Cohort analysis groups customers by shared characteristics (usually acquisition date) to track behaviour over time. It reveals trends hidden in aggregate data.

How Cohort Analysis Works

Group customers by when they first purchased, then track metrics (repeat rate, revenue, retention) for each cohort over subsequent periods.

View Example

January cohort: 1,000 new customers
Month 1: 15% repurchased
Month 2: 8% repurchased
Month 3: 5% repurchased

Compare to February cohort to see if retention is improving.

Why Cohort Analysis Matters

  • Shows true customer behaviour over time
  • Identifies if retention is improving or declining
  • Measures impact of changes (did new onboarding help?)
  • Reveals customer quality by acquisition source

Common Cohort Metrics

  • Retention rate by period
  • Cumulative revenue per customer
  • Repeat purchase rate
  • Average order value over time

Tools for Cohort Analysis

Google Analytics 4 has basic cohorts. Shopify analytics, Klaviyo, and dedicated tools like Lifetimely provide deeper cohort insights for ecommerce.