Cohort Analysis
Cohort Analysis - dividing clients into groups by date of attraction and analyzing their behavior over time.
Cohort Analysis - cohort analysis, dividing customers into groups (cohorts) based on a common characteristic (usually the month of first contact or purchase) and tracking their behavior over time.
Cohort analysis answers questions that “average” numbers cannot answer: - Does the LTV of cohorts change over time? January 2024 → December 2024 - Is the quality of marketing growing? (if the LTV of new cohorts grows) - When do users stop coming back on average? (day N retention) - Is there seasonality? (Are December cohorts different from June cohorts?)
In my projects, cohort analysis is the main tool for assessing the effectiveness of long-term marketing. If the average LTV of a project is 12K ₽, this doesn’t say anything. But “cohort Q1 has an LTV of 15K, Q4 - 9K” is a signal that the quality of attraction is declining.
The most common case where cohort comes to the rescue: a marketer launches a new channel, sees an excellent CPL, and reports “everything is cool.” After 3 months, it turns out that the cohort from this channel has 2x less LTV. CPL was good, but customer quality was bad.
I usually do cohort analysis in Google Sheets (for projects with up to 10K clients) or through pandas scripts (for projects with more than that).
Frequently asked questions about Cohort Analysis
What is cohort analysis?+
Why do we need cohort analysis if there is an average LTV?+
Related terms
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