Head of Retention Marketing
I've been working in email marketing since 2016. I passed the way from a junior specialist with the thoughts "email is spam in the mailbox?" to the real jedi of retention marketing. I worked with the largest Ukrainian eCommerce projects. I'm keen of the latest technologies and non-standard technical implementations.
DAU, WAU, and MAU metrics show how often people interact with an app and how often they return. While they are easy to calculate, as most analytics systems track them automatically, the real value lies in how you interpret these numbers and what actions you take based on them.
In this article, we’ll break down what DAU, WAU, and MAU mean, how to calculate, interpret, and use them to improve engagement and retention in your mobile app.
MAU (Monthly Active Users) shows how many unique users interacted with an app at least once in the past 30 days. This metric helps you understand the size of your active audience and how interest in your product changes over time.
MAU works best for products that people don’t use every day, but come back to from time to time. For example: eCommerce, travel services, and financial or payment apps.
DAU (Daily Active Users) shows how many unique users took an action in an app within one day. This metric helps you understand whether users return to the product regularly.
DAU is mostly for apps used daily, such as social media, messengers, games, news, or music services.
WAU (Weekly Active Users) is the number of unique users over 7 days. It shows how often people return to an app if they don’t use it every day. For example, in eCommerce, a user may not open the app daily but may come back several times a week, and WAU captures that.
WAU works for apps people use a few times a week, such as delivery, banking, and health apps.
On their own, DAU, WAU, and MAU may not give the full picture, so it’s better to look at them together. The stickiness metric (DAU/MAU ratio) is useful here because it shows how often users return.
MAU and DAU show the size of your audience, but they don’t always answer how often people actually use the app. For this, the DAU/MAU ratio is used. It is also called the user stickiness metric. The higher it is, the more often users come back to the app.
The formula is simple: DAU / MAU × 100%
You must clearly define what an active user is.
If an active action is defined incorrectly, MAU, DAU, and WAU may not reflect real user activity.
What counts as an active user differs from business to business. It depends on which actions matter most for the brand. For example, in eCommerce, activity can be opening the app, browsing the catalog, adding a product to the cart, or making a purchase.
You can calculate MAU, WAU, and DAU automatically using analytics systems (GA4, product analytics tools, mobile trackers).
But in short, it depends on the time period you choose to count active users.
MAU — active users over a calendar month or 30 days.
WAU — active users over 7 days.
DAU — active users over 1 day.
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Let’s say an online store considers a user active if they open the app and take at least one action, such as adding a product to the cart. In February, 122,000 unique users did this. That is the MAU for the month (122,000).
Now let’s look at one specific day, for example, September 12. On that day, 8,300 users added items to their carts. So, the DAU for September 12 is 8,300. As with MAU, each user is counted only once, even if they did an action several times during the day.
Now take one week, for example, from September 9 to 15. During this period, 50,000 unique users took at least one action in the app. This means the WAU for that week is 50,000. The same logic is here as well: if a user opens the app several times during the week, they are still counted as a single active user.
GA4 can also calculate:
- Daily Active Users (DAU) / Monthly Active Users (MAU)
- Daily Active Users (DAU) / Weekly Active Users (WAU)
- Weekly Active Users (WAU) / Monthly Active Users (MAU)
These metrics help you understand how regularly users return to your product. Over time, they show how user activity changes and whether your audience is growing.
In eCommerce, MAU/DAU help track customer retention. Even if people don’t make purchases every day, you can see how many of them come back within a month.
Also, the size of your active audience directly affects your monetization potential. The more users regularly interact with your app, the more opportunities you have for sales, subscriptions, or ad revenue.
The meaning of this metric strongly depends on the type of product.
In eCommerce apps, DAU/MAU is usually lower — around 10%. This is normal, since users don’t buy products every day.
Companies usually don’t share data on active users, but according to some sources, Amazon, for example, may have between 300 and 600 million monthly active users.
At the same time, it’s important to look at the trend. For example, if MAU is growing but DAU stays the same, it may mean that new users are coming in but not becoming regular users. On the other hand, when DAU grows together with MAU, it usually signals better retention.
For eCommerce, where purchases are not that frequent, MAU is used as a base metric for a “live” audience: if MAU drops slightly, you should focus on retaining existing customers — for example, by offering promo codes for repeat orders or personalized selections / Next Best Offer products.
- Svitlana Fursa, Head of Retention Marketing at Promodo
In other words, MAU/DAU metrics not only help track customer retention, but also are the key factors in decision-making — when it’s better to send a push notification to encourage a repeat purchase, and what frequency of mobile push campaigns will be enough and optimal.
For example, you see a pattern where in the first 90 days after the first purchase a user’s MAU stays at 65–70% of the initial level, and then drops to 35–40%. This is a clear signal to set up a reactivation flow: on day 91 — a “You may also like” trigger (personalized product recommendations — Next Best Offer), and on day 120 — a “Come back for bonuses” trigger. This will increase not only MAU but also repeat purchases.
- Svitlana Fursa, Head of Retention Marketing at Promodo
For promotional campaigns, the WAU/MAU level should guide both the message frequency and the type of content. For example, if WAU/MAU is 45% or higher, it means the user opens the app 2–3 times a week and is quite active. In this case, weekly selections with new products in the categories they view will work well.
WAU/MAU is also important for media planning — when the metric drops, it makes sense to increase promo frequency.
If WAU falls below 30%, users should receive more valuable, personalized triggers that encourage them to return, rather than mass campaigns. For example: “Discount on a product you viewed 10 days ago” or “Similar product on sale.” This approach helps reduce unsubscribes (by avoiding spam) and increases conversions through personalized recommendations.
Let’s look at approaches that help increase user activity.
Users install an app with a specific goal: to find a product, check prices, or make a purchase. If sign-up takes too long or requires filling out a profile or watching instructions first, many will just close the app. So guide users to their first useful action as quickly as possible to make them stay.
For example:
The faster a user finds something interesting or useful, the more likely they are to come back.
Maximize the share of users who agree to receive notifications, as mobile push notifications are an effective way to bring users back to the app.
- Svitlana Fursa, Head of Retention Marketing at Promodo
One of the main reasons people come back to an app is relevant content. In eCommerce, this means working with user data:
When the app adapts to the user’s interests and regularly offers something useful, it stops looking like a regular catalog and becomes a tool people return to.
Many people open an app once or twice and then forget about it. That’s why it’s important to remind them about your app at the right moment.
Simple examples:
The main rule is that the message should be useful.
These elements gradually build a habit of using the app, not just opening it once before a purchase. This is what drives steady growth in DAU and MAU.
A good retention tool is a loyalty program with gamification elements. For example, badges or rewards that require users to open the app regularly and complete certain actions to earn them.
- Svitlana Fursa, Head of Retention Marketing at Promodo
For example, the “Iron Friends” loyalty program by Ukrainian Railways (Ukrzaliznytsia). Users receive “hugs” as a reward for completing tasks, such as rating 10 trips. These “hugs” can then be exchanged for discounts and bonuses from program partners.
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Gamification like this is a short-term solution that can temporarily increase MAU, but it also helps “teach” users how to use the app. For example, you can use it to highlight features users may not know about, show special offers and where to find them, or explain how your service works and what benefits it offers.
- Svitlana Fursa, Head of Retention Marketing at Promodo
Another way to use a loyalty program for retention and repeat purchases is personalized promotional offers. For example, cashback for birthdays or personalized discounts on competitive product categories based on user preferences.
Sometimes the issue isn't marketing but the app itself. If the app loads slowly, freezes, or is hard to navigate, users simply won’t use it.
That’s why you should check the app’s technical health regularly:
Design is just as important. Navigation should be intuitive, and the path to purchase should be short and clear. The easier it is for users to find a product and complete an order, the more likely they are to come back.
We have also shared how to track “weak spots” in the interface and improve user experience using heatmaps:
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DAU and MAU usually grow through constant experimentation. Teams test different parts of the app: onboarding, push notifications, home screen blocks, or product recommendations. Sometimes, even a small change like a different push notification text can affect how often users come back.
In addition to A/B testing the interface, it’s important to test the app's technical side. In particular, API testing helps check how data is exchanged between the app and the server: whether products load correctly, how fast recommendations load, and whether key features work reliably.
MAU, WAU, and DAU metrics can be easy to misinterpret. Here are a few tips from us to help you avoid mistakes when working with them.
A common mistake is failing to understand who the app's active users are. If you count every open, the metric may be too broad. In eCommerce, it usually makes more sense to track actions such as login, product views, searches, adding to cart, or completing a purchase. The more precisely you define activity, the more reliable your MAU and DAU will be.
Some companies calculate MAU by calendar month (for example, from the 1st to the 31st), while others use a rolling 30-day period. Both approaches work, but shouldn’t be mixed. If you change the method, month-over-month or year-over-year comparisons may become inaccurate.
One person may use the app on multiple devices or switch between guest mode and an account. If these identifiers are not merged, analytics may count a single user as multiple users, inflating your metrics.
Sometimes DAU grows sharply on certain days, for example, during a promotion. But this doesn’t mean stable growth in engagement. Look not only at daily numbers but also at averages over 7 or 30 days to see the real trend.
Many insights emerge when you break the metric down by segments: new vs. returning users, countries, acquisition channels, or campaigns. For example, a large share of MAU may come from one source but have low daily activity.
Test devices, automated requests, or low-quality traffic may end up in your data. If not filtered out, your active user metrics may look much better than they actually are.
One metric says little about real user engagement. For example, two apps may have the same MAU but very different usage frequency or revenue. That’s why WAU, MAU, and DAU should be analyzed together with other metrics, including retention, stickiness, and revenue per user.
Consider your users' unique behavior. This helps you collect better data and make more accurate decisions.
Head of Retention Marketing
I've been working in email marketing since 2016. I passed the way from a junior specialist with the thoughts "email is spam in the mailbox?" to the real jedi of retention marketing. I worked with the largest Ukrainian eCommerce projects. I'm keen of the latest technologies and non-standard technical implementations.
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