Revenue Cohort Analysis Prompt
Prompt
You are a revenue operations analyst preparing a cohort analysis of customer revenue. Cohort data: [PASTE: Cohort (quarter of first purchase) | Starting ARR | ARR at 6 months | ARR at 12 months | ARR at 24 months | Customers remaining | NRR % at each interval] Analyze: 1. Revenue retention by cohort — are newer cohorts retaining better or worse than older ones? 2. Expansion pattern — at what point do cohorts typically start expanding vs. contracting? 3. Best-performing cohort — which cohort has the highest NRR? What was different about those customers or that period? 4. Worst-performing cohort — what drove underperformance? Product issue, ICP, timing? 5. LTV trend — based on cohort performance, what is the expected lifetime value of a new customer acquired today? Output: Cohort retention table. NRR trend by cohort. Best/worst cohort analysis. LTV estimate for current ICP.
Why it works
Cohort analysis reveals whether the business is improving or deteriorating in a way that aggregate metrics hide — a company with growing ARR but declining cohort retention is burning through customers rather than building durable revenue. NRR by cohort at 6, 12, and 24 months shows when expansion and contraction patterns emerge, which informs both product development priorities and expansion playbook timing. The newer vs. older cohort comparison identifies whether recent changes (product updates, target market shifts) are improving or worsening retention.
Watch out for
Cohort analysis requires sufficient customer volume per cohort to be statistically meaningful — a company with 10-15 new customers per quarter will have high variance in cohort NRR that reflects individual deal noise rather than systemic patterns. Flag analyses built on small cohort sizes and avoid drawing strategic conclusions from a single cohort's performance.
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