Cohort Analysis
Analyzing groups of customers who share a common characteristic to understand behavior patterns over time.
Definition
Cohort analysis groups customers by shared characteristics (signup month, acquisition channel, plan type) and tracks their behavior over time. Instead of looking at all customers together, you compare how different cohorts perform. This reveals patterns hidden in aggregate data and helps measure the true impact of changes.
Why It Matters
Aggregate metrics lie. Your overall retention might look stable while recent cohorts churn faster. Cohort analysis reveals these trends. For email, it helps you understand whether onboarding improvements actually work, which acquisition sources bring quality customers, and how email program changes affect long-term outcomes.
How It Works
Define cohorts based on relevant characteristics (signup date, first plan, signup source). Track key metrics (activation, retention, revenue) over time for each cohort. Compare cohorts to see if newer ones perform better or worse. Use findings to optimize acquisition, onboarding, and retention strategies.
Best Practices
- 1Create cohorts based on characteristics that matter to your business
- 2Track cohorts long enough to see meaningful retention patterns
- 3Compare cohorts to measure impact of product and email changes
- 4Use cohort insights to forecast future performance
- 5Segment email analysis by cohort for accurate attribution
- 6Investigate when cohort performance suddenly changes
- 7Build cohort views into regular reporting
Campaign Analytics
Analyze email performance by customer cohort. See how email engagement varies across signup dates, acquisition sources, and plan types.
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