Clawfu-skills health-score-monitor
Design and maintain customer health scoring systems with automated alerts and trending analysis
git clone https://github.com/guia-matthieu/clawfu-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/guia-matthieu/clawfu-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/customer-success/health-score-monitor" ~/.claude/skills/guia-matthieu-clawfu-skills-health-score-monitor && rm -rf "$T"
skills/customer-success/health-score-monitor/SKILL.mdHealth Score Monitor
Build systematic customer health monitoring with composite scores, trend tracking, and automated alerting for proactive customer success.
When to Use This Skill
- Designing health score frameworks
- Setting up monitoring dashboards
- Creating alert thresholds
- Analyzing health trends across portfolio
- Optimizing existing health models
Methodology Foundation
Based on Gainsight Health Score Design and Totango Customer Success metrics, focusing on:
- Multi-dimensional scoring
- Leading vs lagging indicators
- Score normalization
- Trend analysis
- Alert prioritization
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Designs scoring framework | Dimension weights |
| Calculates composite scores | Alert thresholds |
| Identifies trending patterns | Intervention triggers |
| Suggests monitoring cadence | Resource allocation |
| Recommends improvements | Business rule exceptions |
What This Skill Does
- Framework design - Multi-factor health model
- Score calculation - Weighted composite scores
- Trend analysis - Direction and velocity
- Alert rules - When to notify teams
- Portfolio view - Aggregate health visibility
How to Use
Design a health score monitor for my customer portfolio: Business Context: - Product type: [SaaS/Platform/Service] - Contract model: [Annual/Monthly/Multi-year] - Key value metric: [What shows customer success?] - CSM:Account ratio: [1:X] Available Data Points: - Product: [List usage metrics available] - Support: [List support metrics available] - Financial: [List financial signals] - Relationship: [List engagement data] Current Challenges: - [What's not working with current approach?]
Instructions
Step 1: Define Health Dimensions
Standard 4-Pillar Model:
| Dimension | Weight | What It Answers |
|---|---|---|
| Product | 30-40% | Are they using it? |
| Support | 15-25% | Are they happy? |
| Financial | 20-25% | Are they paying/growing? |
| Relationship | 20-25% | Are we connected? |
Adjust weights based on your business:
- High-touch: Increase Relationship
- Usage-based pricing: Increase Product
- Support-intensive: Increase Support
Step 2: Select Metrics per Dimension
Product Health Metrics:
| Metric | Type | Scoring |
|---|---|---|
| DAU/MAU | Leading | % of benchmark |
| Feature adoption | Leading | % features used |
| Time in product | Leading | Minutes vs avg |
| Key feature usage | Leading | Yes/No or frequency |
| Usage trend | Leading | Up/Flat/Down |
Support Health Metrics:
| Metric | Type | Scoring |
|---|---|---|
| CSAT score | Lagging | 1-5 scale |
| Ticket volume | Leading | vs baseline |
| Escalations | Leading | Count (negative) |
| Response sentiment | Leading | Positive/Neutral/Negative |
| Time to resolution | Lagging | vs SLA |
Financial Health Metrics:
| Metric | Type | Scoring |
|---|---|---|
| Payment status | Lagging | Current/Late |
| Expansion | Leading | Pipeline/Discussion |
| Contract type | Lagging | Multi-year bonus |
| Renewal date | Context | Days remaining |
| ARR trend | Lagging | Growth/Flat/Decline |
Relationship Health Metrics:
| Metric | Type | Scoring |
|---|---|---|
| Champion engaged | Leading | Active/Passive/None |
| Exec sponsor | Leading | Yes/No |
| NPS/CSAT | Lagging | Score |
| QBR attendance | Leading | Regular/Sporadic/None |
| Last touch | Leading | Days since contact |
Step 3: Create Scoring Rules
Example Scoring Matrix:
Product Score (0-100): +30: DAU/MAU > 70% +20: DAU/MAU 50-70% +10: DAU/MAU 30-50% +0: DAU/MAU < 30% +25: Feature adoption > 60% +15: Feature adoption 40-60% +5: Feature adoption < 40% +20: Usage trending up +10: Usage stable -10: Usage trending down +15: Key feature used weekly +5: Key feature used monthly -10: Key feature abandoned Max: 100 (or normalize)
Step 4: Set Alert Thresholds
| Condition | Alert Level | Action |
|---|---|---|
| Score drops >15 pts | 🔴 Critical | Immediate CSM review |
| Score below 40 | 🟠 High | Intervention required |
| Score 40-60 | 🟡 Medium | Proactive outreach |
| Renewal <60 days + <60 score | 🔴 Critical | Save plan |
| Usage drop >30% WoW | 🟡 Medium | Check-in call |
Step 5: Define Monitoring Cadence
| Activity | Frequency | Owner |
|---|---|---|
| Score refresh | Daily/Weekly | Automated |
| Alert review | Daily | CSM |
| Portfolio review | Weekly | CS Manager |
| Model calibration | Quarterly | CS Ops |
Examples
Example 1: SaaS Health Score Design
Input:
Design health score for our B2B SaaS platform: Business Context: - Product: Project management software - Contract: Annual, avg $50K - Value metric: Projects completed, team adoption - CSM ratio: 1:40 Available Data: - Product: Logins, projects created, tasks completed, integrations used - Support: Zendesk tickets, CSAT, NPS - Financial: ARR, payment status, expansion pipeline - Relationship: Meeting attendance, email engagement Challenges: - Too many "yellow" accounts, can't prioritize - Alerts are noisy, CSMs ignoring them
Output:
## Health Score Framework: Project Management SaaS ### Design Principles Given 1:40 ratio and "alert fatigue" issue: 1. **Prioritize leading indicators** - Catch issues early 2. **Reduce noise** - Tighter alert thresholds 3. **Enable triage** - Clear Red/Yellow/Green actions --- ### Scoring Model #### Dimension Weights | Dimension | Weight | Rationale | |-----------|--------|-----------| | Product | 40% | Usage = value realization | | Support | 15% | Lower touch model | | Financial | 25% | Contract health critical | | Relationship | 20% | Moderate touch needed | --- #### Product Score (40 points max) | Metric | Criteria | Points | |--------|----------|--------| | **Weekly Active Users** | | | | | >70% of seats | 12 | | | 50-70% | 8 | | | 30-50% | 4 | | | <30% | 0 | | **Projects Created (monthly)** | | | | | >5 per user | 10 | | | 2-5 per user | 6 | | | <2 per user | 2 | | **Tasks Completed** | | | | | >80% completion rate | 8 | | | 50-80% | 5 | | | <50% | 0 | | **Integrations** | | | | | 2+ active | 6 | | | 1 active | 3 | | | None | 0 | | **Usage Trend** | | | | | Increasing | 4 | | | Stable | 2 | | | Declining | -4 | --- #### Support Score (15 points max) | Metric | Criteria | Points | |--------|----------|--------| | **CSAT** | | | | | >4.5 | 6 | | | 4.0-4.5 | 4 | | | 3.5-4.0 | 2 | | | <3.5 | 0 | | **Ticket Volume** | | | | | Below baseline | 5 | | | At baseline | 3 | | | 2x+ baseline | 0 | | **Escalations** | | | | | None (90 days) | 4 | | | Resolved | 2 | | | Open | -4 | --- #### Financial Score (25 points max) | Metric | Criteria | Points | |--------|----------|--------| | **Payment Status** | | | | | Current | 10 | | | 30 days late | 5 | | | 60+ days | 0 | | **Expansion** | | | | | Closed this year | 8 | | | In discussion | 5 | | | No opportunity | 2 | | **Contract Type** | | | | | Multi-year | 7 | | | Annual | 4 | | | Month-to-month | 0 | --- #### Relationship Score (20 points max) | Metric | Criteria | Points | |--------|----------|--------| | **Champion Status** | | | | | Active advocate | 8 | | | Engaged | 5 | | | Passive | 2 | | | Gone/None | 0 | | **NPS** | | | | | 9-10 (Promoter) | 6 | | | 7-8 (Passive) | 4 | | | 0-6 (Detractor) | 0 | | **Last Touch** | | | | | <30 days | 6 | | | 30-60 days | 4 | | | 60-90 days | 2 | | | >90 days | 0 | --- ### Health Bands | Score | Status | Count Target | CSM Action | |-------|--------|--------------|------------| | 80-100 | 🟢 Healthy | 60% | Quarterly touch, expansion | | 60-79 | 🟡 Monitor | 25% | Monthly touch, watch trends | | 40-59 | 🟠 At Risk | 12% | Bi-weekly, intervention plan | | 0-39 | 🔴 Critical | 3% | Weekly, executive escalation | **Target Distribution** at 1:40 ratio: - 24 Healthy (quarterly = 8 touches/month) - 10 Monitor (monthly = 10 touches) - 5 At Risk (bi-weekly = 10 touches) - 1 Critical (weekly = 4 touches) - **Total: 32 touch points/month** (manageable) --- ### Alert Rules (Noise Reduction) **Only Alert When:** | Alert | Condition | Frequency | |-------|-----------|-----------| | 🔴 Critical New | Score drops below 40 | Immediate | | 🔴 Renewal Risk | Score <60 AND renewal <60 days | Immediate | | 🟠 Score Drop | Drops >15 points in 7 days | Daily digest | | 🟡 Watch | Usage down >30% WoW | Weekly digest | **Suppress Alerts For:** - Accounts <30 days old (onboarding) - Accounts in active implementation - Known seasonal low periods - Manual "snooze" by CSM --- ### Dashboard Views **Portfolio Summary:**
┌─────────────────────────────────────┐ │ My Portfolio: 40 accounts │ ├─────────────────────────────────────┤ │ 🟢 24 (60%) │ 🟡 10 (25%) │ │ 🟠 5 (12%) │ 🔴 1 (3%) │ ├─────────────────────────────────────┤ │ ⚠️ 3 accounts dropped this week │ │ 📈 5 accounts improved │ └─────────────────────────────────────┘
**Account Drill-Down:**
┌─────────────────────────────────────┐ │ Account: TechCorp | Score: 62 🟡 │ ├─────────────────────────────────────┤ │ Product: 28/40 ████████░░ │ │ Support: 12/15 █████████░ │ │ Financial: 14/25 ██████░░░░ │ │ Relationship: 8/20 ████░░░░░░ │ ├─────────────────────────────────────┤ │ Trend: ↘️ -8 pts (30 days) │ │ Renewal: 90 days │ │ Action: Schedule check-in │ └─────────────────────────────────────┘
Example 2: Health Trend Analysis
Input:
Analyze health trends for my portfolio: Q4 Scores: - Oct: 23 Green, 12 Yellow, 4 Orange, 1 Red - Nov: 20 Green, 14 Yellow, 5 Orange, 1 Red - Dec: 18 Green, 13 Yellow, 7 Orange, 2 Red Also: - 3 accounts churned in Q4 - 2 expansions closed - NPS survey: 42 average (was 48)
Output:
## Q4 Health Trend Analysis ### Portfolio Drift Summary | Status | Oct | Nov | Dec | Change | |--------|-----|-----|-----|--------| | 🟢 Green | 23 (58%) | 20 (50%) | 18 (45%) | ↘️ -13% | | 🟡 Yellow | 12 (30%) | 14 (35%) | 13 (33%) | → +3% | | 🟠 Orange | 4 (10%) | 5 (13%) | 7 (18%) | ↗️ +8% | | 🔴 Red | 1 (2%) | 1 (2%) | 2 (5%) | ↗️ +3% | **Trend: ⚠️ Deteriorating** - 5 accounts moved from Green to lower status - Orange/Red grew from 12% to 23% - Portfolio health declining month-over-month --- ### Churn Correlation | Churned Account | Last Score | Days at Red | |-----------------|------------|-------------| | Account A | 28 | 45 days | | Account B | 35 | 30 days | | Account C | 41 | 22 days | **Insight**: All churned accounts were Red/Orange for 20+ days **Action**: Accounts at Orange >14 days need intervention --- ### Key Drivers of Decline **Analyzing accounts that dropped:** | Factor | Accounts Affected | Avg Point Drop | |--------|-------------------|----------------| | Usage decline | 8 | -12 pts | | Champion change | 3 | -18 pts | | Support issues | 4 | -8 pts | | Payment delays | 2 | -6 pts | **Primary Driver**: Usage decline (likely seasonal + holiday) --- ### NPS Correlation | NPS Segment | Avg Health Score | Q4 Change | |-------------|------------------|-----------| | Promoters (9-10) | 78 | -3 | | Passives (7-8) | 58 | -6 | | Detractors (0-6) | 38 | -10 | **Insight**: Detractor scores dropping fastest **Action**: Prioritize intervention for Detractors --- ### Q1 Recommendations **Immediate (Week 1):** 1. Save plan for 2 Red accounts 2. Intervention for 7 Orange accounts 3. Outreach to 3 champion-change accounts **Short-term (Month 1):** 1. Re-engagement campaign for low-usage accounts 2. Proactive support reach-out to ticket-heavy accounts 3. NPS follow-up calls with Detractors **Strategic (Quarter):** 1. Investigate seasonal patterns (plan for Q4 2026) 2. Champion backup program implementation 3. Revisit Orange threshold (too many?) --- ### Target for Q1 | Status | Dec | Q1 Target | Delta | |--------|-----|-----------|-------| | 🟢 Green | 18 | 22 | +4 | | 🟡 Yellow | 13 | 14 | +1 | | 🟠 Orange | 7 | 3 | -4 | | 🔴 Red | 2 | 1 | -1 | **Success = Move 5 accounts up at least one tier**
Skill Boundaries
What This Skill Does Well
- Designing health frameworks
- Calculating composite scores
- Identifying trends and patterns
- Setting alert thresholds
What This Skill Cannot Do
- Access your actual data
- Implement in your systems
- Know your specific business rules
- Replace data engineering
When to Escalate to Human
- Threshold decisions
- Weight calibration based on churn data
- Alert rule tuning
- Cross-functional alignment
Iteration Guide
Follow-up Prompts
- "How should I weight these dimensions differently for enterprise vs SMB?"
- "What metrics should I add for a usage-based pricing model?"
- "Create alert rules that reduce noise by 50%."
- "Design a health score for a high-touch services business."
References
- Gainsight Health Score Best Practices
- Totango Customer Health Methodology
- ChurnZero Scoring Framework
- Customer Success Benchmarks
Related Skills
- Deeper churn analysischurn-prediction
- RevOps perspectiveaccount-health
- Growth focusexpansion-signals
Skill Metadata
- Domain: Customer Success
- Complexity: Advanced
- Mode: centaur
- Time to Value: 2-4 hours for framework design
- Prerequisites: Data availability assessment