Cohort and Retention Analysis for Recurring Revenue Businesses
Generates a complete cohort analysis report to understand retention patterns and identify critical churn windows.
Develop a detailed cohort analysis that reveals behavioral patterns over time, identifies the critical churn window, and quantifies the financial impact of retention.
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Prompt objective
Develop a detailed cohort analysis that reveals behavioral patterns over time, identifies the critical churn window, and quantifies the financial impact of retention.
Real use case
The meditation app ZenMind, with 28,000 downloads per month and a $4 monthly subscription, has a 65% churn rate in the first month but doesn't know if this is normal for the industry, when exactly users drop off, or what differentiates those who stay from those who leave.
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Prompt
Develop a complete cohort analysis for [COMPANY NAME], a [BUSINESS TYPE] with [NUMBER] customers and monthly recurring revenue of $[AMOUNT].\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Required Data:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Customer table with acquisition date\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Transaction/event table with timestamps\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Analysis period: last [NUMBER] months\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Desired segments: [ACQUISITION CHANNEL / PLAN / REGION]\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Part 1 — Cohort Retention Matrix:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\nTable (example structure):\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n| Cohort | Month 0 | Month 1 | Month 2 | Month 3 | ... | Month 12 |\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n|--------|---------|---------|---------|---------|-----|----------|\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n| Jan/26 | 100% | [X%] | [X%] | [X%] | ... | [X%] |\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n| Feb/26 | 100% | [X%] | [X%] | | | |\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- SQL query to generate the matrix (with CTEs and window functions)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Python/Pandas version for supplementary analysis\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Visual heatmap with color scale (green = high retention)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Part 2 — Pattern Analysis:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Average retention curve (all cohorts)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Identification of the \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
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