Analytics Updated 2026-07-04

Cohort Analysis

Cohort Analysis is the segmentation of users into groups based on shared characteristics or behaviors, then tracking how each group performs over time. It reveals whether user quality, retention, or value varies by acquisition source or timing.

Definition

A cohort is a group of users who share a defining characteristic, such as acquisition date, traffic source, geography, or device type. Analytics platforms track cohorts separately over subsequent periods to measure retention, engagement, and lifetime value. Cohort retention tables show what percentage of each cohort returns after 1 day, 7 days, or 30 days.

Cohort analysis reveals which user segments are most valuable and which churn quickly. If users acquired via one channel have higher retention than another, that informs marketing spend allocation. Cohort analysis can also test feature impact by comparing users who accessed a feature versus those who did not.

Why it matters for AI visibility

Comparing cohorts of users who arrive via AI assistants to those arriving via traditional search reveals whether AI-referred users have different lifetime value or retention. If AI-referred users have lower retention, it may indicate misalignment between AI preview and full content. Understanding cohort behavior by AI source helps teams optimize content for AI visitors.

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