Engagement MetricsvsCustomer Health Score
A side-by-side breakdown of Engagement Metrics and Customer Health Score — what they measure, common mistakes, and when to use each one.
The Concept
Engagement metrics measure how actively and deeply users interact with your product. The most important is the DAU/MAU ratio (Daily Active Users ÷ Monthly Active Users), also called the 'stickiness ratio.' A 50% DAU/MAU means half your monthly users come back every day. Facebook's DAU/MAU is 66%, making it one of the stickiest products ever built. For SaaS, a 13-20% DAU/MAU is average, 20-30% is good, and 30%+ signals exceptional engagement that predicts strong retention.
A Customer Health Score is a composite metric (typically 0-100) that predicts whether a customer will renew, expand, or churn. It combines product usage data (login frequency, feature adoption), engagement signals (support tickets, NPS responses), and business outcomes (ROI achieved, time-to-value). Gainsight data shows that accounts scoring above 80 renew at 96%, while accounts below 40 churn at 55%. Proactively reaching out to at-risk accounts can save 20-30% of them.
The Trap
The trap is tracking surface-level engagement (page views, sessions) instead of meaningful engagement (core actions completed). A news site with 10 million page views but 2-minute average session time has shallow engagement — users skim headlines and leave. A project management tool with 500K sessions where users create tasks, assign team members, and complete workflows has deep engagement. Vanity engagement metrics (views, clicks) correlate poorly with retention; value-delivered metrics (workflows completed, goals achieved) correlate strongly.
The trap is building a health score based on vanity metrics like 'total logins' instead of value-delivered metrics like 'completed workflows.' A customer logging in daily to export data to a spreadsheet (because your reporting is broken) looks 'healthy' by login frequency but is actively seeking alternatives. Similarly, weighting NPS too heavily ignores that a promoter (NPS 9) with declining usage is more at-risk than a passive (NPS 7) with increasing usage.
The Action
Define your 'engagement stack' — 3 tiers of user engagement: (1) Passive: user logged in / opened the app. (2) Active: user performed a core action (sent a message, created a document, ran a report). (3) Power: user used advanced features or collaborated with others. Calculate DAU/MAU and track all three tiers separately. Target: at least 40% of MAU should be 'Active' tier. Set engagement alerts: if a user drops from Power to Passive, trigger a Customer Success touchpoint within 48 hours.
Build a weighted health score with 3 categories: (1) Product Engagement (40% weight): DAU/MAU ratio, core feature usage, breadth of feature adoption. (2) Relationship Signals (30%): NPS/CSAT trend, support ticket sentiment, executive sponsor engagement. (3) Business Outcomes (30%): ROI achieved vs promised, time-to-value, expansion usage. Score each 0-100, weight and combine. Set alerts: Green (70+), Yellow (40-69), Red (0-39). Review all Red accounts weekly with a playbook for intervention.
Formulas
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