TL;DR
What DAU, WAU, and MAU mean, the formula behind each, DAU/MAU ratio benchmarks, and how to pick the right active-user metric for your product. DAU, WAU, and MAU count how many unique users actually use your product in a day, a week, or a month.
DAU, WAU, and MAU count how many unique users actually use your product in a day, a week, or a month. They are the baseline active-user metrics behind almost every engagement and growth conversation. This guide defines each one, gives the formula behind it, explains the DAU/MAU stickiness ratio with benchmarks, and shows how to decide which metric should lead for your product.
What is DAU?
DAU (Daily Active Users) is the number of unique users who perform at least one qualifying action in your product within a single day.
Formula: DAU = count of distinct users with at least one qualifying event during one calendar day (in a fixed timezone).
A single "DAU" is simply one unique user counted as active that day — if the same person opens your app five times on Tuesday, they still count once. Deduplication per window is what separates active-user metrics from raw event or session counts.
The definition hinges on what counts as "active." A session start is the loosest version; a meaningful action — sending a message, running a report, completing a task — is a far better signal. Whatever you pick, keep it consistent, because every other active-user metric in this guide inherits it.
What is MAU?
MAU (Monthly Active Users) is the number of unique users who perform at least one qualifying action in your product within a month — either a calendar month or a rolling 28–30-day window.
Formula: MAU = count of distinct users with at least one qualifying event during the month. A rolling 28-day window avoids the distortion of months having different lengths and different weekday counts.
Because it uses the widest window, MAU is the most forgiving of the three metrics — a user who shows up once a month counts the same as one who shows up daily. That makes it a good measure of reach and a poor measure of habit, which is exactly why the DAU/MAU ratio below exists.
What is the DAU/MAU ratio?
The DAU/MAU ratio — often called stickiness — is the share of your monthly active users who show up on a typical day, calculated by dividing DAU by MAU.
Formula: DAU/MAU ratio = (average DAU over the month ÷ MAU) × 100. A ratio of 20% means the average monthly user is active about 6 days out of 30.
Commonly cited benchmark bands: under 10% is normal for low-frequency products (tax software, travel booking); 10–20% is a typical range for SaaS and consumer apps; 20%+ signals a genuine habit; 50%+ is rare, messaging-app territory. Compare against your own category and cadence rather than a single universal target — a 12% ratio can be excellent for a product designed for weekly use.
One caveat: use an averaged DAU (not a single day's) and note whether MAU is calendar-month or rolling, since weekday/weekend swings and month length both move the ratio.
DAU, WAU, and MAU formulas at a glance
| Metric | Window | Formula |
|---|---|---|
| DAU | One day | Distinct users with ≥1 qualifying event that day |
| WAU | Seven days | Distinct users with ≥1 qualifying event in the 7-day window |
| MAU | Calendar month or rolling 28–30 days | Distinct users with ≥1 qualifying event in the window |
| DAU/MAU ratio | One month | (average DAU ÷ MAU) × 100 — the stickiness percentage |
DAU vs WAU vs MAU: which to use when
Use DAU when your product is meant to be a daily habit, WAU when the natural cadence is a few times a week, and MAU when usage is occasional but should be consistent month over month.
The three metrics nest: everyone counted in DAU is also in that week's WAU, and everyone in WAU is in that month's MAU, so DAU ≤ WAU ≤ MAU by definition. That nesting is what makes the ratios between them meaningful — DAU/MAU measures daily stickiness, and WAU/MAU tells you whether your monthly audience shows up at least weekly. Watching the gaps between the three lines is often more informative than watching any single line.
Choosing DAU as the primary metric
DAU is crucial for products that rely on frequent, daily engagement. If your product is something users interact with multiple times a day - like social media apps or messaging platforms - DAU is a key metric. It shows how often users return and engage on a daily basis. But if you offer a product that doesn't require frequent use (like a task manager or a tool for occasional use), DAU might not be as critical.
Choosing WAU as the primary metric
WAU (Weekly Active Users) counts unique users active within a seven-day window, and it is particularly useful for products where engagement is expected a few times per week. This metric is great for understanding short-term user behavior. For instance, a mobile games app might want to track how often users engage with the app throughout the week, as regular check-ins (3-4 times a week) may signal successful engagement. However, users may only need to engage weekly with other businesses, such as project management tools, so WAU can be more relevant than DAU.
Choosing MAU as the primary metric
MAU helps you track longer-term engagement. If your product is something people use occasionally but consistently such as a calendar app, subscription-based service, or even e-commerce sites - MAU is critical to measure. It shows whether users stick around over time, even if they don't engage daily or weekly. If you're in a business that isn't based on daily engagement (such as SaaS, where users only log in when they need to complete a task), MAU will likely be more meaningful for gauging user retention.
Why active-user metrics matter?
Ultimately, which metric matters most depends on your product and what you're trying to measure. Active user metrics are more than just numbers, they provide a snapshot of your product's success in engaging users. DAU, WAU, and MAU help you understand user retention and the effectiveness of your product. For example, if your DAU is increasing, it indicates that users are returning regularly, a good sign of engagement. If the numbers are declining, it may suggest friction points or declining interest.
How to measure DAU, WAU, and MAU?
To effectively measure DAU, WAU, and MAU, you need to define the specific actions that constitute an active product user, whether logging in, making a purchase, or engaging with key features.
Three pitfalls account for most inflated or noisy active-user numbers. First, identity: the same person on a phone and a laptop becomes two users unless device IDs resolve to one user ID. Second, timezones: computing "a day" in UTC while your users live elsewhere shifts activity across day boundaries and distorts DAU. Third, internal and bot traffic: employees, test accounts, and crawlers should be excluded from the qualifying-event definition.
Settle all three once, in your warehouse's event model, so every team computes the same numbers from the same tables.
Using product analytics tools like Mitzu, you can track DAU, WAU, and MAU with greater accuracy and granularity. These tools allow you to segment users based on behavior, demographics, or acquisition channels, helping you identify which user groups are most engaged and which need re-engagement. For example, you can track a specific cohort's weekly interactions to see how their engagement evolved comparing to the previous month.
Mitzu is an agentic product analytics platform that runs on your data warehouse: you ask for DAU, WAU, or stickiness in plain language, and a deterministic query engine — grounded in a semantic layer of your events — generates the SQL. The same question always produces the same SQL, and the SQL stays reviewable, so your active-user metrics are computed on live warehouse data without copying it anywhere.
FAQ
What is a good DAU/MAU ratio?
A DAU/MAU ratio of 10–20% is typical for most SaaS and consumer products, 20%+ indicates a strong daily habit, and 50%+ is exceptional, seen mostly in messaging and social apps. Low-frequency products can be healthy well under 10% — judge the ratio against your product's intended cadence.
When should I prioritize DAU over WAU or MAU?
Prioritize DAU when your product depends on daily habits, such as messaging, social, or collaboration flows. If your product has naturally lower interaction frequency, WAU or MAU may be a better primary metric. The right choice depends on expected user cadence.
Is a rising MAU always a good sign?
Not necessarily. MAU can rise while activation, depth, or retention quality declines. Always pair active-user counts with funnel conversion and cohort retention to understand whether growth is meaningful.
How can I compare DAU/WAU/MAU across segments?
Segment active users by acquisition channel, plan type, region, or device class to identify engagement differences hidden in aggregates. This reveals which user groups are healthy versus at-risk. Warehouse-native analysis makes these cuts easier to maintain.
How does Mitzu help track active-user metrics?
Mitzu runs active-user queries directly on your warehouse and lets teams define active events visually. You can monitor DAU, WAU, and MAU on live data without exporting to third-party stores. SQL remains transparent for validation.
