Prompt that checks whether cohorts silently drop leavers and skew claims. Paste it into an AI tool of your choice, which then spots survivorship bias in cohorts.
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What is compared?
retention
revenue per cohort
activity duration
feature use
mixed
Built how?
start month
first purchase
signup
campaign
unclear
Judged how?
after 30 days
after 90 days
only currently active
vs prior period
mixed
Your prompt
Help me check whether my cohort analysis is skewed by survivorship bias.
Analysis: [Analysis]
Cohort: [Cohort]
Comparison: [Comparison]
Steps: 1. Read the cohort definition, who enters when and who leaves. 2. Check whether dropouts silently disappear in later periods. 3. Compare metrics including dropouts with metrics on actives only. 4. Propose a fair base set and clear exclusion rules. 5. Flag claims that rest only on survivors. 6. Write a careful wording for the report.
Output: cohort definition, bias finding, fair alternative, rewording.
Take particular care to keep the starting set and show dropouts next to success.
Before you answer, check: Are all instructions met? If key information is missing or a placeholder in square brackets is still in the text, ask instead of guessing. Mark assumptions as assumptions.
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This is an instruction for an AI, not the result itself.
Prompt that explains a cohort table, compares cohorts at the same age and separates chance differences from real trends.
Prompt · Intermediate · about 8 min
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