How MAU is calculated
Monthly active users is the number of unique users active at least once in a monthly window:
MAU = count of unique users active in the 30 days ending on day D
A worked example: in September, 410,000 unique users open your app at least once. September MAU is 410,000. If average DAU in September was 82,000, stickiness is 82,000 / 410,000 = 20%.
As with DAU, "active" needs a written definition. An app open, a sign-in, or a meaningful action all give different results. The same definition should drive DAU, MAU and the stickiness ratio.
How MAU changes month to month
MAU moves with three flows:
MAU this month = MAU last month - churned users + new users + resurrected users
Say August MAU was 400,000. In September, 90,000 of those users did not return, 85,000 new users arrived, and 15,000 users who were inactive in August came back. September MAU is 400,000 - 90,000 + 85,000 + 15,000 = 410,000. Net growth looks modest, but the gross flows show heavy churn masked by acquisition. That breakdown is where growth and product teams find their work.
MAU pitfalls
- Counting devices instead of people. Reinstalls and multiple devices can count one person twice unless you deduplicate on a user ID.
- Loose activity definitions. Background refreshes or push receipts should not count as activity.
- Acquisition spikes. A big campaign month inflates MAU with users who never return. Compare MAU with retention and revenue.
- Pricing tied to MAU. Some vendors bill by MAU, so a loose definition can also raise costs.
MAU and acquisition quality
MAU tells you how big your active audience is; attribution tells you where it came from. Linkrunner attributes installs to their source, re-attributes reinstalls, and reports retention by campaign at D1, D7, D14 and D30, so you can see which campaigns keep adding to next month's MAU and which only fill this month's. Linkrunner bills by attributed install, not by active user; see pricing.