DAU/MAU (stickiness): definition, how to calculate, and benchmarks

DAU/MAU explained: what it measures, how to compute it correctly, and how to interpret stickiness for different product cadences.

Updated 2026-01-27

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What DAU/MAU measures

DAU/MAU is a stickiness metric: how many monthly active users are active on a typical day. It's useful for engagement tracking, but it depends heavily on how you define 'active' and your product's natural cadence.

Formula

DAU/MAU = DAU / MAU

How to use it

  • Keep a stable 'active' definition (e.g., key event) for comparability.
  • Track by segment (persona/plan) to avoid blended averages hiding issues.
  • Use WAU/MAU for weekly cadence products; DAU/MAU can be too noisy otherwise.

How to improve stickiness

  • Shorten time-to-value so new users return quickly.
  • Make core workflows habitual with reminders, templates, and defaults.
  • Remove friction in repeat actions (speed, saved state, permissions).

Benchmarks and caveats

  • Daily cadence products expect higher DAU/MAU than weekly or monthly tools.
  • Use a consistent active window (calendar day vs rolling 24 hours).
  • Compare within the same segment before comparing across products.

Stickiness QA checklist

  • Ensure DAU and MAU use the same event definition and filters.
  • Exclude internal users and test accounts from both numerators.
  • Deduplicate users across devices if possible.

Common mistakes

  • Comparing DAU/MAU across products with different usage frequency expectations.
  • Using DAU and MAU from different date ranges or definitions.
  • Treating stickiness as the only goal (retention and revenue still matter).

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