Product & User Engagement

Customer Health Score CHS

Customer Health Score is a composite metric that combines multiple behavioral, engagement, and relationship signals to produce a single score indicating how likely a customer account is to renew, expand, or churn. It synthesizes product usage data, support sentiment, NPS, executive engagement, and contract signals into an early warning system for customer success teams. High health scores correlate with expansion revenue; low scores predict churn risk.

Health score models should be trained on historical churn data and validated by tracking whether low-scoring accounts actually churn at higher rates than predicted.

Formula
Weighted composite of product engagement, support sentiment, NPS, and relationship signals
Where It Lives
  • GainsightIndustry-standard customer health scoring platform
  • TotangoCustomer success health score and SuccessPlay automation
  • MixpanelProduct usage data feeding health score models
  • SalesforceAccount health score integration with CRM data
What Drives It
  • Product usage frequency and depth (most heavily weighted)
  • Support ticket volume and recent negative sentiment
  • NPS score and qualitative feedback
  • Executive engagement and relationship quality
  • Contract renewal timeline proximity
Benchmark

Health score models should demonstrate 70%+ accuracy in identifying accounts that churn vs. those that renew within 90 days of score calculation.

Common Questions About Customer Health Score

What signals should be included in a customer health score?
The most predictive signals typically are: product login frequency and feature breadth of use (most important), support ticket volume and escalation rate, NPS score and qualitative themes, executive sponsor engagement and QBR attendance, usage trend direction (improving vs. declining over 30 days), and contract renewal date proximity. Weight each signal based on its historical correlation with renewal vs. churn outcomes in your customer base.
How do I validate a health score model?
Build the model on a training dataset of historical customer outcomes. Then test it on a holdout set: does the model correctly predict churn and renewal at meaningful accuracy? Track monthly whether accounts scoring red actually churn at higher rates than accounts scoring green. If the model is not predictive, review which signals are most correlated with actual outcomes and reweight accordingly. Models should be recalibrated at least annually.
What should trigger a CS intervention from the health score?
Tier your response by severity: accounts crossing from green to yellow should trigger an automated check-in email or CSM outreach within the week. Accounts crossing from yellow to red should trigger an immediate phone call from the CSM and escalation to the account's executive sponsor if appropriate. Accounts that have been red for more than 30 days approaching renewal should be escalated to VP-level intervention and an active save plan should be created.
How does product-led growth affect health score design?
In PLG companies, product usage signals are even more central to health scoring because the product is the primary delivery mechanism of value. Track not just logins but key feature completion rates, collaborative usage (multiple users from the account), usage trend momentum (is adoption growing within the account?), and proximity to natural upsell trigger points. In PLG, health score data also feeds the sales team's expansion pipeline.
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