Retention Champions: What we can and cannot learn from health app loyalty data

When comparing user retention across app categories, Health and Fitness apps are clearly leading the pack: 30 days after its initial installation and launch, almost 50% of Android users are still using a Health and Fitness app. Weather apps come in second with a 30-day retention rate of ca. 35%, News & Magazines apps rank third with ca. 27%:

30-day-retention by app category (March 2016, Android)

These numbers, published by Yahoo-owned Flurry Analytics in May 2016, are encouraging for everyone in the digital health space. However, the Health and Fitness category covers a wide spectrum of apps, from 7-minute workouts to medical devices. So how about a more narrow definition of Health apps as apps supporting managing a health condition? As IMS Health analysed in 2015, ca. 24% of the apps available support disease and treatment management:

Health Apps by Use Case (IMS Health, 2015)

How do these more narrowly defined health apps perform in terms of loyalty? Data for this subgroup is not easily available. On the contrary, for privacy reasons these apps are most likely (and perhaps hopefully) underpresented in Flurry’s data: Flurry has historically not been the go-to destination for apps handling sensitive user data, not lastly due to Steve Jobs‘ very explicit disapproval. Nevertheless a look at Flurry’s data supports this believe: On its second axis of app loyalty, the frequency of use per week, Health and Fitness apps score 3 uses per week:

Flurry App Loyalty Matrix 2016

Given that disease management apps center on use cases like medication management, this number appears low.

The upshot? From all data available, digital health apps can engage their users for an unrivalled period of time. In particular for the subcategory of disease management apps, this most likely goes along with a very high frequency of use, often more than once a day. Beyond that, drawing conclusions from aggregate benchmarks proves hard for an app category with use cases as specific as we find them in digital health.

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