Cohort Analysis for Subscription Retention
Structure a cohort analysis to understand and improve retention for subscription-based services.
Implement a cohort analysis that reveals retention and churn patterns by customer group, enabling preventive actions.
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Prompt objective
Implement a cohort analysis that reveals retention and churn patterns by customer group, enabling preventive actions.
Real use case
Premium Coffee Club, with 3,200 subscribers, knows the overall churn rate is 12%/month but cannot tell if it's improving or worsening. They suspect Black Friday cohorts churn faster than organic subscribers.
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Prompt
Structure a retention cohort analysis for [COMPANY NAME], a [SUBSCRIPTION TYPE] subscription service with [NUMBER] active subscribers. **1) Cohort Definition:** - By signup month (last 12 months) - Additional: by acquisition channel (organic, paid, referral) - Additional: by plan tier (basic, premium) **2) Cohort Table:** Build the table template: | Cohort | M0 | M1 | M2 | M3 | M4 | M5 | M6 | - M0 = signup month (100%) - Each cell = % retained - Highlight: where the biggest drop occurs (cliff) **3) Analysis:** - What is the "critical month" (largest drop-off)? - Is there a trend of improvement in recent cohorts? - Difference by acquisition channel - Difference by plan tier - Identified seasonality **4) Actions per Insight:** For each pattern found, suggest: - Specific preventive action - Ideal timing for intervention - Communication channel - Message/offer **5) Implementation:** - Recommended tool (Mixpanel, Amplitude, SQL + Looker Studio) - SQL query to generate the cohort table - Update frequency (weekly/monthly) - Automated dashboard **6) LTV by Cohort:** - LTV calculation by cohort and channel - Maximum acceptable CAC per channel based on LTV - Revenue projection by active cohort
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- 1Replace the key placeholders first: COMPANY NAME, SUBSCRIPTION TYPE, NUMBER.
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