the report After you run the report, this will create another sheet in your document. It will look something like this:  Step 3 - Create a pivot table  In the rows section, add the Affiliation dimension to differentiate between the order types.  Shopify will mean a one time purchase (normal purchase). The other two order types are the first subscription order and recurring order.  In the values area, add:  The user IDs summarised by countunique The customer lifetime value summarised by median so that we have the median LTV. We use median over average so that this number is not influenced too much by the outliers.  Purchase count summarised by median.  Average order value  The end result should look something like this:  Step 4 - Interpret the data In this report, we can instantly draw some conclusions:  Most customers make single purchases rather than subscribing  Subscription first order median purchase is 2, so this means users have purchased in the past before committing to a subscription Subscribers purchase 8 times (median value), with a median CLV is around $500.  How to take this further Since we know most customers order at least once before committing to a subscription, we can calculate the average number of days between a single purchase and a first subscription purchase.  When you’re armed with that type of information, you can adjust your email marketing flows accordingly and adjust your remarketing campaigns to shorten or lengthen the number of days your ads show to leads.  With the help of the Customer IDs, we can also calculate the month over month churn rate (we’ll get to that in a follow-up post). It's your turn now How do you use these additional events and custom dimensions in your segmentation?  What was your biggest insight using these events and custom dimensions?  How did it influence your marketing campaigns? Share your experience (and current approach with GA) via the live chat in the bottom corner. I'm curious about the different ways you make use of these additional data points! In the meantime, our team is at the ChargeXSummit in Santa Monica sharing all about our ReCharge connection for subscription-based stores. [note]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/note]

It's no secret that Google Analytics (GA) is the bedrock of modern analytics. For analytics experts in all verticals — not only ecommerce — Google Analytics is the primary tool for setting goals, tracking results, ecommerce benchmarking and optimising campaigns for peak performance. [note]Do you really need a Google Analytics expert to help with your Shopify data?[/note] But GA is no walk in the park. It's a complex platform with a robust dashboard, unique features like Enhanced Ecommerce and dozens of helpful tracking features for merchants big and small. Because GA can be a learning curve for less experienced users, many Shopify merchants opt to work with a Google Analytics consultant or Google Analytics consulting group to navigate the waters of GA and optimise their product campaigns. [subscribe heading="Get top Google Analytics consultants for Shopify" background_color="green" button_text="get started" button_link="https://www.littledata.io/app/enterprise"] But before you go hunting for Google Analytics consultants for your store, make sure they check all the boxes: Can they code in GA? From UTM parameters to more complex bug fixes, a respectable GA consultant should be comfortable with code. While troubleshooting and custom implementations are the most common calls for coding experience, Google Analytics experts should be able to code in GA with no problems. Are they comfortable segmenting data? As the old adage goes, averages always lie. In other words, insights from data reports go beyond the average numbers that GA shows. To better understand the data, an experienced GA consultant should know how to segment the data. If you hire a GA consultant who shows you plain GA exports exactly as Google shows it to the user, he/she is providing your store no value. Data without a plan of action is just a collection of reported numbers — nothing more. Do they deliver insights, not reports? Not every Shopify store owner understands bounce rates, but most understand that there are shoppers who find their way to an online store, don't take any on-site action, and leave the site right away. In other words, a good Google Analytics consultant should not be interested in exports from GA, but insights. A reliable Google Analytics expert should be able to extrapolate data from GA, explain to store owners what it means and communicate the impact for ecommerce managers. We've seen that many merchants are not interested in complex GA data, and you probably don't have time to read comprehensive reports — what you probably need is guidance, translation and plain english to turn data into actionable insights. Why Shopify store owners choose enterprise plans There's no getting around it — highly effective (and affordable) Google Analytics consultants are difficult to come by. Luckily, there's a better way for merchants to track data they can trust and build their strategy around reliable reporting from GA. Littledata's enterprise plans (which are also optimised for Shopify Plus) offer all the benefits of a personal Google Analytics consultant along with better insights, the experience to address complex issues, and dashboards to visualise the KPIs that matter to your store. [subscribe heading="Try Littledata free for 30 days" background_color="grey" button_text="start my free trial"] 1) Start with an audit, sail to higher revenue We first got started as a next-gen audit tool, so it's no accident that enterprise plans begin with an audit review.   During the audit, we review your store's data gaps and tracking issues keeping you from data you can trust for actionable insights. Our audits extend across marketing channels, mobile app performance and user behaviour on your storefront and product pages.   Our Google Analytics-certified account managers ensure a smooth process through strategy, implementation and optimisation. 2) Define project goals If your store requires more than just ongoing audit fixes, we work with your team to define custom goals for the products you really want to push.   This can be something as standard as setting up Enhanced Ecommerce in Google Analytics or as complex as developing a multi-site dashboard to analyse average customer revenue by location. Either way, enterprise plans offer complete online support for peace of mind.   3) Decision-making power throughout the process Unlike some account managers, our team is hands-on from initial GA set up to implementation.  You'll be looped in throughout the entire process with an in-app, custom dashboard that updates real-time.   If you have GA questions, enterprise customers can also communicate with our account team through Slack and Trello.   4) Always getting better Our GA team monitors your data collection for accuracy and depth before creating custom recommendations.   These include step-by-step reports showing how to use your new analytics setup, how to maximise automated reporting and how to improve your marketing ROI and drive more revenue through fixed attribution. Take the first step Beyond deep experience with Shopify and Shopify Plus, we have a number of seamless connections with everyday tools like Facebook Ads and Google Ads for accurate marketing attribution, plus full support for Google Tag Manager setup, etc. Take the first step into our custom enterprise plans. 🚀