Product AnalyticsvsEngagement Metrics

Product analytics is the practice of measuring HOW users interact with your product to make better decisions. The core metric is DAU/MAU ratio (Daily Active Users ÷ Monthly Active Users), which measures 'stickiness' — how often users return. A 50%+ DAU/MAU means users open your product 15+ days per month (Facebook-like engagement). Most B2B SaaS lives at 15-25% DAU/MAU. Product analytics turns guesses into data: instead of 'users like feature X,' you know '34% of users use feature X, and those users have 60% lower churn.'

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.

The vanity metrics trap kills product teams. Tracking total signups, page views, or 'registered users' tells you nothing about product health. Twitter had 1B+ registered accounts but only 330M MAU — 67% of accounts were dead. Another trap: measuring too many metrics. Teams that track 50+ metrics end up acting on none. The best product teams track 3-5 core metrics obsessively. Amplitude's data shows teams with fewer than 10 tracked events make decisions 3x faster than teams tracking 100+.

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.

Set up a core event taxonomy with 5-8 key events that define your product's value delivery. For a SaaS tool: signup → activation (first 'aha' moment) → completed core action → returned within 7 days → invited team member → upgraded to paid. Track activation rate (% of signups who reach the 'aha' moment within 7 days) — this single metric predicts long-term retention better than any other. Target 40%+ activation rate.

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.