DAU/MAU

DAU/MAU is a ratio that divides your Daily Active Users by your Monthly Active Users to produce a stickiness score between 0 and 1 (or 0% to 100%). It answers a simple but powerful question: of all the people who use your product in a month, what percentage use it on any given day?

Why it matters: DAU/MAU is one of the strongest indicators of product-market fit and habitual usage. A ratio of 50% means that on any given day, half your monthly users show up. That signals a product woven into daily routines. Facebook historically maintains a DAU/MAU above 65%. Most B2B SaaS products land between 15-30%. Anything above 25% for a B2B tool is considered strong. The benchmark depends heavily on category: a daily communication tool should be much higher than a quarterly reporting tool.

How to calculate: define "active" clearly first. Is it any login, or does it require a meaningful action? For a messaging app, sending a message is active. For an analytics platform, running a query or viewing a dashboard is active. Simply opening the app and closing it should probably not count. Once defined, the math is simple: DAU on a given day / MAU for the 28-day window containing that day.

Deeper analysis: track the trend over time, not just the snapshot. A declining DAU/MAU with stable MAU means users are visiting less frequently, even if they have not fully churned yet. This is an early warning signal. Also segment by user type: new users, power users, and reactivated users may have very different stickiness patterns.

Common mistakes: using DAU/MAU as a vanity metric without understanding what drives it. A high ratio from compulsive notification design is not the same as a high ratio from genuine value delivery. Another mistake is comparing your ratio to companies in completely different categories. A payroll system used biweekly should not benchmark against a daily chat tool.

Tools like Amplitude and Mixpanel calculate DAU/MAU natively. In GA4, you can approximate it using active users metrics, though the definition of "active" differs from product analytics tools.

Practical example: a project management tool has a DAU/MAU of 18%. They add a daily standup feature that prompts users to log a quick status update each morning. Over three months, DAU/MAU climbs to 31%, and correlated retention improvements show in their cohort analysis.