Mobile App Data Benchmarks are quite opaque. Though getting accurate data for your app category and competitor is difficult, general inference about good and bad can be based on publically available data. This also helps in figuring out the product -market fit of your product. I have gathered the information from different mobile app analytics companies and analytics team of different startups.

Andrew Chen and Quettra Study 

For an average app D1 (Active users after a day of install) is 29%. It almost lost 71% users. While D30 for an average app is 10%.

Now here users are lost doesn’t mean that users are suddenly going completely inactive – they might just be using the app once per week, but they are not active on that particular day. Don’t confuse this app install retention, though they are correlated. If the user is not using the app, chances are high that app will be uninstalled.

According to Ankit Jain (formerly head of search+discovery for Google Play)

“Users try out a lot of apps but decide which ones they want to ‘stop using’ within the first 3-7 days. For ‘decent’ apps, the majority of users retained for 7 days stick around much longer. The key to success is to get the users hooked during that critical first 3-7 day period”.

Flurry App Uninstall Benchmarks

Flurry comes out with a great article on the breakdown of retention versus frequency for a bunch of mobile app categories.

This will serve as retention over 30 days benchmark for different categories i.e. Health and Fitness, Education, Entertainment, Finance, News etc. As per the report, Health and Fitness have the highest retention i.e. 48% in Android. Games have generally low retention. Please note that this retention over 30 days different from D30 retention. D30 is based on active user lost i.e. users not active on the 30th day. While, Flurry measures active app installs in 30 days (number provided by Google Console and iTunes).

Apsalar Android Benchmark

Marketers are most interested in understanding and mitigating uninstall rate problems in the first weeks of a customer engagement. But data show that after a few weeks, user behavior is mostly set for long term. That’s why 4 weeks benchmark is provided. These number seems bit biased to good quality apps, but neverthless are good benchmark

APAC region has worst mobile app unistall rate. Major reason why rates are higher in India and across APAC is less expensive phones purchases here have much smaller memories.

Localytics and Similiar Web Report

After a user installs an app, it get’s used alot in first 3 days. However, on ana average app retains only 23% of Daily Active Users within 3 days of installation. In general, app with high D3 retention rates drive high engagement in future. Average app is approximately unistalled in 8 months, and for gaming app it is about 7 months.

Users who are retained for 7 days stick around. The percentage of users who abandon an app after one use is now 23%. The percenatage of users who are retained 11 or more times, hence retained are 38%. That means a whopping 62% will use an app less than 11 times.

“For successfyl retention strategy – Build a good relationship between 3-7 days period and before 11 app opens”

Retention in below Localytics report is defined as returning to the app at least 1x within 30 days.

“So in general, with the exception of gaming apps,anything around 20% retention rate at 90 days is average across the mobile industry, and anything north of 25% is what you should strive to reach.”

Below is statistic for top performing app. These apps are defined as top performers by having over 1 million monthly active users.

There are some paid tools and partner tools which you can use to track retention in competitor website. Retention in terms of DAU or MAU upon install can be easily correlated with the uninstall rate. I find them quite useful, apart from the fact that they cost us and ask us to share data. Here are some: Survey Monkey, App Annie and Priori Data.