Step-by-Step Guide

How to Calculate DAU, MAU, and Stickiness

Four steps to calculate daily active users, monthly active users, and the DAU/MAU stickiness ratio. Formula, 2024 benchmarks, and tips for product managers.

Last updated: April 2026

1
Define what "active" means for your product

DAU and MAU are only useful if everyone on the team agrees on which event counts as active. Pick the action that signals real value, not a passive ping.

For a chat app, sending or reading a message.
For a finance app, opening a balance or running a transaction.
For a B2B tool, completing a job-to-be-done such as creating a record.
Avoid background sync, push opens, or app foreground without action.

Formula

Active user = unique user who fired the chosen value event in the time window

Pro tip: Write the definition down in a one-pager and pin it. Drift in the active-user definition is the most common reason DAU/MAU charts mislead the team.

2
Count distinct users per day to get DAU

DAU is the number of unique users who fired the active event on a given day. The unit of analysis is the user, not the session, so de-duplicate.

Pull the event log for one calendar day in your product timezone.
Filter to your defined active event.
De-duplicate by user ID so each user counts once.
Repeat for a 7- or 28-day rolling window to spot trends.

Formula

DAU(day) = count of distinct user IDs that fired the active event on that day

Pro tip: For B2B products with weekend drops, report DAU on a weekday-only basis or use a 7-day rolling average. A flat DAU chart with weekly seasonality is harder to read than a smoothed one.

3
Count distinct users in a 30-day rolling window to get MAU

MAU is the number of unique users active across the trailing 30 days. Use a rolling window so the metric updates daily, not just at month-end.

Pull the event log for the trailing 30 days from any reference date.
Filter to your active event.
De-duplicate by user ID across the full 30-day range.
Treat it as a rolling cohort that updates every day.

Formula

MAU(date) = count of distinct user IDs active on any of the prior 30 days

Pro tip: Calendar-month MAU and rolling 30-day MAU are different metrics. Pick one and stay consistent. Most analytics tools default to rolling.

4
Divide DAU by MAU to get stickiness

The stickiness ratio is just DAU divided by MAU, expressed as a percentage. It tells you what fraction of your monthly users come back on any given day.

Pick a single reference date.
Pull DAU for that day and MAU for the trailing 30 days ending on that date.
Divide DAU by MAU and multiply by 100.
Example: 4,000 DAU and 20,000 MAU = 20% stickiness.

Formula

Stickiness = (DAU / MAU) x 100%

Pro tip: Compare against the right benchmark. Mixpanel's 2024 Benchmarks report puts average stickiness at roughly 37% across all industries (the older 13% figure reflected B2B SaaS specifically). Social and messaging apps typically run 50-70%, productivity tools 25-45%, fintech or e-commerce 15-30%.

Calculate Your Stickiness Ratio

Skip the SQL. Use our free DAU/MAU calculator with built-in benchmarks, trend tracking, and category comparisons.

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Frequently Asked Questions

What is a good DAU/MAU stickiness ratio?

It depends on the product category. Mixpanel's 2024 Benchmarks report puts the all-industry average at roughly 37% (the older 13% figure reflected B2B SaaS specifically). Social and messaging apps often hit 50-70% because the use case is multiple-times-per-day. Productivity tools land in the 25-45% range. Fintech and e-commerce typically run 15-30% because users don't need to log in every day. Twenty percent is a common rule of thumb for healthy consumer apps, but check the benchmark for your category before celebrating or panicking.

Should I use rolling 30-day MAU or calendar-month MAU?

Rolling 30-day MAU is the modern default because it updates every day and avoids end-of-month spikes. Calendar-month MAU still appears in older reports and investor decks. Whichever you pick, lock it in across the team and don't switch mid-quarter.

What event should count as "active"?

The event that signals the user got value. For a chat app, that's sending or reading a message. For a CRM, it's logging activity or updating a record. Avoid passive events like app foreground or push-notification delivery, which inflate the numbers without reflecting real engagement.

Can DAU/MAU mislead me?

Yes. A user who logs in once a month for two seconds counts the same as a user who comes back daily. Pair stickiness with retention curves, session length, and key-action completion to get a fuller picture.

How does DAU/MAU relate to retention?

Stickiness is a same-window snapshot. Retention curves track cohorts over time. A high DAU/MAU with a steep retention drop tells you new users churn fast even though current users come back often. Track both.