Analyze customer churn patterns and create retention strategies. TRIGGERS - Use when user wants to reduce churn, improve retention, or understand why customers leave.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add Winbda/claude-skills-collection --skill churn-analyzer --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Churn Analyzer?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/winbda-churn-analyzer)More formats (shields.io, HTML) on the badges page.
---
name: churn-analyzer
description: |
Analyze customer churn patterns and create retention strategies.
TRIGGERS - Use when user wants to reduce churn, improve retention, or understand why customers leave.
---
# Churn Analyzer
## Overview
Analyzes churn patterns, identifies root causes, and creates actionable retention strategies.
## Workflow
### Step 1: Gather Context
1. **Business model**: SaaS, service, product?
2. **Current churn rate**: Monthly/annual?
3. **Customer segments**: Different tiers or types?
4. **Known reasons**: Why do customers say they leave?
5. **Available data**: What customer data do you have?
### Step 2: Analyze Churn
**Churn calculation:**
```
Monthly churn = Customers lost / Starting customers × 100
Annual churn = 1 - (1 - monthly churn)^12
Revenue churn = MRR lost / Starting MRR × 100
```
**Analysis dimensions:**
- By segment (plan tier, industry, size)
- By tenure (when do they leave?)
- By engagement (usage before churn)
- By acquisition source (where they came from)
- By season (time patterns)
## Output Format
```markdown
# Churn Analysis: [Company]
## Current State
- **Monthly churn**: [X%]
- **Annual churn**: [X%]
- **Revenue impact**: $[X] lost/month
- **Industry benchmark**: [X%]
## Churn Patterns
### By Tenure
| Period | Churn Rate | Insight |
|--------|-----------|---------|
| Month 1 | X% | [early churn = onboarding problem] |
| Month 2-3 | X% | [value realization gap] |
| Month 6+ | X% | [engagement decay] |
### By Segment
[Breakdown by customer type]
## Root Cause Analysis
1. **[Cause 1]** — [% of churn] — [evidence]
2. **[Cause 2]** — [% of churn] — [evidence]
3. **[Cause 3]** — [% of churn] — [evidence]
## Retention Strategy
### Quick Wins (This Month)
1. [Action]: Expected impact [X% reduction]
2. [Action]: Expected impact [X% reduction]
### Medium-Term (This Quarter)
1. [Action]: Expected impact [X% reduction]
### Long-Term (This Year)
1. [Action]: Expected impact [X% reduction]
## Financial Impact
If churn reduces from [X%] to [Y%]:
- Monthly revenue saved: $[X]
- Annual impact: $[X]
- LTV improvement: [X%]
```
## Quality Checklist
- [ ] Churn calculated correctly (logo + revenue)
- [ ] Patterns identified by multiple dimensions
- [ ] Root causes ranked by impact
- [ ] Retention strategies are specific and actionable
- [ ] Financial impact quantified
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!