Measuring your Monthly Active User (MAU) rate has long been a core insight for assessing the general health of your business.
Websites, applications, and especially subscription-based companies often rely on this metric for insights into growth, churn, user satisfaction, and more.
In this post, we'll take a closer look at MAU, what it can do for you, and what, exactly, it can’t.
Monthly Active Users (abbreviated as MAU) is a measurement of the number of unique users who visit or engage with your website or app within a 30-day period. These users are typically identified with an email address, username, or ID. Once identified, they will only be counted once during this 30-day period, regardless of how often they interact with your product.
What makes a user “active” can vary and will depend on a variety of factors, such as the product type, the company’s goals, and the available actions a user can complete. Some organizations may count a user as active by simply logging into their account. Others may require users to use a specific feature or service – or multiple.
MAU is often analyzed alongside the Daily Active User (DAU) metric in order to build a more comprehensive picture of how users interact with the product.
The primary reason to use MAU is because it can help you track customer engagement. This, in turn, can enable you to strategize for future growth.
The key here is how MAU measures “active users.” Rather than simply measuring a metric like your monthly downloads or overall number of users, both of which can easily be affected by factors such as marketing or the age of your product, “active users” can tell you whether users are actually getting value. In other words, it is a useful indication of how your product is performing. When tracked over time and combined with other Key Performance Indicators (KPIs), MAU can help you identify what is and isn’t working so you can plan accordingly.
Here are some even more specific ways MAU can be an important metric for tracking user behavior and growing your business:
It can be a consistent check on product health. MAU offers the opportunity to see whether or not users are actually engaging with your product. As you track this over several months or years, you can pull out larger trends and patterns that paint an even more detailed picture of the health of your product
It can help you predict future growth or churn. Over time, as you collect more data on MAU, you’ll likely be able to point to features or product changes that improve user engagement and increase growth, or do the opposite. Knowing this can give you a headstart on creating a successful growth strategy.
Many businesses like to pair DAU and MAU together in order to determine the rate at which users return to their product within a 30-day period. Expressed as a percentage, this number gives insight into one of the best predictors for future growth: user retention. The higher percentage of users returning to use your app, the better your performance.
The formula looks like this:
DAU ÷ MAU = DAU/MAU Ratio
Here’s a practical example of how this works. If you have a DAU of 100 and a MAU of 500, then your DAU/MAU ratio would be 20 percent. Put another way, one out of every five users, within this given month, returned to use the product again.
Before measuring MAU, it’s important to understand its three separate components:
Users: A unique person who performs an action or engages with your product in some way.
Timespan: The 30-day window in which all unique users who perform an action are counted.
Activity: The action that a user must perform to be counted as active within the 30-day window. This is up to each organization to define themselves and can range from general to specific.
So to calculate MAU, you can just count the number of active users you have over a 30-day period. However, each of these three components can be as simple or complex as you make them. Let’s explore each a bit further.
Like DAU, it can be helpful to break users down into those who are new and those who are returning. This would give you the following formula:
Unique New Users + Unique Returning Users = Total MAU
New users are those who have not previously used your product while returning users are those who have. You may be able to differentiate them by noting whether they already have an account or through a unique user ID you’ve previously assigned them. Keep in mind that both of these are unique, meaning that if a person comes back and uses a feature multiple times throughout a month, they will still only count once.
Of course, whether or not you divide your MAU number this way is up to you. Many companies simply count active users and leave it at that. But an advantage of doing it this way is that it can help you analyze two important factors for success:
How well you are attracting new users. This is always an important metric to track. A growing number of new users is a sign of product health, while a falling number may be a warning sign.
How well you are retaining existing users. You also need to measure the number of users who return. This will tell you how sticky your app or product is. A high number here is an even more robust sign of health.
This is the specific window in which users are counted. Generally, this is defined as 30 days. However, depending on your needs, you may also use the exact calendar month. You could also define this window as beginning and ending on the 15th of each month, rather than the 1st.
However you define your MAU timespan, it is important to be consistent. You will want to track MAU over not just one month, but many. This will enable you to spot trends and patterns that can help you build your future strategy. Once you have collected consistent MAU data for long enough, you may even find it helpful to compare similar time periods going past several years.
The definition of what an “active user” is can vary widely across different companies. For some, this may be a simple action, such as opening an app or logging in. For others, it may be something more specific, such as using a certain feature or UI element. Some may have even more particular requirements, such as a series of multiple different actions a user must take.
Ultimately, deciding on what action or actions a user must perform in order to count toward MAU will depend on several factors, such as your product or service, the different ways users can interact with it, and, most importantly, the goals of your company.
After all, the point of MAU is to define a metric you can use to increase product usage, improve user retention, and grow your company. Because of this, it is essential for you to define it using an action that directly impacts your success.
Olga Berezovsky, author of the Data Analysis Journal newsletter, recommends using the main user action as the activity event in order to collect clean and precise data.
She shared a few examples of what actions can be used for defining an Active User for well-known companies in the table below:
The many different ways you can define “active users” when calculating MAU is a big reason why more people are calling it either unreliable or irrelevant.
If one company decides a user needs to sign in once a month in order to count as active, they will likely have a much larger MAU than a company that decides users must instead sign in multiple times. Without a more uniform definition, it is basically impossible to compare this metric across competitors.
There is also the question of whether or not you are actually measuring real user activity. Companies that use a basic action, such as a sign in, to define their active users risk overcounting MAU. The result may look good on paper, but will largely be meaningless.
On the other side, companies that define MAU too specifically, such as by limiting it to only certain types of users who perform a specific series of actions, may not be capturing the full breadth of user activity.
These issues should be considered and, where possible, accounted for when calculating MAU. Here are some strategies for doing this:
Account for depth of usage. Because you’re looking at user activity across a month, subjective measures like logins fail to differentiate between users who sign in once per month versus power users who sign in 30 times a month. Instead, try to identify a more meaningful action, such as interaction with a core feature. And don’t forget about using the DAU/MAU ratio, as it is a great way to measure retention.
Don’t look at MAU alone. As helpful as MAU can be, it should not be considered the final word on product success. There are many other metrics you should consider alongside it as well. These include churn rate and retention rate, Average Revenue Per User (ARPU), and more granular user metrics like DAU and Weekly Active Users (WAU).
Analyze MAU trends. Just as you shouldn’t consider MAU on its own, neither should you consider any one MAU number by itself. Instead, look for larger trends that your MAU numbers, over multiple months or even years, reveal. Are active users growing in certain months but shrinking others? Did a change in UI lead to an initial increase before decreasing again? Look past the numbers for patterns that may reveal whether or not you’re heading in the right direction.