Product AnalyticsvsChurn Rate

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.'

Churn rate measures the percentage of customers who cancel or stop paying during a given time period. It is the silent killer of SaaS businesses — even a small monthly churn compounds into massive annual losses. A 5% monthly churn sounds manageable, but compounded over 12 months, you lose 46% of your customer base. To maintain the same revenue, you need to acquire enough new customers to replace nearly HALF your base every year. This is why the best SaaS companies obsess over churn — Slack's monthly churn below 1% means they retain 89% of customers annually, creating a compounding revenue machine.

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 only 'logo churn' (customers lost) and ignoring 'revenue churn' (revenue lost from downgrades). You could have 3% logo churn but 8% revenue churn if your largest customers are downgrading. Revenue churn is more dangerous because it hits your top line harder. The second trap: calculating churn from the wrong denominator. Always use start-of-period customers, not end-of-period or average. Using end-of-period inflates your denominator and makes churn look artificially low.

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.

Calculate two churn metrics monthly: Logo Churn = Customers Lost ÷ Start-of-Month Customers × 100. Revenue Churn = MRR Lost (cancellations + downgrades) ÷ Start-of-Month MRR × 100. Implement an exit survey on your cancellation page to identify the #1 reason people leave — the top reason is usually fixable. Target: under 5% monthly for SMB SaaS, under 2% for mid-market, under 1% for enterprise.