Analytics & Retention

DAU vs MAU

Also known asDaily vs Monthly Active UsersDAU MAU difference

DAU counts unique users active in a day; MAU counts them across a month. The same product reports both — and their ratio, DAU/MAU, is the standard stickiness metric.

Key takeaways

  1. 01DAU = unique users active in a single day; MAU = unique users active across a ~30-day window. A user counts once per window regardless of session count.
  2. 02DAU/MAU is the stickiness ratio — the share of monthly users active on an average day. ~14% is the catalog median; 50%+ is daily-essential territory.
  3. 03Headline DAU for high-frequency products (social, games, messaging); MAU is the fairer headline for low-frequency apps (travel, finance, utilities).
  4. 04Watch the trend, not the absolute number — and prefer trailing-28-day MAU over calendar-month MAU to remove month-length noise.

DAU and MAU are the two headline active-user counts, and they differ only in the window. [[dau]] (Daily Active Users) counts the unique users who opened the app on a given day; [[mau]] (Monthly Active Users) counts the unique users who opened it across a ~30-day window. In both, a user is counted once per window no matter how many times they returned — these are reach metrics, not session counts.

The same product reports both, and the revealing number is the ratio between them. DAU divided by MAU is the [[dau-mau]] stickiness ratio: of all the people who used the app this month, what share use it on an average day? A ratio of 0.2 means the typical monthly user shows up roughly 6 days a month; 0.5+ is daily-habit territory.

DAU vs MAU at a glance

DAUMAU
WindowA single dayA ~30-day rolling (or calendar) month
MeasuresDaily reach / habit intensityTotal monthly reach / audience size
Volatile?Yes — swings with weekday, campaigns, contentNo — smooths daily noise
Best forHigh-frequency apps (social, games, messaging)Low-frequency apps (travel, finance, utilities)

Neither is "better" — they answer different questions. DAU is about daily habit; MAU is about total reach. The ratio of the two is about stickiness.

Which one should you headline?

Match the metric to your usage frequency. A messaging app or a daily game lives or dies on DAU — if people do not open it most days the product is not working, and MAU would flatter a failing habit. A travel-booking app, a tax app, or an insurance app is naturally low-frequency: nobody books flights daily, so MAU is the honest reach number and a low DAU/MAU ratio is expected, not a problem.

The cardinal rule for both: watch your own trend, not the absolute number or a competitor's. Absolute DAU and MAU depend heavily on category, audience size, and ad spend, so cross-app comparisons mislead. A 5% month-over-month decline in your own DAU series is far more informative than how your number stacks against someone else's.

The 28-day vs calendar-month subtlety

"Monthly" is ambiguous. Calendar-month MAU varies with month length (28-31 days) and weekday alignment, injecting noise that has nothing to do with your product. Trailing-28-day MAU — every data point covering exactly 28 days — is the cleaner, more comparable definition, and it is what mature analytics teams use as the MAU denominator in the stickiness ratio. Most platforms (Amplitude, Mixpanel) expose both; pick one and stay consistent.

Quick answers

What is the difference between DAU and MAU?

DAU (Daily Active Users) counts unique users active in a single day; MAU (Monthly Active Users) counts unique users active across a ~30-day window. Both count a user once per window regardless of session count. DAU captures daily habit and is volatile; MAU captures total monthly reach and is smoother. The same app reports both.

What is a good DAU/MAU ratio?

DAU/MAU (stickiness) measures the share of monthly users active on an average day. Across the catalog the median is ~14%. Rough bands: utilities 5-15%, media 10-25%, social / productivity 30-60%, daily-essential apps (messaging, banking) 50%+. Compare to your own category and historical trend rather than a universal target — a low ratio is fine for low-frequency products.

Should I track DAU or MAU?

Both, but headline the one that fits your usage frequency. High-frequency products (social, games, messaging) should lead with DAU — daily return is the whole point. Low-frequency products (travel, finance, utilities) should lead with MAU, because daily use was never expected. Track the DAU/MAU ratio either way as your stickiness gauge.

Why use trailing-28-day MAU instead of calendar-month?

Calendar months vary in length (28-31 days) and weekday composition, which adds noise unrelated to product performance. Trailing-28-day MAU gives every data point an identical window, so changes reflect real user behavior rather than the calendar. It is the more rigorous choice and the standard denominator for the stickiness ratio.

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