Why WAU/MAU exists
Many B2B products are used weekly rather than daily (planning, reporting, reviews). WAU/MAU can be a more meaningful engagement signal than DAU/MAU for weekly cadence products.
Formula
WAU/MAU = WAU / MAU
Define 'active' before you compute anything
- Active should be a meaningful value event (not just a login).
- Keep the event definition identical for WAU and MAU; otherwise the ratio is meaningless.
- Use a threshold when needed (e.g., created >= 1 report) to avoid counting one-off clicks.
How to interpret WAU/MAU (rough ranges)
| Product cadence | What WAU/MAU suggests | Notes |
|---|---|---|
| Weekly workflow | Higher is expected | Planning/reviews naturally repeat weekly |
| Monthly workflow | Lower can be normal | Invoices and month-end close are lumpy |
| Mixed usage | Segment first | Blended averages hide power users vs casual users |
Measurement details that trip teams up
Rolling windows
WAU is often defined as unique actives in the last 7 days and MAU as unique actives in the last 28-30 days. If you use calendar weeks/months, the ratio will jump around due to boundary effects.
Cohorts and segments
Segment WAU/MAU by persona, plan, or acquisition channel. If you mix onboarding cohorts with mature cohorts, WAU/MAU can fall even when mature retention is stable.
How to improve WAU/MAU (without gaming it)
- Strengthen the weekly habit loop: reminders, templates, and recurring workflows.
- Reduce time-to-value for the weekly task (fewer steps, better defaults).
- Instrument and fix churn drivers: reliability, onboarding, and missing product value.
Common mistakes
- Using different active definitions for WAU vs MAU.
- Comparing segments with different cadences and calling one 'better'.
- Ignoring seasonality (weekly usage can spike around business cycles).
- Treating stickiness as a retention metric (it is an engagement proxy; cohorts still matter).