Business context
Why Monthly Active Users matters
Rising MAU indicates broader monthly reach, but the cause may be acquisition rather than stronger retention. Falling MAU warrants checking both new and returning user movement.
- Business question
- How many unique users meaningfully engage with the product over a month?
- Teams that use it
- Product, growth, finance, customer success, and leadership teams.
- Decisions it supports
- Reach and adoption reporting, capacity planning, growth analysis, customer health, and engagement strategy.
Calculation
Monthly Active Users formula
Total Unique Users Per Month
Formula components
- Unique users
- Deduplicated users with at least one qualifying active event in the monthly window.
- Active event
- The agreed behaviour representing meaningful product use.
- Monthly window
- Either a calendar month or a rolling 30-day period, used consistently.
How to calculate Monthly Active Users
- Choose the active event and whether the metric uses calendar or rolling months.
- Collect valid events in the full window.
- Resolve identities and exclude test, bot, or staff activity where appropriate.
- Count distinct qualifying users once for the whole window.
Worked example
Monthly Active Users example
During July, an application records at least one core action from 42,600 distinct valid users.
- Measurement window = 1–31 July.
- Active event = completed core action.
- Unique users across the full month = 42,600.
MAU for July is 42,600.
A total of 42,600 unique users were meaningfully active at least once in July; repeat days do not create additional users.
How to interpret the result
Decompose MAU into new, retained, resurrected, and churned users. That movement explains whether growth is durable or dependent on continuous acquisition.
Calendar MAU and rolling 30-day MAU are not interchangeable. Product cadence, seasonality, user role, and active-event choice also shape the level.
Common mistakes and limitations
- Summing DAU
- Adding daily counts duplicates users active on multiple days.
- Mixing window types
- Calendar months have different lengths; rolling windows move every day.
- Using all registered users
- MAU includes only users meeting the active rule in the window.
- Ignoring identity stitching
- Anonymous and signed-in records can represent the same user.