Customer success teams are firefighters. They react to problems.
A customer health score makes them paramedics. It predicts problems before they happen.
This guide covers how to build and use a health score dashboard.
What Is a Customer Health Score?
A single number (0-100) predicting: "Will this customer renew?"
High score (80+) = likely to renew Low score (40-) = at-risk, might churn
How to Calculate It
Weight the factors that predict churn:
Product Engagement (30%)
- Login frequency
- Feature adoption
- Sessions per week
- Days since last login
Usage Growth (25%)
- Seats/users growing?
- Usage volume trend
- Feature expansion
Support Health (20%)
- Open support tickets?
- Response times met?
- Sentiment from tickets
Business Health (25%)
- Payment issues?
- Contract renewal date
- Payment rate (paying on time?)
Formula:
Health Score =
(Engagement × 0.30) +
(Growth × 0.25) +
(Support × 0.20) +
(Business × 0.25)
Scale 0-100
The Dashboard Layout
┌─────────────────────────────────────────┐
│ AT-RISK CUSTOMERS (score < 40) │
│ Customer A: 25 (no login in 30 days) │
│ Customer B: 38 (2 open support tickets)│
│ [ACTION: Reach out today] │
└─────────────────────────────────────────┘
┌──────────────────────────────────────────┐
│ NEEDS ATTENTION (score 40-60) │
│ Customer C: 55 (engagement down 40%) │
│ Customer D: 48 (ticket response slow) │
│ [ACTION: Check in this week] │
└──────────────────────────────────────────┘
┌──────────────────────────────────────────┐
│ HEALTHY (score 60+) │
│ Customer E: 88 (usage up, engaged) │
│ Customer F: 92 (expanding seats) │
└──────────────────────────────────────────┘
[Trend: Health scores down 5% from last month]
Color-Coded Risk Levels
- 🔴 Red (0-40): Critical, reach out immediately
- 🟡 Yellow (40-60): At-risk, schedule check-in
- 🟢 Green (60-100): Healthy, nurture for expansion
Key Features
1. Trending: Show score over time. A dropping trend is a warning even if current score is decent.
2. Drill-Down: Click a customer to see: "Why is their score low?"
- Low engagement? (Missing feature tutorials?)
- Support issues? (Fix those tickets)
- Payment delays? (Contracts upcoming?)
3. Segmentation: Filter by:
- Industry / segment
- Customer size
- Product tier
- Tenure
This reveals patterns. Maybe Enterprise customers always dip in Q2.
Using the Dashboard
Daily (CS team):
- Check red/yellow customers
- Reach out to at-risk accounts
- Log actions taken
Weekly (Manager):
- Trend analysis (is health improving?)
- Identify patterns (which segments are at-risk?)
- Allocate resources (where to focus CS effort?)
Monthly (Leadership):
- Correlation analysis (is product improving retention?)
- Forecast (predict churn for next quarter)
- Strategy (which customers need improvement? Which markets?)
What a Good Health Score Does
✓ Predicts churn 4-8 weeks in advance (time to intervene) ✓ Identifies root cause (engagement? support? pricing?) ✓ Guides CS actions (who to reach out to, what to fix) ✓ Validates product improvements (did feature launch improve scores?) ✓ Segments customers (which deserve enterprise support?)
Building the Score: Frameworks
Simple (DIY): 1-5 scale for engagement, support, growth, business Average them. Done.
Moderate (tools-based): Use a CS platform (Gainsight, Planhat) that tracks these automatically.
Advanced (data-driven): Use ML to weight factors by their actual correlation to churn.
Start simple. You can sophisticate later.
Common Mistakes
❌ Using vanity metrics: Email opens don't predict churn. Actual usage does.
❌ Ignoring external factors: Market downturn affects everyone. Score needs context.
❌ Setting it and forgetting it: Health scores decay. Recalibrate quarterly.
❌ Not acting on low scores: A dashboard is useless if CS doesn't follow up.
Checklist
- ✓ Health score predicts churn (validate against actual churn)
- ✓ Factors weighted by importance
- ✓ Includes engagement, growth, support, business health
- ✓ Scored 0-100 (easy to interpret)
- ✓ Color-coded (red/yellow/green)
- ✓ Shows trend (not just current score)
- ✓ Drill-down to root causes
- ✓ Updated at least monthly
- ✓ CS team acts on low scores
- ✓ Calibrated against actual churn
The Bottom Line
A health score is a prediction tool. Use it to call customers before they leave.
A customer with a dropping health score is more valuable than data about a customer who already churned.
Get ahead of churn. That's what the dashboard is for.