health-score-monitor

What this skill does

# 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:
- 2