The DAU/MAU ratio divides daily active users by monthly active users to show how often your monthly users come back. A ratio of 20% means the average monthly user is active about six days a month. Daily-habit apps such as messaging and social aim high, while apps used occasionally, such as travel or tax tools, naturally score lower. Use it as a trend for your own app and category, alongside retention cohorts, rather than as a universal score.
How to calculate DAU/MAU
Daily active users (DAU) is the number of unique users active on a given day. Monthly active users (MAU) is the number of unique users active during the trailing 30 days. Divide the average DAU over a period by MAU for the same period. If you average 15,000 DAU and have 75,000 MAU, the ratio is 20%.
Define active consistently. An app open is the simplest definition, but a meaningful action, such as sending a message or completing a lesson, gives a truer view of engagement. Use the same definition for DAU and MAU, and avoid changing it mid-year, or trends become meaningless.
What the ratio tells you
DAU/MAU measures frequency: how many days in a month the typical active user returns. A ratio near 50% means users come back roughly every other day, which is typical of strong daily habits. A ratio near 10% means users visit about three days a month, which may be perfectly healthy for an app with occasional use cases.
The ratio is most useful as a trend. A rising ratio means users are forming stronger habits; a falling ratio can signal declining value, notification fatigue, or a growing share of new users who have not yet formed habits. Investigate changes rather than reacting to a single month.
Benchmarks depend on the category
Communication and social apps aim for daily use, so they target high ratios. Games vary by genre, with casual daily-reward games often higher than premium narrative games. Productivity, fitness, and learning apps sit in the middle, depending on whether the product is designed for daily practice. Shopping, travel, finance, and utility apps are often lower because people use them when a need arises.
Instead of chasing a universal number, compare your ratio with your product's intended usage frequency. If your app is meant to be a daily habit and the ratio is low, there is a gap. If it is a weekly tool, a ratio around 15 to 25% may already reflect healthy engagement. Pair the ratio with retention rate for a fuller picture.
Limitations to keep in mind
DAU/MAU can be distorted by growth. A big acquisition push adds many new monthly users who have not yet formed habits, which lowers the ratio even if existing users are more engaged than ever. Segment by cohort or tenure to separate new-user effects from changes in core engagement.
The ratio also hides who is engaged. A small group of power users can keep it high while most users drift away. Look at the distribution of active days per user, and track weekly active users (WAU) for products with weekly rhythms. Our guide to cohort analysis shows how to break engagement down.
How to improve stickiness
Design for a natural cadence. Daily reminders, streaks, fresh content, and social features encourage frequent use when they fit the product. Personalized feeds and progress tracking give users reasons to return. Widgets and notifications can bring users back for quick, valuable interactions.
Avoid forcing frequency where it does not fit. A budgeting app that nags users daily may annoy them; a weekly summary may be better. Use push notifications and in-app features that match how users want to engage, and test changes against retention and uninstall rates, not just DAU.
Stickiness and ASO
Stickier apps tend to earn more ratings, better reviews, and more word of mouth, all of which support store conversion and visibility. Engagement signals may also feed store algorithms indirectly. A listing that attracts users who match the product's intended use improves stickiness from day one.
That is why ASO and product teams should share engagement data. If users acquired through a particular keyword theme show low stickiness, the listing may be attracting the wrong audience. Our ASO KPIs guide explains how to connect store metrics with post-install engagement.
Common DAU/MAU mistakes
Comparing your ratio to a social network's benchmark when your app is a monthly tool is the classic mistake. Another is using inconsistent definitions of active, such as counting background sessions or push-triggered opens that did not involve real use, which inflates numbers.
Teams also celebrate a higher ratio caused by declining MAU: if casual users leave, the remaining users look more engaged even though the business is shrinking. Always look at DAU, MAU, and the ratio together, plus revenue and retention.
A worked example: a fitness app's stickiness
A fitness app reports a DAU/MAU of 12% and wants to reach daily-habit levels. Segmenting shows that users who joined a structured four-week plan have a ratio near 35%, while users who browse workouts freely sit near 7%. The plan users also retain far better.
The team makes plan selection part of onboarding, adds a weekly schedule widget, and sends reminders only on planned workout days. Over three months, the overall ratio rises to 18%, day-30 retention improves, and ratings mention the plans as a favorite feature. The app is used more without sending more notifications.
How to do it, step by step
- Define active usersChoose a meaningful action that reflects real use and apply it consistently to DAU and MAU.
- Calculate the ratio over timeCompute average DAU divided by MAU monthly, and plot the trend.
- Set expectations by usage frequencyDecide how often users should naturally use the product and compare the ratio with that rhythm.
- Segment by cohort and behaviorSeparate new and tenured users, and compare engaged features or plans.
- Test engagement featuresAdd habit-forming features that fit the product and measure ratio, retention, and uninstalls together.
Before and after examples
Illustrative examples written for a generic app in this category, not client results. Swap in your own product, audience, and data.
Any app open, including background refresh.
Completed at least one workout or logged one meal.
Why it works: Action-based definitions reflect true engagement.
Our 12% ratio is far below Facebook, so we are failing.
Plan users are at 35%; browsers at 7%. Steer more users into plans.
Why it works: Segmenting turns a number into a decision.
Send a daily push to every user.
Remind users only on planned workout days and add a schedule widget.
Why it works: Fitting the product's rhythm raises frequency without fatigue.
Action plan
- Define active as a meaningful action
- Track DAU, MAU, and the ratio together
- Judge the ratio against intended usage frequency
- Segment by cohort and tenure
- Build habit features that fit the product
- Share engagement data with ASO teams
Metrics to monitor
- DAU/MAU ratio trend
- Active days per user distribution
- WAU/MAU for weekly products
- Retention by engagement segment
- Uninstall rate after engagement campaigns
Record the baseline, release date, audience, markets, and external changes before interpreting movement. Rankings and conversion are useful signals, but a decision is stronger when activation, retention, and business value confirm that the page attracted the right users.
Frequently asked questions
What is a good DAU/MAU ratio?
It depends on the category and intended usage. Daily-habit apps aim high, while occasional-use apps can be healthy at lower ratios. Track your trend and compare with similar apps.
How do you calculate DAU/MAU?
Divide average daily active users by monthly active users for the same period. For example, 15,000 DAU divided by 75,000 MAU is 20%.
Why did my DAU/MAU drop after a marketing campaign?
New users increase MAU before they form habits, which lowers the ratio. Segment by cohort to see whether core engagement changed.
Is DAU/MAU better than retention?
They answer different questions. Retention shows how many users stay; DAU/MAU shows how often active users return. Use both.
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