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WAU/MAU Calculator

Compute WAU/MAU and translate it into implied active weeks per month.

WAU/MAU measures weekly engagement within the month and is often better for products with weekly usage cadence.

It reduces daily noise and can align better with weekly workflows and B2B usage patterns.

Prefer an explanation- Read the guide.
Related definitions:waumaustickiness
WAU/MAU: a weekly stickiness metric for B2B and weekly workflowsPLG metrics hub: activation, trial conversion, stickiness, and adoptionDAU/MAU (stickiness): definition, how to calculate, and benchmarksRetention & 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:
37.5%
WAU
3,000
MAU
8,000
Target WAU/MAU (optional)
50%

How to calculate

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

Formula

WAU/MAU = WAU / MAU
  • WAU and MAU use the same 'active' definition and time period.
  • Implied active weeks per month uses a 4.33-week approximation.

Benchmarks

  • Higher WAU/MAU usually implies a tighter weekly habit (stickiness), but expectations vary by product type.
  • Compare WAU/MAU by segment (plan, team size, use case) to find where engagement is strongest.
  • Track WAU/MAU alongside retention; stickiness without retention can still be fragile.

FAQ

When should I use WAU/MAU instead of DAU/MAU-
Use WAU/MAU when usage is naturally weekly (e.g., planning, reporting). It's often a more stable signal than DAU/MAU for weekly cadence products.
Can WAU/MAU be above 100%-
No, not with consistent definitions. If it happens, it usually indicates you're using mismatched denominators or date ranges.

Common mistakes

  • Mixing different 'active' definitions between WAU and MAU.
  • Comparing across segments with different usage frequency expectations.
  • Using WAU from a different month than MAU.

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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.