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DAU/MAU (Stickiness) Calculator

Compute DAU/MAU stickiness and translate it into implied active days per month.

DAU/MAU is a common stickiness metric: how frequently monthly active users are active on a typical day.

It's useful for product engagement, but it depends on how you define 'active' and can vary widely by product type.

Prefer an explanation- Read the guide.
Related definitions:daumaustickiness
DAU/MAU (stickiness): definition, how to calculate, and benchmarksPLG metrics hub: activation, trial conversion, stickiness, and adoptionWAU/MAU: a weekly stickiness metric for B2B and weekly workflowsRetention & churn hub: cohorts, GRR/NRR, and retention curves
 
 
Set 0 to disable target calculation.
%
Tip: you can type commas (e.g., 10,000).

Example

Using the default inputs, the result is:
15%
DAU
1,200
MAU
8,000
Target DAU/MAU (optional)
20%

How to calculate

  1. Enter DAU and MAU for the same period and same 'active' definition.
  2. Review DAU/MAU and implied active days per month.

Formula

DAU/MAU = DAU / MAU
  • DAU and MAU use the same 'active' definition and time period.
  • Implied active days per month uses a 30-day approximation.

FAQ

What is a good DAU/MAU-
It depends on product cadence. Daily tools can be 20-60%+; weekly workflows may be lower. Track trends and segment by persona/plan for actionability.
Should I use WAU/MAU instead-
If your product is naturally weekly (not daily), WAU/MAU can be a better stickiness metric and less noisy than DAU/MAU.

Common mistakes

  • Using inconsistent 'active' definitions (sessions vs key event).
  • Comparing across products with different usage cadences (daily vs weekly).
  • Using DAU and MAU from different date ranges.

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Quick checks

  • Keep time units consistent (monthly vs annual) across inputs and outputs.
  • Segment by cohort/channel/plan before trusting a blended average.
  • Use the related guide to avoid common definition and denominator mismatches.