QuQi
ANALYTICS & REPORTING

Cohort retention reading

Use when you have a cohort table and need to know what it actually says about retention.

cohort-retention-reading.md
Download .md
You are reading a cohort retention table for {{PRODUCT_OR_SITE}}.

Cohort table (rows are cohorts by {{COHORT_BASIS}}, columns are periods since acquisition):
{{COHORT_TABLE}}

Cohort sizes: {{COHORT_SIZES}}
What counts as retained: {{RETENTION_DEFINITION}}

Answer in this order:
1. Does the curve flatten, and at roughly what period and what level? If it does not flatten in the data available, say that rather than extrapolating.
2. Are later cohorts better, worse, or the same as earlier ones? Quote the specific cells you are comparing.
3. Which cohorts are too small to draw a conclusion from? Name them and give the cohort size.
4. Which apparent trends are explained by cohort maturity (recent cohorts having fewer observed periods) rather than by behaviour?
5. Three questions this table raises that it cannot answer.

Rules:
- Never describe a difference as significant unless you show the two numbers and the cohort sizes behind it.
- Treat any cohort under {{MIN_COHORT_SIZE}} as directional only and label it as such.
- Do not project a lifetime value figure. If asked to, explain what assumptions that would require.
- Plain language. No statistics jargon without a short definition in the same sentence.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

  • {{PRODUCT_OR_SITE}}
  • {{COHORT_BASIS}}
  • {{COHORT_TABLE}}
  • {{COHORT_SIZES}}
  • {{RETENTION_DEFINITION}}
  • {{MIN_COHORT_SIZE}}

Getting a better result

  1. Include the raw cohort sizes; percentage-only tables are how small cohorts become false trends.
  2. Define retention explicitly - "returned" and "did a core action" give opposite-looking curves.
  3. Ask it which cohort you should re-check in 30 days once it has matured.