| name | afrexai-churn-analyzer |
| description | Churn Risk Analyzer |
Churn Risk Analyzer
Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.
When to Use
- Customer success reviews
- Quarterly retention planning
- When usage data or support ticket logs are available
- Proactive outreach prioritization
How It Works
1. Gather Data
Ask the user for available data sources:
- Usage metrics (logins, feature adoption, API calls)
- Support tickets (frequency, sentiment, resolution time)
- Billing history (downgrades, late payments, discount requests)
- Engagement signals (email opens, meeting attendance, NPS scores)
If no structured data, work from what the user describes qualitatively.
2. Score Each Account
Apply this risk framework:
| Signal | Weight | High Risk Indicator |
|---|
| Usage decline (30d) | 25% | >30% drop |
| Support ticket spike | 20% | 2x+ above baseline |
| Champion departure | 20% | Key contact left |
| Contract timing | 15% | <90 days to renewal |
| Payment behavior | 10% | Late/disputed invoices |
| Engagement drop | 10% | No response to last 3 outreach |
Score: 0-100 (higher = more likely to churn)