health-score-monitor

name	health-score-monitor
description	Design and maintain customer health scoring systems with automated alerts and trending analysis
license	MIT
metadata	{"author":"ClawFu","version":"1.0.0","mcp-server":"@clawfu/mcp-skills"}

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

1. Framework design - Multi-factor health model
2. Score calculation - Weighted composite scores
3. Trend analysis - Direction and velocity
4. Alert rules - When to notify teams
5. 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 analysis
• account-health - RevOps perspective
• expansion-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