What Is MAU in Mobile Games? How to Calculate the DAU/MAU Ratio, Genre Benchmarks, and When the Number Misleads

MAU (monthly active users) is the number of unique users who open a game at least once during a set window, usually 28 or 30 days. Dividing DAU (daily active users) by MAU gives the DAU/MAU ratio, which shows what share of this month's players come back on an average day; the industry calls it stickiness. A DAU/MAU of 20% means the typical monthly player opens the game on about 6 of every 30 days.

The definition is simple; comparing the numbers is not. Google Play Console counts MAU over a rolling 28-day period, while Google Analytics 4 (GA4) uses the last 30 days. Published DAU/MAU figures for games range from an 11.8% median for US iOS apps to 32% among mobile game products tracked by one analytics vendor, nearly a threefold spread. Gather the public data available as of October 2026 and the picture is consistent: DAU/MAU can only be compared within the same definition and the same population, and it moves sharply in the same game depending on retention and the mix of new users.

The definition of DAU itself is covered in What is DAU? The Key Metric Connecting Mobile App Growth and Ad Performance, and DAU by genre in DAU by Game Genre: The Complete 2026 Guide to Daily Active Users in Mobile Gaming. This post covers the denominator, MAU, and the ratio between the two.

What Does MAU Actually Count in a Mobile Game?

MAU is the number of unique users who were "active" at least once within a defined window, and the same game produces different numbers depending on whether that window is 28 days, 30 days, or a calendar month, and on what counts as active.

Start with the window. Google defines Play Console's DAU/MAU as the ratio of users who open your app each day versus each month, using a 28-day rolling period, and calls it a key measure of stickiness. GA4's DAU/MAU metric, by contrast, divides users who engaged on a given calendar day by users who engaged in the last 30 days. Financial reporting often uses calendar months or quarterly averages. The longer the window, the more people fall into it at least once, so MAU grows and DAU/MAU shrinks. Put a 31-day calendar-month MAU next to a 28-day MAU and the ratio differs before anything about the game has changed.

The 28-day window is popular because it is exactly four weeks, so every window contains the same mix of weekdays. Games see different traffic on weekends and weekdays, and calendar months that alternate between four and five weekends make month-over-month trends wobble for reasons that have nothing to do with engagement.

Then there is the definition of active. Even for the same day, what gets counted changes the number.

Play Console counts an app open as activity, while GA4 requires a session that clears its engagement bar. Roblox counts accounts, not people, and its filing states plainly that because one person can use several accounts, DAU is not a measure of unique individuals. Before comparing an internal dashboard with any external benchmark, confirm which definition your own number uses.

How Do You Calculate and Read the DAU/MAU Ratio?

DAU/MAU is the average DAU over a period divided by the MAU for that same period, and multiplying it by the number of days in the window turns it into the average number of days each monthly active user showed up.

The formula is DAU/MAU = average DAU ÷ MAU × 100. If 200,000 unique users played at least once over 30 days and average DAU across those 30 days was 36,000, DAU/MAU is 18%.

Converting the ratio into days makes it far more intuitive. Adding up DAU across 30 days gives the same total as adding up each user's active days. So average DAU divided by MAU is exactly equal to the average number of active days per monthly user, divided by 30. The 18% in the example means monthly players came in on 5.4 of 30 days on average; 20% means 6 days, and 30% means 9. Before asking whether a ratio is good or bad, rephrase it as "how many days a month do our players come back?" That question is much easier to compare against how a genre is actually played.

Two cautions apply. First, using a single day's DAU instead of the period average gives a different answer. Dividing one day's DAU by trailing 30-day MAU, as GA4 does, spikes on event days and weekends and dips on weekdays; for trend lines, the period average is more stable. Second, shortening the window to 28 days shrinks the denominator and nudges the ratio up for the same game. If 28-day MAU in the example were 190,000, the ratio would be about 18.9% (an illustrative assumption).

DAU/MAU also connects directly to revenue. As covered in Revenue = DAU × ARPDAU: The Daily Metric That Separates Real Growth From Install Spikes, daily revenue is DAU × ARPDAU, so monthly revenue can be written as MAU × DAU/MAU × days × ARPDAU. With 200,000 MAU, 18% DAU/MAU, and $0.12 ARPDAU, 30-day revenue is about $129,600. Hold MAU and ARPDAU constant and lift DAU/MAU to 21%, and revenue rises to about $151,200, an increase of 16.7%. That gain comes without a single new user, just from existing players coming back about one more day a month.

What Is a Good DAU/MAU Ratio by Genre?

Based on public data as of October 2026, mobile game DAU/MAU clusters roughly between 10% and 25%, with short, daily-habit genres such as puzzle, board, card, and word games at the higher end. However, there is effectively no recent dataset that publishes genre-level distributions with its source and population disclosed, so the table below places figures from different periods and populations side by side.

A few notes on reading the table. The most recent figures with a stated population come from MWM's US iOS data: an 11.8% median for games and 23.9% for the top 10%. In the same dataset, the median across all apps is 14.1%, which makes games one of the less sticky categories at the median. A large share of games are played briefly right after launch and then forgotten.

Genre differences show up more clearly in older data. In GameAnalytics data covering January 2016 to September 2017, card, board, and word games led with averages of 14% to 16%, while most other genres averaged below 10%. A follow-up covering more than 75,000 games from June 2018 to May 2019 put the market median at about 8% and the top 15% at about 19%, with board, card, puzzle, and word games in the lead above 20%. Figures published in 2020 put idle games at 18% and hyper-casual at 10.5%. Hyper-casual games are built for intense play right after install followed by fast churn, so active days per month stay low.

Individual titles show where the ceiling sits. Hungry Studio announced in January 2026 that its block puzzle game Block Blast had reached 70 million DAU and 300 million MAU, which works out to about 23%. That even one of the largest puzzle games in the world sits around 25% is a useful reference point.

Midcore, RPG, and strategy have the least public data. Stillfront, a Swedish listed publisher whose key franchises include strategy games (Supremacy, Empire) and an MMO (Albion), reported 6.70 million DAU and 33.6 million MAU for Q2 2026, or about 20%. Because that is a portfolio-wide figure mixing several genres, it is better treated as a reference than as a midcore benchmark. GameAnalytics reports that midcore titles lead on frequency at six to seven sessions per day, but that measures sessions within a day, while DAU/MAU measures days within a month. The two should not be confused.

Casino-style titles appear as the stickiest genre in past GameAnalytics data, but because they are gambling-adjacent and behave differently from general game benchmarks, they are excluded from this table.

Why Do DAU/MAU Benchmarks Disagree So Much?

DAU/MAU benchmarks diverge mainly because their populations, aggregation methods, and window definitions all differ, and the widely quoted "20% is good, 30% is best-in-class" rule has been called out as having no measured gaming data behind it.

First, the populations differ. GameAnalytics' PC figure (a 4–5% median) covers 3,582 PC games with at least 100 MAU, which pulls in very small titles. MWM looks only at US iOS apps above a download and DAU threshold. Mixpanel's 32% comes from products at companies that pay for an analytics platform, which tend to be games with established teams and data practices. Change which games are in the sample and the same metric can differ several times over.

Second, the aggregation differs. A median gives every game equal weight, so the long tail of small games drags it down. An average pooled across devices or users is driven by the largest games with the most players. Mixpanel does not explain how it aggregates, but a figure pooled across more than 800 million devices would inevitably lean toward big titles. Comparing a top-10% or top-1% figure against a median is another common mistake.

Third, windows and definitions of active differ. Whether a source uses a rolling 28 days, the last 30 days, a calendar month, or a quarterly average, and whether an app open is enough or an engaged session is required, changes both numerator and denominator. As shown earlier, switching from 28 to 30 days alone shifts the ratio.

Fourth, the rules of thumb have unclear origins. The idea that a strong mobile game sustains a DAU/MAU above 0.2 appears in a Game Developer article as far back as 2013. Yet Game Growth Advisor, which maintains a widely cited mobile game KPI benchmark page, stated in its August 2026 update that the commonly repeated 20% and 30% thresholds have no measured population behind them for mobile games, and that it could not find a primary gaming dataset publishing a DAU/MAU distribution. That does not make 20% wrong, but the case for using it as a target is weaker than its popularity suggests.

The safest approach is to use external benchmarks only to check whether a game is far off the market, and to set real targets from the game's own history measured on one consistent definition, or from titles of a similar genre within your own portfolio.

How Does DAU/MAU Relate to D1, D7, and D30 Retention?

DAU/MAU is the combined result of how often existing players return and how many new users are mixed into MAU, and the retention curve drives both.

On the retention side, GameAnalytics' 2026 benchmarks, as summarized by GameDev Reports, put mobile D1 retention for the top 25% of games just above 30%, and median D7 retention just under 4%. Most people who install a game stop opening it within a week. Retention bands and how to read the curve are covered in detail in D1/D7/D30 Retention Benchmarks for 2026: What Good Looks Like and How to Read Your Own Curve.

A simple calculation shows what this does to DAU/MAU. Suppose 140,000 established players stay active through the month and play on 7 of 30 days on average. Average DAU is about 32,667 and DAU/MAU about 23.3%. Now add 60,000 new installs in the same month who play an average of 1.5 days before churning. Average DAU rises 9% to about 35,667, but MAU becomes 200,000 and DAU/MAU falls to about 17.8% (illustrative assumptions). New users raise DAU while lowering the ratio.

That is why DAU/MAU should always be split into new and existing users. When the blended ratio drops, the response depends entirely on the cause: a larger share of new users from scaled UA, or existing players coming back less often. The first calls for onboarding and first-week design to improve new-user D1 and D7; the second calls for content and LiveOps that give existing players a reason to return every day.

When Does a High DAU/MAU Mislead?

If DAU/MAU rises while MAU or DAU falls in absolute terms, the game may not have improved at all; lighter users may simply have left and shrunk the denominator. The ratio should always be read alongside absolute DAU and MAU.

The first case is a base that has narrowed to loyal players. Stillfront's filings show DAU of 7.29 million and MAU of 39.8 million in Q2 2025, against 6.70 million and 33.6 million in Q2 2026. DAU fell about 8%, but MAU fell about 16%, so DAU/MAU rose from about 18.3% to 19.9%. The company attributed the decline in users to a continued shift of user acquisition toward its key franchises. If that is the intended strategy, there is no problem, but concluding from the ratio alone that engagement improved would miss the shrinkage. The same illusion appears late in a game's life, when MAU erodes down to the core audience.

It works in the other direction too. Block Blast grew from 40 million DAU and 160 million MAU in December 2024 (about 25%) to 70 million DAU and 300 million MAU in January 2026 (about 23%). DAU grew 75% while the ratio went down. A fast-growing game pulls in more low-frequency users, so a falling ratio is natural and is not, on its own, a sign of declining health.

The second case is single-day spikes from events and UA campaigns. When one day's DAU is divided by trailing 30-day MAU, the ratio jumps on major event days and update launches. The 2013 Game Developer article also warned that the ratio is skewed upward while a UA campaign runs, so comparisons between games need care. On campaign days, new installs land in DAU all at once; after they churn, they stay in MAU for 28 to 30 days and pull the ratio down a few weeks later. For months with events or campaigns, read the period average, split into new and existing users, not a single day.

The third case is bots and multiple accounts. In its FY2025 10-K, Roblox disclosed that DAU measures account activity and is not a count of unique individuals, and that undetected fraud and unauthorized access may contribute to an overstatement of DAU. In games with rewards attached, or in markets with heavy emulator use, accounts that log in automatically every day can push DAU/MAU above reality. If a ratio sits noticeably above its genre's range, check device, IP, and session-length distributions alongside it.

How Should You Raise DAU/MAU?

The core of raising DAU/MAU is giving players a reason to open the game today; pushing more notifications or loosening the definition of active only moves the number, not revenue or retention.

The most direct lever is goals that reset daily. Daily quests, consecutive login rewards, and energy or reward chests that refill on a daily cycle all add active days. If the rewards are too generous, though, players start logging in without playing, so daily goals work best when they require at least one pass through the core loop.

The second lever is LiveOps cadence. Weekly events, seasons, and limited-time content running on a steady rhythm create something players should not miss this week, which shortens the gap between visits. Social mechanics that involve commitments to other players, such as guild raids or co-op missions, pull people back daily more strongly than solo content. Specific MAU retention tactics are covered in How to Retain MAU in Mobile Games: Proven Strategies for 2026.

The third lever is measurement. Tracking DAU/WAU and WAU/MAU alongside DAU/MAU separates weekly habits from monthly churn, and GA4 provides all three out of the box. Whether an increase is worth anything should be judged by whether ARPDAU and D30 retention moved with it. If active days rose but ARPDAU fell, the likely explanation is more visits that collect a reward and leave.

External channels affect visit frequency as well. Players who arrive through a structure that keeps rewarding playtime or daily attendance after install have a reason to come back across multiple days, unlike a one-time install. Playio is an Android-based community of five million gamers that analyzes genre preferences, play history, and in-game behavior data to connect players with games that fit their tastes. Pricing is CPI by default, and CPE based on reaching playtime thresholds, daily attendance, or completing specific in-game actions is also supported. Run on CPE, what the advertiser buys is play spread over several days rather than a single install, so the campaign goal points in the same direction as a metric like DAU/MAU that asks how many days a month players return.

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Key Takeaways

MAU is the count of unique users active at least once in a window: a rolling 28 days in Google Play Console, the last 30 days in GA4. DAU/MAU is average DAU divided by MAU, and multiplied by the window length it becomes the average number of days a monthly player shows up (20% equals 6 of 30 days). As of October 2026, public data puts mobile game DAU/MAU at an 11.8% median and 23.9% for the top 10% among US iOS apps, with short, daily genres such as puzzle, board, card, and word games running higher. Sources differ in population, aggregation, and window definition, so their figures can be several times apart, and the familiar 20% and 30% thresholds have been flagged as lacking gaming data behind them. More new users can raise DAU while lowering the ratio, and losing light users can raise the ratio while the game shrinks. Read DAU/MAU within your own trend on a single definition, split by new and existing users, and always next to absolute DAU, MAU, and ARPDAU.

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Sources

• Android Developers Blog, Google Play Console powers better decision making, 2021-03-02 (DAU/MAU: "the ratio of users who open your app each day vs. each month (28-day rolling period)"; a key measure of stickiness): https://android-developers.googleblog.com/2021/03/google-play-console-powers-better.html

• Google Analytics Help, [GA4] Analytics dimensions and metrics (DAU/MAU: users who engaged on the calendar day out of users who engaged in the last 30 days; DAU/WAU and WAU/MAU; active users are users with an engaged session): https://support.google.com/analytics/answer/9143382?hl=en

• Roblox Corporation, Form 10-K FY2025 (DAU defined as a user who logged in and visited on a unique registered account on a given calendar day; DAUs are not a measure of unique individuals; undetected fraud and unauthorized access may contribute to an overstatement of DAUs): https://www.sec.gov/Archives/edgar/data/1315098/000131509826000024/rblx-20251231.htm

• MWM, Stickiness glossary (all apps median 14.1%, top 10% 31.0%, State of April 2026; games median 11.8%, top 10% 23.9%, US, May 2026; US iOS apps with ≥1,000 d30 downloads and ≥100 DAU): https://mwm.ai/glossary/stickiness

• MWM, DAU/MAU glossary (genre ranges: casual 0.15–0.35, hyper-casual 0.10–0.20; dataset for the genre table not disclosed): https://mwm.ai/glossary/dau-mau

• Mixpanel, Mobile gaming benchmarks 2026, 2026-03-30 (mobile gaming stickiness in North America and APAC 32%; 517.6B events across 808.2M devices; aggregation method not disclosed): https://mixpanel.com/blog/mobile-gaming-benchmarks-2026/

• GameDev Reports, GameAnalytics: Mobile and PC Game Benchmarks in 2026, 2026-06-04 (16,262 mobile games with ≥1,000 MAU: D1 top 25% just above 30%, D7 median just under 4%; 3,582 PC games with ≥100 MAU: 2025 DAU/MAU median 4–5%, top 10% 13–15%, top 1% just under 40%): https://gamedevreports.substack.com/p/gameanalytics-mobile-and-pc-game

• WN Hub, How does your mobile game compare in 2019? GameAnalytics provides benchmark stats, 2019-07-01 (June 2018 to May 2019, 75K+ games; market median ~8%, top 15% ~19%; board, card, puzzle, word games lead above 20%): https://wnhub.io/news/analytics/item-2261

• WN Hub, Benchmarks of mobile game genres (retention, session time, ARPPU and "stickiness"), 2017-10-24 (GameAnalytics, January 2016 to September 2017; card, board, word and similar genres 14–16%; most genres average below 10%): https://wnhub.io/news/marketing/item-13358

• Game World Observer, GameAnalytics names benchmark engagement metrics for idle games, 2020-12-22 (stickiness: idle 18%, hyper-casual 10.5%): https://gameworldobserver.com/2020/12/22/gameanalytics-names-benchmark-engagement-metrics-idle-games

• Game Industry Library, GameAnalytics Mobile Gaming Benchmarks 2025 (11,600 titles, ~1.48B MAU; midcore 6–7 sessions per day): https://gameindustrylibrary.com/documents/gameanalytics-mobile-gaming-benchmarks-2025

• Business Wire, Block Blast Scales to 70M DAU as Hungry Studio Runs Over 10,000 Experiments in a Single Year, 2026-01-08 (70M DAU, 300M MAU; developer-reported): https://www.businesswire.com/news/home/20260108572322/en/Block-Blast-Scales-to-70M-DAU-as-Hungry-Studio-Runs-Over-10000-Experiments-in-a-Single-Year

• mobilegamer.biz, Data digest, 2026-01-14 (Block Blast up from 40M DAU and 160M MAU in December 2024): https://mobilegamer.biz/data-digest-2025s-top-earning-genres-appsflyer-for-sale-block-blast-hits-70m-dau-app-store-earnings-more/

• Stillfront, Interim Report Q2 2026, 2026-07-24 (DAU 6.70M vs 7.29M; MAU 33.6M vs 39.8M; ARPDAU SEK 2.14 vs 2.12; user decline reflects a continued shift of UA toward key franchises; key franchises Supremacy, Jawaker, BitLife, BIG, Empire, Albion, Board): https://investgame.net/news/pdf/2026-07-24-report-interim-report-q2-2026-stillfront_wp/

• Stillfront, Interim Report Q2 2026 press release (MFN): https://mfn.se/all/a/stillfront-group/stillfronts-interim-report-q2-2026-strengthened-profitability-and-continued-revenue-stability

• Game Developer, How Do I Know I Have a Healthy Game?, Trevor McCalmont, 2013-02-28 (strong games sustain DAU/MAU above 0.2; ratio skewed upward during UA campaigns): https://www.gamedeveloper.com/business/how-do-i-know-i-have-a-healthy-game-

• Game Growth Advisor, Mobile Game KPIs & Benchmarks 2026, published 2026-03-17, updated 2026-08-01 (the 20% and 30% thresholds have no measured population behind them for mobile games; no primary gaming dataset publishing a DAU/MAU distribution found): https://gamegrowthadvisor.com/blog/2026-03-17-mobile-game-kpis-benchmarks-2026/

• Own calculations: Block Blast and Stillfront DAU/MAU ratios (division of announced or reported figures), conversion to average active days, revenue example (200,000 MAU, 18% DAU/MAU, $0.12 ARPDAU), 190,000 28-day MAU assumption, and new/existing user mix example (60,000 new, 140,000 existing): illustrative calculations