Customer Health Score
A composite metric combining multiple signals like product usage, support tickets, NPS responses, and payment history to predict customer retention or churn risk.
Why customer health score matters
No single metric reliably predicts churn. Customer health scores combine behavioral, sentiment, and financial signals into a single actionable score that helps customer success teams prioritize their efforts.
A well-designed health score gives you weeks or months of warning before a customer churns, turning reactive firefighting into proactive retention.
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How to Track in KISSmetrics
Use KISSmetrics to track the behavioral components: login frequency, feature breadth, key action completion, and support interactions. Combine these with financial data (payment history, expansion/contraction) and sentiment data (NPS, support satisfaction) to build a composite score.
Common Mistakes
- -Using too many input signals - start with 3-5 that you can validate
- -Not weighting signals based on their actual correlation with churn
- -Building a score and never validating it against actual churn outcomes
- -Updating scores too infrequently to be actionable
Pro Tips
- +Start simple: a traffic-light system (green/yellow/red) based on login frequency and key feature usage
- +Backtest your score against historical churn data before deploying it
- +Set up automated alerts when a previously healthy account drops to at-risk
- +Review and recalibrate your scoring model quarterly as your product evolves
Related Terms
Churn Rate
The percentage of customers or revenue lost over a given period. Customer churn measures account losses; revenue churn measures dollar losses.
Net Promoter Score (NPS)
A customer loyalty metric measured by asking "How likely are you to recommend us?" on a 0-10 scale. Scores range from -100 to +100.
Customer Effort Score (CES)
A metric that measures how easy it was for a customer to accomplish a specific task or resolve an issue, typically on a 1-7 scale from "Very Difficult" to "Very Easy."
Retention Analysis
Retention analysis measures the percentage of users who continue to return to and engage with a product over time, tracking how well a product sustains its user base beyond initial acquisition.
Further Reading
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