Build a churn early-warning system and intervention playbook for your product, using Claude to analyze patterns and draft the save sequences.
Free checklist · copy-paste ready · built by the BrainVaultAI team
Churn is almost always predictable in hindsight. The customers who left showed signals weeks before they canceled. This playbook prompt helps you identify those signals, build a scoring system, and script the interventions, before the next wave churns out. You get a checklist of churn signals to instrument, a prompt to analyze why customers actually left, and a prompt to draft the save sequences for at-risk accounts. Run the analysis prompt after any churn event. Run the playbook-builder once per quarter. The goal is a repeatable system: spot the signal early, trigger the intervention automatically, and close the feedback loop so you learn with every save attempt.
Churn Signal Checklist
Instrument these signals. Any 2+ in a 7-day window = at-risk account. Engagement signals:
- [ ] Login frequency dropped >50% week-over-week
- [ ] Core feature usage dropped >40% vs. their average
- [ ] Support tickets opened in past 14 days without resolution
- [ ] Last login was >14 days ago
- [ ] Feature adoption score below 30% (less than 3 of 10 key features ever used) Relationship signals:
- [ ] No response to last 2 check-in emails
- [ ] Champion contact left the company (job change alert)
- [ ] Invoice paid late or disputed
- [ ] Downgrade request submitted
- [ ] Negative NPS response (0-6) in past 30 days Context signals:
- [ ] Customer in a vertical with known industry headwinds
- [ ] Customer came in on a heavy discount (low switching cost)
- [ ] Onboarding incomplete >60 days after signup
- [ ] No internal advocates identified at the account
Churn Analysis Prompt
You are a customer success analyst. Here is data on a customer who recently churned:
- Industry / company size: [INSERT]
- Tenure: [INSERT months]
- Plan: [INSERT]
- MRR lost: $[INSERT]
- Last activity: [INSERT]
- Support history: [INSERT, issues, resolutions, open tickets]
- Feature usage summary: [INSERT, what they used, what they ignored]
- Exit reason given (if any): [INSERT]
- Internal notes from CSM: [INSERT] Analyze:
1. What was the most likely primary churn cause?
2. What were the earliest warning signals we missed?
3. Was this churn preventable? If yes, at what point and with what action?
4. What does this tell us about a segment of similar customers?
5. What should we change in our product, onboarding, or CSM process? Direct analysis only. No softening. Name the failure.
At-Risk Account Save Prompt
You are a customer success manager drafting an intervention for an at-risk account. Account details:
- Company: [INSERT]
- Champion contact: [INSERT name/role]
- Risk signals triggered: [LIST FROM CHECKLIST]
- Their stated goal when they signed up: [INSERT]
- Current product usage: [INSERT, what they use and how often]
- Days until renewal: [INSERT] Draft:
1. A personalized outreach email (under 150 words). Lead with value, not desperation. Reference their specific goal.
2. A 3-point internal action plan: what we'll fix, offer, or change before the call
3. A talk track for the save call: what to open with, what to offer, what to ask
4. A clear decision tree: if they say X, we do Y Tone: peer-to-peer, direct, no corporate language.
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