--- name: churn-prediction description: Identify at-risk customers using behavioral signals, engagement patterns, and health indicators before they cancel license: MIT metadata: author: ClawFu version: 1.0.0 mcp-server: "@clawfu/mcp-skills" --- # Churn Prediction > Detect early warning signals of customer churn through systematic analysis of usage patterns, support interactions, and relationship health. ## When to Use This Skill - Monthly/quarterly churn risk reviews - Prioritizing CSM intervention - Building early warning systems - Post-mortem analysis on lost customers - Executive churn reporting ## Methodology Foundation Based on **Lincoln Murphy's Churn Analysis** and **ProfitWell Retention Research**, analyzing: - Product engagement decay - Support sentiment trends - Payment behavior changes - Relationship deterioration - Competitive signals ## What Claude Does vs What You Decide | Claude Does | You Decide | |-------------|------------| | Identifies risk signals | Save vs. let go decisions | | Calculates risk scores | Resource allocation | | Suggests interventions | Discount/concession offers | | Prioritizes at-risk accounts | Executive escalation timing | | Analyzes churn patterns | Retention strategy changes | ## What This Skill Does 1. **Signal detection** - Identify behavioral indicators of churn risk 2. **Risk scoring** - Calculate churn probability 3. **Root cause analysis** - Why are they likely to leave? 4. **Intervention planning** - What actions could save them? 5. **Pattern recognition** - Learn from past churned accounts ## How to Use ``` Assess churn risk for this customer: Account: [Company Name] Contract: $[ARR], Renewal: [Date] Tenure: [Months] Usage Signals: - Login frequency: [trend] - Feature adoption: [% and trend] - Active users: [current vs licensed] - Key feature usage: [specific metrics] Support Signals: - Recent tickets: [count and nature] - CSAT trend: [improving/stable/declining] - Escalations: [any open or recent] - Sentiment: [last few interactions] Relationship Signals: - Champion status: [engaged/disengaged/left] - Exec sponsor: [status] - NPS response: [score and comments] - QBR attendance: [pattern] Financial Signals: - Payment status: [current/late] - Contract discussions: [any mentions of changes] - Competitor mentions: [any signals] ``` ## Instructions ### Step 1: Evaluate Leading Indicators **30-60 Day Warning Signs:** | Signal | Risk Level | Weight | |--------|------------|--------| | Login drop >50% | High | 15 | | Feature usage stopped | High | 15 | | Support tickets spike | Medium | 10 | | Champion left | Critical | 20 | | Negative NPS | High | 12 | | Payment late | Medium | 8 | | No QBR attendance | Medium | 8 | | Competitor mentioned | High | 12 | ### Step 2: Calculate Churn Probability **Risk Score Formula:** ``` Churn Risk = Sum of weighted signals / 100 Score Ranges: - 0-20: Low Risk (normal attention) - 21-40: Moderate Risk (proactive outreach) - 41-60: High Risk (intervention required) - 61-80: Critical Risk (executive escalation) - 81-100: Imminent Churn (save or plan exit) ``` ### Step 3: Identify Root Cause Category | Category | Indicators | Typical Save Rate | |----------|------------|-------------------| | Product Fit | Low adoption, wrong use case | 30% | | Value Gap | Not seeing ROI, budget pressure | 45% | | Service Issue | Support failures, unresolved bugs | 60% | | Relationship | Champion left, no engagement | 35% | | Competition | Actively evaluating others | 25% | | Business Change | M&A, budget cuts, pivot | 15% | ### Step 4: Prescribe Intervention **By Root Cause:** | Cause | Primary Action | Secondary Action | |-------|----------------|------------------| | Product Fit | Success planning | Right-size contract | | Value Gap | ROI review | Executive sponsor call | | Service Issue | Escalation + resolution | Service credits | | Relationship | New champion dev | Executive mapping | | Competition | Competitive defense | Pricing review | | Business | Flexible terms | Pause option | ### Step 5: Create Save Plan **90-Day Save Framework:** - **Days 1-7**: Triage and stabilize - **Days 8-30**: Address root cause - **Days 31-60**: Rebuild value perception - **Days 61-90**: Secure commitment ## Examples ### Example 1: High-Risk Account **Input:** ``` Account: MediaTech Corp Contract: $96K ARR, Renewal: April 15 (45 days) Tenure: 18 months Usage Signals: - Logins: Down 65% last 30 days - Feature adoption: 35% (was 60%) - Active users: 8 of 25 licensed - Core feature: Stopped using analytics module Support Signals: - Tickets: 8 this month (normally 2) - CSAT: Dropped from 4.5 to 3.2 - Escalation: 1 open (data export issue) - Sentiment: Last 3 interactions negative Relationship Signals: - Champion: VP Marketing left 6 weeks ago - Exec sponsor: Never established - NPS: 4 (was 8 six months ago) - QBR: Cancelled last two Financial Signals: - Payment: Current - Mentions: "Evaluating options" in last call - Competitor: Saw CompetitorX demo on their calendar ``` **Output:** ``` ## Churn Risk Assessment: MediaTech Corp ### 🔴 CRITICAL RISK - 78/100 **Churn Probability: 75-85%** **Time to Action: Immediate** --- ### Risk Signal Analysis | Signal | Finding | Points | |--------|---------|--------| | Usage drop 65% | Critical | 15/15 | | Feature stopped | Analytics abandoned | 15/15 | | Champion left | No replacement | 20/20 | | NPS Detractor | Dropped 4 points | 12/12 | | Competitor eval | Demo scheduled | 12/12 | | No QBR | 2 cancelled | 8/8 | | **Total** | | **78/100** | ### Root Cause Analysis **Primary: Relationship Void** (Champion departure) - VP Marketing left 6 weeks ago - No executive sponsor ever established - Organizational knowledge lost - No one internally championing value **Secondary: Value Gap** (Product not delivering) - Usage collapse suggests not getting value - Analytics module abandoned = key feature unused - May have been champion-dependent usage **Tertiary: Active Competition** - CompetitorX demo on calendar - "Evaluating options" language - Classic exit signals ### Competitor Intelligence **CompetitorX Positioning:** - Likely pitching: Simpler interface, lower price - Their weakness: Less robust analytics - Our defense: Depth of features, integration ### 90-Day Save Plan **WEEK 1: Emergency Triage** | Day | Action | Owner | |-----|--------|-------| | 1 | Resolve data export escalation | Support | | 1 | CSM call to understand situation | CSM | | 2 | Identify new potential champion | CSM | | 3 | VP CS call to express commitment | VP CS | | 5 | Executive sponsor outreach (their CMO) | CRO | **WEEK 2-4: Stabilize** - [ ] Close escalation completely - [ ] Meet new champion (find one!) - [ ] Re-onboard inactive users - [ ] Document value delivered to date - [ ] Competitive battle card preparation **WEEK 5-8: Rebuild Value** - [ ] ROI review presentation - [ ] Success planning session - [ ] Showcase new features - [ ] Get 3 quick wins documented **WEEK 9-12: Secure Renewal** - [ ] QBR with exec attendance - [ ] Renewal discussion - [ ] Multi-year incentive if appropriate - [ ] Reference/case study request (confidence signal) ### Save Probability Assessment | If We... | Save Probability | |----------|------------------| | Do nothing | 15% | | Standard outreach | 25% | | Execute full plan | 45% | | Add discount/concession | 55% | | Exec-to-exec + plan | 60% | ### Decision Point **Recommended: Full save effort** - $96K ARR worth 60-90 hours of CSM time - Cost to acquire replacement: ~$30K - Reputation risk if churns **If No Traction by Day 30:** - Prepare for graceful offboarding - Offer reduced contract if budget issue - Maintain relationship for potential return ``` ### Example 2: Cohort Churn Analysis **Input:** ``` Analyze churn patterns from these 10 churned accounts: 1. AlphaCo: Left after 8 months, champion left, low usage 2. BetaTech: Left after 14 months, pricing, competitor win 3. GammaCorp: Left after 6 months, wrong fit, never adopted 4. DeltaInc: Left after 24 months, budget cuts, loved product 5. EchoSys: Left after 10 months, support issues, 3 escalations 6. FoxtrotLLC: Left after 18 months, competitor, champion left 7. GolfCo: Left after 4 months, implementation failed 8. HotelGrp: Left after 12 months, didn't see ROI 9. IndiaInc: Left after 9 months, champion left, low NPS 10. JulietCorp: Left after 20 months, M&A, product deprecated ``` **Output:** ``` ## Churn Cohort Analysis: Q4 Losses ### Summary - **Total Churned**: 10 accounts - **Total ARR Lost**: [Calculate from data] - **Average Tenure**: 12.5 months --- ### Root Cause Distribution | Root Cause | Count | % | Avg Tenure | |------------|-------|---|------------| | Champion Left | 4 | 40% | 11.3 mo | | Competitor | 3 | 30% | 17.3 mo | | Product/Fit | 2 | 20% | 5.0 mo | | Business Change | 2 | 20% | 22.0 mo | | Service/Support | 1 | 10% | 10.0 mo | | Value/ROI | 2 | 20% | 10.0 mo | *Note: Some accounts had multiple causes* ### Key Insights **1. Champion Dependency is Critical (40%)** - 4 of 10 churns involved champion departure - Average: Churned 3-4 months after champion left - **Action**: Multi-threading program required **2. Early Churn = Fit Problem** - 3 accounts churned <6 months - All had adoption/implementation issues - **Action**: Improve qualification + onboarding **3. Competitor Wins Correlate with Tenure** - Competitor losses at 14, 18, 20 months - Long enough to evaluate alternatives - **Action**: Value reinforcement at 12-month mark **4. Business Change is Uncontrollable** - 2 churns from M&A/budget cuts - Both were "happy" customers - **Action**: Accept, maintain relationship ### Early Warning Signal Validation | Signal | Present Before Churn | Lead Time | |--------|---------------------|-----------| | Champion left | 4/10 (40%) | 3-4 months | | Usage drop >40% | 7/10 (70%) | 6-8 weeks | | NPS drop | 6/10 (60%) | 2-3 months | | Missed QBR | 5/10 (50%) | 3-4 months | | Support spike | 3/10 (30%) | 4-6 weeks | **Best Predictor**: Usage drop >40% (70% correlation) ### Preventability Assessment | Account | Preventable? | What Would Have Helped | |---------|--------------|------------------------| | AlphaCo | Likely | Champion backup plan | | BetaTech | Possibly | Competitive defense earlier | | GammaCorp | Unlikely | Better qualification | | DeltaInc | No | Business change | | EchoSys | Likely | Faster escalation resolution | | FoxtrotLLC | Possibly | Multi-thread + compete | | GolfCo | Likely | Implementation oversight | | HotelGrp | Likely | Proactive ROI review | | IndiaInc | Likely | Champion backup | | JulietCorp | No | M&A out of control | **Preventability Rate**: 60% (6/10 could have been saved) ### Recommendations **Process Changes:** 1. Implement champion backup contact rule (2+ contacts) 2. Add 12-month value review to CSM playbook 3. Create competitive defense triggers 4. Improve implementation success metrics **Investment Areas:** 1. CSM capacity for proactive outreach 2. Competitive intelligence 3. Champion development program **Metrics to Track:** - Champion backup coverage % - Time to first value - Competitive mention alerts - 12-month NPS trend ``` ## Skill Boundaries ### What This Skill Does Well - Systematic risk signal analysis - Probability scoring with clear logic - Root cause categorization - Intervention planning ### What This Skill Cannot Do - Access actual customer data - Predict exact churn timing - Know internal customer dynamics - Replace relationship intuition ### When to Escalate to Human - Strategic accounts (top 10%) - Complex multi-product relationships - Escalation requiring legal/exec involvement - Pricing concession decisions ## Iteration Guide ### Follow-up Prompts - "Create a 30-60-90 save plan for this account." - "What competitive response should we prepare?" - "Which of my at-risk accounts should I prioritize?" - "Analyze the pattern across all my churned accounts." ### Monitoring Cadence 1. Score all accounts monthly 2. Alert on score drops >15 points 3. Weekly review of Critical/High risk 4. Quarterly pattern analysis ## Checklists & Templates ### At-Risk Account Checklist - [ ] Usage trend analyzed (30/60/90 day) - [ ] Support sentiment reviewed - [ ] Champion status confirmed - [ ] NPS collected or requested - [ ] Competitor signals checked - [ ] Financial health verified - [ ] Save plan documented ## References - Lincoln Murphy's Churn Analysis Framework - ProfitWell Retention Benchmarks - Gainsight Customer Health Methodology - ChurnZero Predictive Analytics ## Related Skills - `account-health` - Broader health scoring - `health-score-monitor` - Continuous monitoring - `renewal-management` - Renewal process ## Skill Metadata - **Domain**: Customer Success - **Complexity**: Advanced - **Mode**: centaur - **Time to Value**: 20-30 min per account - **Prerequisites**: Customer data, history, context