What is Cohort Analysis?
TL;DR
Grouping users by shared characteristics (usually acquisition date) and analyzing their behavior over time. A cohort might be "all users acquired in January", you then track how many return after one week, one month, three months. Cohort analysis reveals retention patterns and long-term engagement, not just immediate metrics. In Google Analytics 4, cohort exploration shows how acquisition groups behave over time. This matters for subscription businesses, apps, and any service with ongoing relationships. If January's cohort returns 40% after one month but February's only returns 25%, something changed, investigate what. Cohort analysis shifts focus from aggregate numbers (which mix new and returning users) to understanding customer lifecycle patterns. Essential for measuring true long-term marketing impact.
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Frequently Asked Questions About Cohort Analysis
What is cohort analysis and why does it matter?
Cohort analysis groups users by when they arrived (or another shared trait) and tracks their behavior over time. It reveals retention patterns, do customers acquired last month stick around? Essential for understanding long-term value, not just initial conversions.
How do I create cohort analysis in GA4?
Go to Explore → create a Cohort Exploration. Choose your cohort definition (usually acquisition date), the metric to track (return rate, purchases), and the time period to analyze. GA4 shows how each cohort performs over time.
What can cohort analysis tell me about my marketing?
Which acquisition sources produce customers with long-term value versus one-time buyers. If Facebook cohorts have 5% return rate but organic search cohorts have 40%, focus on organic. Cohort analysis shows true marketing ROI over time.
How is cohort analysis different from regular user metrics?
Regular metrics mix all users together. Cohort analysis isolates groups to see patterns. Your overall return rate might be flat, but cohort analysis reveals that new cohorts are returning less, a problem hidden in aggregate data.
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