health-score-monitor
关于
This skill helps developers design and maintain customer health scoring systems with automated alerts and trending analysis. It's useful for building monitoring dashboards, setting alert thresholds, and analyzing health trends across a customer portfolio. The skill provides a framework for multi-dimensional scoring based on methodologies like Gainsight and Totango.
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技能文档
Health 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
churn-prediction- Deeper churn analysisaccount-health- RevOps perspectiveexpansion-signals- Growth focus
Skill Metadata
- Domain: Customer Success
- Complexity: Advanced
- Mode: centaur
- Time to Value: 2-4 hours for framework design
- Prerequisites: Data availability assessment
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