Cohort Analysis
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Instead of looking at averages, users are grouped by their "birth date" (registration time), and the behavior changes of each group are observed in the subsequent 1st week, 1st month, etc.
SCAFFOLDING EFFECT
Reduce cognitive load
- Expose illusions: If the total number of users is increasing, but the "first-month retention rate" of new users is declining month by month, it indicates that the product is "getting worse." This fatal signal can only be seen through cohort analysis.
Anchor fast decisions
Cohort analysis groups users by the same time period or experience, tracking the retention and behavior of each group over time.
MINIMUM ACTION
In progress 0/3Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Cohort_analysisverified
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