Explore Cohort Analysis using your Stripe data
Cohort Analysis with Stripe Data
Cohort analysis transforms how Stripe users understand customer behavior by tracking groups of customers over time based on when they first made a purchase or subscription. With Stripe’s rich transaction data—including payment dates, amounts, subscription cycles, and customer IDs—you can identify patterns in customer retention, revenue growth, and churn that directly impact your business strategy. This analysis helps inform critical decisions around pricing strategies, product development, marketing spend allocation, and customer success initiatives.
However, performing meaningful cohort analysis manually is extremely challenging. Spreadsheets quickly become unwieldy when exploring different cohort definitions (monthly vs. weekly, subscription vs. one-time customers), time periods, and segmentation criteria. Formula errors are common and costly, while maintaining accurate calculations as new data flows in becomes a full-time job. Stripe’s built-in reporting tools, while useful for basic metrics, offer rigid outputs that can’t accommodate custom cohort definitions or answer follow-up questions like “How do cohorts from different marketing channels compare?” or “What’s the impact of pricing changes on specific customer segments?”
Count eliminates these pain points by automatically connecting to your Stripe data and enabling flexible cohort analysis examples through an intuitive interface. Whether you need a quick cohort analysis tutorial or want to dive deep into complex customer behavior patterns, Count makes it simple to explore every angle without the manual overhead.
Questions You Can Answer
What’s the retention rate for customers who made their first purchase in January 2024?
This cohort analysis example shows how many customers from a specific acquisition month remain active over time, helping you understand the long-term value of your customer acquisition efforts.
How do subscription retention rates compare between monthly and annual billing cycles?
By segmenting cohorts based on Stripe’s billing interval data, you can identify which pricing models drive better customer loyalty and inform your subscription strategy.
What’s the revenue retention pattern for customers acquired through different payment methods?
This analysis reveals whether customers paying via card, bank transfer, or digital wallets show different spending behaviors over time, optimizing your payment flow priorities.
Show me cohort analysis for customers by their initial subscription plan tier.
Comparing retention across Stripe’s product tiers helps identify which plans create the stickiest customers and where you might have pricing or value proposition issues.
How does customer lifetime value differ between cohorts from high-value vs. low-value initial transactions?
This sophisticated cohort analysis tutorial approach segments customers by their first transaction amount from Stripe data, revealing whether big spenders continue spending more over time.
Compare retention rates for B2B vs. B2C customers based on transaction patterns and metadata.
Using Stripe’s customer metadata and transaction frequency, this cross-cutting analysis identifies behavioral differences between business segments to tailor retention strategies.
How Count Does This
Count’s AI agent delivers bespoke cohort analysis tailored to your exact Stripe question — no rigid templates. Whether you’re analyzing subscription retention or purchase frequency cohorts, Count writes custom SQL logic specific to your business model and timeframes.
Running hundreds of queries in seconds, Count automatically explores multiple cohort dimensions simultaneously. For example, it might analyze monthly acquisition cohorts while also examining cohorts by subscription plan, customer segment, and geographic region — uncovering retention patterns you’d never discover manually.
Count handles messy Stripe data seamlessly, automatically cleaning common issues like duplicate transactions, test payments, or incomplete customer records. This ensures your cohort analysis example reflects genuine customer behavior without manual data preparation.
With transparent methodology, Count shows exactly how it defined your cohorts, calculated retention rates, and handled edge cases like refunds or plan changes. Every transformation is visible and verifiable.
Count delivers presentation-ready cohort analysis complete with retention tables, survival curves, and actionable insights — perfect for executive reporting or team discussions. The collaborative platform lets your team explore cohort trends together, asking follow-up questions like “What drives the retention difference between annual and monthly subscribers?”
For multi-source analysis, Count can combine Stripe cohorts with customer support data, product usage metrics, or marketing attribution data, creating comprehensive retention insights that span your entire customer journey.