For many years the industry standard for measuring mobile app user engagement has been some combination of Daily Active Users (DAU), Monthly Active Users (MAU), and Time Spent. Analyzing how often users are opening an app and how long they’re using it can paint a broad picture of how engaged an app’s user base is.
However, there are limitations to examining engagement metrics that are derived as an average of an entire app user base. Evaluating DAUs and MAUs, for example, groups the entire user base of an app into one cohort to give a simple average and doesn’t show the nuance between cohorts of app users, particularly how well an app is generating and retaining Power Users.
This is where the Power User Curve comes in.
What is a Power User?
Power Users in Sensor Tower are the most valuable customers of an app: they engage with it the most, have the highest lifetime value (LTV) of all users, and are most likely to refer other users (resulting in organic growth).
Note that Power Users in this context may not be the most technologically adept users and this module cannot give insights into the development of, for example, complex user interface elements aimed at those who require advanced functionality.
What is the Power User Curve?
Consumer Intelligence’s Power User Curve is a visual representation of an app’s user engagement by the total number of days its users are active in a given month. A Power User Curve is particularly helpful at showing if an app is resonating with a highly-engaged group of users and if the app is generating more power users over time.
The Power User Curve graphs the total number of days per month the percentage of users who opened an app. You can visualize up to five apps on one graph.
For example, you can compare the stickiness of some of the major players in the Dating app category over a specified date range:
The Power User Curve allows you to easily see which apps have the highest and lowest proportion of highly engaged users. For example, almost half of Badoo users open the app fewer than five days per month leading to a curve that skews distinctly to the left.
In contrast, Hinge exhibits something closer to a Smile curve with high concentrations of casual and power users. It is also possible for an app’s Power User Curve to skew hard to the right with large groups of power users – this type of curve is common with popular social media or messaging apps.
By leveraging other Sensor Tower modules, it is possible to understand why different apps exhibit different Power User Curves.
Though Hinge is the third most popular app in terms of active users, its users are the stickiest. This may be because Hinge has a different format relative to its peers; rather than prompting daters to swipe left or right on would-be matches, Hinge requires its users to ‘like’ and ‘comment’ on other people’s photos/feeds to strike up a conversation, mimicking addictive social media applications.
Modules such as Sensor Tower’s App Intelligence can help explain why an app’s curve may shift over time. For example, Hinge has been able to maintain its strong Power User Curve by adding additional features to the app giving users even more reason to open the app daily – one example being the introduction of voice features in late October 2021. This update enabled users to add voice recordings to their profile and send voice notes to one another over chat.
According to Sensor Tower Engagement Insights, in November 2021, less than a month after the change, Hinge’s average time spent per user overtook that of Tinder, and in 1Q22 Hinge enjoyed a 17% YoY increase in the average time spent per user, while Tinder, Bumble and Badoo were either flat or down in the year.
With plans to begin rolling out Hinge into non-English speaking countries, the app’s strong engagement metrics leave parent company Match Group well placed.
Working with the Power User Curve
To select your app or cohort of apps, simply click on the Analyze users of dropdown and select from the available Applications or Games. You can either Search for an app… or scroll through apps listed alphabetically by genre (e.g. Banking, Comics, Dating). You can also select a category of apps by selecting the category name. You can select up to five applications at a time.
To see a list of the apps it is possible to analyze in this module, please see this Help Center article.
To remove any app from your cohort, simply click on the X in the top right corner of the app’s name and publisher details. To clear the entire cohort, click Clear Entities to the right of the selected apps.
You can specify a particular Date Range to analyze – all available data will be shown by default – and which Region you wish to look at. By default, Worldwide data will be shown but it is also possible to view only users in Latin America, Southeast Asia, or the USA.
The Justify Curves toggle helps users easily compare data between months that don’t have the same number of days. This is done by massaging our data to only show the first and last 14 days.
You can view the data as either grouped columns or a line graph by selecting your preference with the Plot Type dropdown.
If you wish to temporarily remove an app from the graph, simply click on the app’s name in the key located directly below the graph. Click the app’s name again to reinstate it. Removing outliers can sometimes make the data significantly easier to interpret.
Data is also shown in a table below the main Power User Curve graph. You can easily see the percentage of users that open a given app for any number of days in a month as well as the average number of days. You may need to scroll to the right to see all data.
Comparing data over time
To see usage data broken down by month, click on the small arrow to the left of the application name in the Segment table. This will show you a breakdown of users of that app by month and year. Check the checkbox beside a given month to see this data plotted on the graph above. You can select or deselect app data en masse by clicking on the checkbox in the table header row or beside a given app name.
Power User Curve data is also available via our API. One advantage of obtaining data this way is that you can easily compare more than five applications at a time.
Power User Curve Methodology
Consumer Intelligence pulls this unfiltered data directly from Sensor Tower’s own proprietary panel of mobile devices. Our panel-based apps are purpose-built from the ground up to provide the most accurate metrics possible while delivering world-class user privacy and security.
A user is deemed to have used an app on a given day if they have opened it in the foreground of their mobile device; widget usage does not count for the purposes of this module nor does having an application open in the background. There is also no minimum usage threshold: any duration in the foreground will constitute usage.
Power User data is available starting 30 March 2020 and is updated at the start of every month.
Data can be viewed by the following regions: Worldwide, Latin America, Southeast Asia, and the US.
Please note that data is currently only available for the Google Play store.