Retention Hypothesis Generator
Diagnose why users are churning with data-driven hypotheses, structured experiments to validate each one, and prioritized recommendations.
Help me diagnose and improve user retention for my product.
Product: {{product}} Current retention rate: {{retention}} Retention period: 30-day Known data points: {{data}} Recent changes: None
Generate:
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10 hypotheses for why users are churning, ranked by likelihood. For each:
- The hypothesis statement
- What data would confirm or refute it
- How to measure it
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Experiment design for the top 3 hypotheses:
- What to test
- Success metric
- Sample size needed
- Expected timeline
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Quick wins — 3 changes you can implement this week that typically improve retention
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Cohort analysis suggestions — How to segment users to find where retention breaks down
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Benchmark comparison — What good retention looks like for this type of product
Variables
Product description and type
Current retention rate (e.g., '25% Day-30')
Retention measurement period
Relevant metrics and data points you have
Recent product changes or launches