Using Analytics To Identify Subscription Growth Opportunities

𝗧𝗵𝗲 𝘀𝗶𝗹𝗲𝗻𝘁 𝗺𝗲𝘁𝗿𝗶𝗰 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝘆𝗼𝘂𝗿 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆: 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗟𝗶𝗳𝗲𝘁𝗶𝗺𝗲 𝗩𝗮𝗹𝘂𝗲 (𝗖𝗟𝗩) When I talk to e-commerce founders, especially those in the subscription space, I often ask: "Do you know which of your customers brings the most value over time?" And most of the time, they don't. They track sales. They track churn. They track ad spend. But they don’t know their CLV. That’s a missed opportunity. Here’s why CLV matters: It tells you who’s actually worth retaining. Who you should be upselling. Who you shouldn’t lose. I recently worked on a demo project for a subscription-based e-commerce business. The aim was simple: → Understand the value of each customer based on historical purchase data → Segment them based on spend, retention, and behavior → Build strategies for each group Using past order data, I calculated the average revenue per user, retention rate, and order frequency. That gave me a clean CLV number per customer segment. Then I did the real work segmentation. ✔️ VIP customers who were consistent high spenders ✔️ One-time buyers who never came back ✔️ Mid-tier customers with potential to upgrade Here’s what the insights showed: 🔸 VIPs made up only 12% of customers, but drove nearly 40% of revenue 🔸 The mid-tier group had a strong engagement rate, but a low average order value 🔸 One-timers came from high-spend ads but had poor retention With this, I proposed: 💡 A targeted email flow just for VIPs, offering early access and premium tier benefits 💡 A personalized campaign to mid-tier customers to bump their order frequency 💡 Pausing cold traffic ads and doubling down on warm audience retargeting The result? A smarter roadmap. Not just “do more marketing” but where, to whom, and why. You don’t need more data. You need better direction. If you’re running a subscription or ecommerce business and want clarity on who your high-value customers are, let’s talk. This kind of analysis can save you thousands and help you focus where it really matters #CustomerLifetimeValue #EcommerceAnalytics #DataDrivenMarketing #MiniCaseStudies #RetentionStrategy #SubscriptionBusiness #DigitalMarketing #LookerStudio #FreelanceDataAnalyst

Typically, I see growth teams focusing on the biggest funnel drop, but this is usually not the biggest opportunity for growth, and unproductive. Let me explain by going deeper into a more holistic approach to managing growth funnels. Most of the analytics tools available today offer limited funnel metrics: funnel drops and completions. It’s therefore understandable that teams focus on the biggest drop. The truth is - most users won’t complete your funnel anyway. Your product probably wasn’t built for them, there’s no product-market fit, and changing their low intent is unlikely. Optimizing might keep them 1-2 more stages, but they’ll likely churn at the next. Move on! Your best opportunity lies with high-intent users who don’t complete the funnel. They have a good product-market fit and should complete. First identifying this group is crucial to understanding why some don’t succeed. How to identify High-Intent Users: Try changing up your analytics approach, put the dashboards, #correlation, and lengthy #abtesting aside for a minute. Here are a few ways to help you identify your high-intent users. Search for the signals of intent: Shorter time to complete steps, differences in onboarding questions and responses, permissions etc. Group users into segments, such as the marketing received, localizations, user properties, and behavioral groups. Calculate the likelihood of users in a sub-segment completing the funnel. Then, upon aggregating all the sub-segments together, you understand the quality and intent of the segment. Users with the most signals of intent are your high-intent users. Find high-intent users automatically. Consider leveraging a causal model. Loops, for example, automatically identifies high-intent users, by looking at the sub-segments and finding intent signals. It can otherwise be a very manual process when you are limited to funnel drop and completion metrics. How to Identify the Biggest Opportunities: Once you have identified your high-intent users, you need to size the opportunity before starting to form hypotheses. Opportunity size is based on the questions: Assuming this segment completed this step of the funnel, what would be the effect on the total funnel completion rate. Loops automatically presents you the biggest opportunities to improve your funnel. It calculates what would be the impact on the total funnel completion rate, if you improve a specific step of the funnel. Action the Insight: By identifying high-intent users and their pain points and motivations you can better shape the top of the funnel and increase completions. Armed with the confidence and impact insight of your biggest opportunity, you can turn your attention to the specific actions needed for funnel completion, as expected. Remember, most users will drop. Invest your time in identifying and understanding high-intent users. Causal inference models can help you find the answer, with less time, effort, and stress. #productledgrowth #causalml #growth

Subscription services need strong analytics to build smarter & strategically strong plans. 🚀 Subscription models aren’t just a trend anymore—they’re shaping the future of eCommerce. 🛍 But are you leveraging data & analytics sufficiently, to iteratively build your strategy, & have your customers coming back? Here’s why you should make data analytics an integral part of your business approach: 🎯 Customer Retention Isn’t a Guessing Game Many eCommerce businesses still rely on gut feeling & high level market trends when deciding what keeps their subscribers happy. What if you could make smarter, data-driven decisions instead? Here’s how: 1️⃣ Understand User Behavior at a Granular Level Accurate analytics helps you spot patterns in how your subscribers behave. 👉 For example, a fitness app found that users who completed daily workouts stayed subscribed longer. With this insight, the app focused on features that encourage consistent engagement, boosting retention. 2️⃣ Personalize the Experience Analytics isn’t just about numbers—it’s about the people behind them. By segmenting your customers based on their behavior & psychographics, you can create personalized experiences that drive loyalty. 👉 Example: Netflix tailors its show and movie recommendations at a segment of one level, making subscribers feel seen and valued, while also making their life easier! 3️⃣ Track Key Metrics Keep an eye on crucial metrics such as Churn Rate, Average Order Value (AOV), & Customer Lifetime Value (CLTV). These metrics tell you what’s working, & where you need to pivot. 👉 For instance, a music app discovered that users who created personalized playlists were less likely to churn. Now they focus on promoting playlist creation to keep users engaged. 4️⃣ Leverage Predictive Analytics Want to predict churn before it happens? Predictive analytics can highlight warning signs of disengagement so you can take action before your subscribers leave. 👉 Takeaway: With predictive analytics you can send personalized reminders, special incentives, or tips to at-risk users, keeping them engaged. 5️⃣ Test, Learn, Optimize Don’t settle for your first plan. A/B testing helps you experiment with different subscription models, pricing, & features to arrive at the best. 👉 Example: A video streaming service can test different pricing structures & tiers, & find the best pricing plans that maximize sign-ups, market share, & retention. Bottom line: Subscription analytics give you the insights you need to understand, retain, & grow your subscriber base. Embracing smart data, & analyzing it while keeping the people behind it in your mind can create more personalized, engaging, & profitable subscription model. At Appstle Inc. there are 30,000+ eCommerce businesses that hands-on use our granular analytics to make impactful data driven customer retention strategies. The analytics are an integral part of Appstle Subscriptions. Because there is no better way to profitably scale!