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Using Cohort Analysis to Deeply Understand Your Customers

While overall metrics like MRR, churn rates, and LTV provide a high-level view into the health of your subscription business, cohort analysis allows you to slice your customer data in a way that surfaces insights that can drastically improve products, retention, and growth strategies.


Cohort analysis tracks the behavior and metrics of related groups of customers over time based on shared characteristics like:

  • Acquisition period (month/year they became a customer)

  • Pricing plan or subscription type

  • Acquisition channel or campaign

  • Firmographic data like company size or industry

  • Usage behavior or in-app actions taken


Rather than looking at your entire customer base as one, single group, cohort analysis separates them into related segments. This shows how different segments behave and perform.


For example, looking at your overall customer churn rate may show 5% monthly churn, which seems reasonable. But a cohort analysis could reveal:

  • Customers from your quarterly promotion have 15% churn after 3 months

  • Enterprise customers on your annual plan have <1% churn

  • Customers who adopted a new feature have 30% lower churn


These types of insights allow you to focus on successful segments, optimize offerings that underperform, identify red flags, and continually improve customer experiences.


There are many ways to slice cohorts, but some of the most common cohort analyses include:


Acquisition Cohorts

Group customers by the month/year they were acquired to analyze long-term retention, lifetime value, and revenue contribution over time. This will show seasonality trends and which acquisition channels/campaigns yield the best long-term customers.


Pricing Plan Cohorts

Separate by pricing level or subscription type to compare metrics like churn rates, expansion revenue, and LTV across different plans. This can guide pricing/packaging and identify upside opportunities.


Behavioral Cohorts

Group by product usage behaviors like adopting a new feature or achieving certain milestones. This allows you to quantify the impact of product experiences on key metrics and prioritize improvements.


While implementing cohort analysis has an upfront investment, the payoff in actionable insights can be immense. By a



nalyzing the right segments, you can make data-informed decisions to optimize every aspect of your customer lifecycle rather than operating with averages.

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