What app developers should know about the Monthly Active Users (MAU) metric
By Abhinav Agrawal
MAU stands for “monthly active users”. For mobile apps, the MAU definition is: the number of unique users who have performed some action in an app within the last month.
In this post, we’re going to explore the nuances of that definition, discuss why it’s useful to know and track the monthly active users metric (including how to interpret it while avoiding certain pitfalls), and, finally: explain how you can discover your app competitors’ MAU metrics.
Breaking down the MAU definition
- Unique users: In the calculation of MAU, a user who performs any action in an app during the course of a month is counted only once, regardless of how many times that user might perform actions in the app during that period. That is, every person who performs at least one action is counted only once.
- Perform some action: The often-tricky part is defining the “performed some action” that makes a user eligible to be counted in monthly active users (MAU). Let’s take a photo sharing app like Instagram as an example. Should this action be taking a photo, sharing a photo, liking a photo, or commenting on a photo? We actually recommend using “opening the app” as the eligibility metric for MAU. This is the most widely-used definition in the app industry and will enable easier comparison to other apps and companies. Being a broad definition, it also allows you to easily measure the largest set of users that interact with your app.
- Within the last month: Customarily, the “last month” in MAU is defined as the last (or trailing) 30 days leading up to the date for which you’re calculating MAU.
In summary, we can also express definition of monthly active users (MAU) as: The number of unique users who open the app within a 30-day period leading up to the date for which you’re calculating MAU.
Why is monthly active users (MAU) a useful metric?
Unlike other commonly-reported app metrics such as cumulative downloads or cumulative registrations, monthly active users (MAU) conveys how an app is performing over time in terms of attracting AND maintaining users.
For example, see the chart below for a hypothetical app in terms of cumulative downloads or registrations. (Many numbers quoted in press releases and media articles are precisely this vanity metric of total downloads vanity metrics since that is the largest and most impressive number.) Looking just at that chart, you may be misled into believing that the app is “growing” over time and an exciting opportunity in terms of employment, investment, etc.
However, looking at monthly active users can tell a different story. In this case, not only are the active users significantly lower than total downloads/signups but the app is actually declining in terms of active users over time.
For products that rely on advertising or purchase revenue, monthly active users are the sum total of all users that possibly could be monetized and thus form the “upper limit” of the audience. (For a discussion on how to use monthly active users when presenting to Venture Capital investors, check out this blog post by Social Capital.)
How to interpret changes in monthly active users (MAU)
Generally, MAUs change slowly over time through the combination of acquisition of new users, retention of existing users, and reactivation of lapsed users.
MAU (t) = new users (t) + reactivations of lapsed users (t) + retained users (t)
Increases in MAU happen when the combination of new users and reactivations of lapsed users for an app is more than the churn (or loss) of existing users.
New users (t) + Reactivations of lapsed users (t) > Churn of existing users (t)
Sudden increases in MAUs for you or your competitors can be driven by:
- Increase in new users — A sudden burst of positive press, an app getting featured in the App Store, or a new advertising campaign can increase downloads and new users, driving a corresponding increase in monthly active users.
- Increase in reactivations — Apps that have a large, potentially-dormant install base can drive an increase in MAUs by using push notifications, email, or other re-engagement mechanisms to reactivate lapsed users.
- Decrease in churn — A release of a new version of the app or some new feature may cause a reduction in the normal churn rate of existing users, driving an increase in MAUs.
Decreases in MAU happens when the combination of new users and reactivations of lapsed users for an app is less than the churn of existing users.
New users (t) + Reactivations of lapsed users (t) < Churn of existing users (t)
Sudden decreases in MAUs for you or your competitors can be driven by:
- Decrease in new users — MAUs may decline if new users in the current time period are lower due to expiry or reduction of advertising, promotions, or App Store featuring.
- Decrease in reactivations — Similarly, a decrease in email or Push Notification campaigns will decrease reactivations and total MAUs.
- Increase in churn — Lastly, new features that users dislike or technical problems with the app may increase the churn of existing users leading to lower MAUs.
How to avoid common pitfalls when using monthly active users
Many folks have actually advocated for retiring the MAU metric. While the metric does have its share of issues, we don’t think that ignoring MAU altogether is the right approach. As a lightweight, easily-calculated, and easily-compared metric, MAU is the best option we have.
When using MAU, be wary of these caveats:
- MAU is unreliable for newly-launched apps — Don’t put too much weight on MAU figures early in an app’s life. Given the generous definition of MAU (unique users that open an app in a 30-day period), all of the promotional activities usually associated with an app launch (including PR, ad spend, word-of-mouth, possible featuring in the app store, launch partnerships, and more…) can dramatically inflate MAU numbers relative to what the numbers will be when the app’s traffic normalizes over the next few months.
- MAU doesn’t account for low quality users — Not all users are created equal. For example, users captured from different sources (e.g., advertisements vs. app store charts) tend to display different engagement behaviors, on average. Some sources may allow you to acquire app installs quickly and cheaply, but if the users from those sources don’t engage and/or retain, then that source isn’t very useful. If you happen to acquire a disproportionate amount of your users from a source like that in a particular 30-day period, don’t get too excited over your newly-inflated MAU numbers.
- MAU doesn’t account for depth of usage — Again, to qualify a Monthly Active User, a user merely has to open your app. They don’t have to engage with the app any further than that. Be cognizant that having a high MAU number doesn’t mean that you have a lot of users actually using your app. (And you can only monetize users who engage with your app to any extent.) That’s why it’s a good practice to also measure the number of unique users per month who engage with some core feature of your app.
As Mark Twain once said, “Facts are stubborn things, but statistics are pliable.” Make sure you are not being plied when using the MAU metric!
How to calculate MAU for your app competitors
So how do you know what a “good’ MAU metric is for your app? The best way to determine the answer to that question is to identify the MAU stats for your closest app competitors; the apps that most-resemble yours in terms of their audience and value proposition.
By knowing the range of monthly active users that your various competitors have acquired, you can benchmark your app’s success. You’ll know what numbers represents underperformance, average performance, and high performance, which allows you to set realistic goals and understand the possible size of the market.
To get these app competitor analysis insights, you need an app intelligence tool like SurveyMonkey Intelligence. Sign up for a 14-day free trial of SurveyMonkey Intelligence to get MAU metrics (and lots of other valuable usage and revenue stats) for thousands of iOS and Android apps.
This post originally appeared on September 19, 2016 on the blog of SurveyMonkey Intelligence, a provider of competitive intelligence for the mobile app industry.