Churn Risk Analyzer
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。
SkillHub CLI
skillhub install 1kalin/afrexai-churn-analyzer打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。
Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.
Ask the user for available data sources:
If no structured data, work from what the user describes qualitatively.
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)
For each at-risk account, suggest specific retention plays:
Generate a retention report with:
这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。
Stop losing customers you could have saved.
This skill turns your usage data, support tickets, and engagement signals into a prioritized churn risk scorecard. Each account gets a 0-100 risk score with specific retention actions.
Describe your customers qualitatively and the skill adapts — you don't need a data warehouse to start identifying risk.
Want industry-specific retention strategies? Check out the AfrexAI Context Packs — pre-built AI agent configurations for SaaS, fintech, healthcare, and 7 more verticals. $47/pack.
Curious how much revenue you're leaking? Run the free AI Revenue Calculator.
# 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 C...
# Churn Risk Analyzer Stop losing customers you could have saved. This skill turns your usage data, support tickets, and engagement signals into a prioritized churn risk scorecard. Each account gets a 0-100 risk score with specific retention actions. ## What You Get - Churn risk scoring across 6 behavioral dimensions - Accounts ranked by revenue at risk - Specific retention plays for each critical account - 30/60/90 day action calendar ## Works With - CSV exports from any CRM or billing system - Manual account descriptions - Support ticket logs - Usage/analytics data ## No Data? No Problem. Describe your customers qualitatively and the skill adapts — you don't need a data warehouse to start identifying risk. --- **Want industry-specific retention strategies?** Check out the [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/) — pre-built AI agent configurations for SaaS, fintech, healthcare, and 7 more verticals. $47/pack. **Curious how much revenue you're leaking?** Run the free [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/).
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