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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.

Quellinformationen

Repository
modbender/skill-library-mcp
Letzte Quellaktivität
6. März 2026 um 18:33
Erkannte Sprache von SKILL.md
Englisch
Sterne
12
Forks
3

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
Churn Risk Analyzer
description
Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.
# 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) ### 3. Categorize - **🔴 Critical (75-100)**: Immediate intervention needed - **🟡 At Risk (50-74)**: Schedule check-in this week - **🟢 Healthy (25-49)**: Monitor monthly - **💚 Thriving (0-24)**: Expansion opportunity ### 4. Recommend Actions For each at-risk account, suggest specific retention plays: - Executive sponsor call - Custom success plan - Feature training session - Pricing review / loyalty offer - Roadmap preview (show upcoming value) ### 5. Output Generate a retention report with: - Ranked list of accounts by churn risk - Top 3 actions per critical account - Estimated revenue at risk - 30/60/90 day retention calendar ## Integration Notes - Works with CSV exports, CRM data, or manual input - Pair with the [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/) for industry-specific retention strategies ($47/pack) - For a full AI-powered retention system built for your business, try the [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) to see what you're leaving on the table
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