Skip to main content

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.

ソース情報

リポジトリ
modbender/skill-library-mcp
ソースの最終更新活動
2026年3月6日 18:33
検出された SKILL.md の言語
英語
スター
12
フォーク
3

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

ソースファイルを確認

インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
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
GitHubで見る