Retention is one of the most important components of the user lifecycle, and should hold a central spot in any mobile marketer’s dashboard. On top of providing an invaluable indication of the quality of an app, retention metrics have a direct impact on the calculation of customer lifetime value (LTV) for freemium apps.
User retention however suffers from an existential problem: the lack of consensus over a common definition of what it actually means or how it’s computed. Retention benchmarks are already extremely different across app categories, or the type of service provided. If, on top of this, different definitions are used across the board, the metric stops having any meaning at all.
There is unfortunately no single, canonical way to calculate retention: different methods might be relevant for different analytical purposes. It is up to you as an app publisher to figure out which one(s) work out the best for your own goals.
Below is a simple typology with five definitions of retention. Out of these, two are the most widely used (and get mixed up the most). The other three are less common but can still become relevant for certain types of apps or publishers.
Disclaimer: the names given here are far from official, but rather attempt to describe the specific use case as well as possible. If you can think of a better name, please let me know
Here is the general formula to calculate retention across all definitions:
Regarding the legend, “tick” signs mark the days on which users need to open the app at minima in order to be considered as retained for a given definition. “The X” signs are only there for the sake of clarity as they mark days which do not contribute to considering the users retained for a particular definition.
1. Classic Retention
2. Rolling Retention
3. Full Retention
4. Return Retention
5. Bracket-Dependent Return Retention
Which retention do you use? Do you think the typology should be improved? Let me know in the comments or get in touch directly! This article was originally published on the AppLift blog.
About the author
Thomas heads up content marketing at app marketing platform AppLift. As such he’s in charge of sourcing, curating, creating and distributing insightful content to increase visibility and thought leadership for the company. Thomas loves to scrutinize the relentless and trilling developments of the mobile industry. He can be reached at firstname.lastname@example.org Also see: Applift Blog | Insights | Twitter | Facebook
CEO at PaperLit (part of Datrix | AI applications group) a tech company specialised in the digital transformation, distribution and monetization of content via mobile and smart speakers, for publishers and brands, with hundreds of customers worldwide.
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