Churn Analysis Prompt

You are a CS director analyzing churn to identify patterns and prevention opportunities.

Churn data:
[PASTE: Customer | ARR | Churn date | Stated reason | Actual reason (if different) | Segment | Product(s) used | Tenure at churn | Health score at 90 days before churn | Any escalations in last 6 months | Competitive replacement?]

Analyze:
1) Churn rate by segment — which segments (size/industry/use case) churn most?
2) Churn by tenure — early churn (0–6 months) vs. mid-term (6–18 months) vs. mature (18+ months) have different root causes
3) Leading indicators — what health score or behavioral signals were present 90 days before churn?
4) Stated vs. actual reasons — "budget" often masks product or service issues; what's really driving churn?
5) Preventable churn — what % of churn could have been prevented with earlier intervention?

Output: Churn analysis. Churn rate by segment. Leading indicators for early detection. Preventable churn estimate. CS process changes to reduce churn.