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Cohort Analysis

Quick Definition

Grouping users by signup date and tracking their behavior over time to reveal trends and product improvements.


What is Cohort Analysis?

Cohort analysis groups users by a shared characteristic (usually signup date) and tracks their behavior over time. Instead of looking at all users together, you compare how the January cohort behaves vs the February cohort vs the March cohort.

This reveals whether your product is improving. If each new cohort retains better than the last, you're building a better product.

Why Cohort Analysis Matters

Aggregate metrics hide trends. Your overall retention might look flat, but cohort analysis might reveal that new cohorts retain much better while old cohorts are churning. Or vice versa.

Cohort analysis answers questions like: Are we getting better at retaining customers? Did that product change help? Which acquisition channels bring the best customers?

Running Cohort Analysis

Group users by signup week or month. Track retention, revenue, engagement, or any key metric over time. Visualize as a cohort table or retention curve. Compare cohorts to identify trends and the impact of changes.

Formula

Cohort Retention = Customers Remaining ÷ Original Cohort Size × 100

Track by time period (month, quarter) and segment (source, plan, size)

Example

Your SaaS company tracks January cohort retention:

  • Month 0: 100 customers (100%)
  • Month 1: 85 customers (85%)
  • Month 3: 70 customers (70%)
  • Month 6: 55 customers (55%)
  • Month 12: 45 customers (45%)

The January cohort retains 45% after one year. Compare against February and March cohorts to see if retention is improving.

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