Note that when we say that these DAUs are being “lost” it doesn’t mean that users are suddenly going completely inactive – they might just be using the app once per week, or a few times per month. This work is generally focused on the first days of usage, whereas the long-term numbers are hard to budge, no matter how many reminder emails you send. This maps to my own experience, where I see that most of the leverage in improving these retention curves happen in how the product is described, the onboarding flow, and what triggers you set up to drive ongoing retention. The key to success is to get the users hooked during that critical first 3-7 day period. For ‘decent’ apps, the majority of users retained for 7 days stick around much longer. Users try out a lot of apps but decide which ones they want to ‘stop using’ within the first 3-7 days. (*Tabular data in the footnotes if you’re interested)Īnkit Jain, who collaborated with me on this essay, commented on this trend: The other way to say this is that the average app mostly loses its entire userbase within a few months, which is why of the >1.5 million apps in the Google Play store, only a few thousand sustain meaningful traffic. As my readers know, this is often used in a sentence like “the D7 retention is 40%” meaning that seven days after the initial install, 40% of those users was active on that specific day.īased on Quettra’s data, we can see that the average app loses 77% of its DAUs within the first 3 days after the install. The first graph shows a retention curve: The number of days that have passed since the initial install, and what % of those users are active on that particular day. I’ve worked with mobile intelligence startup Quettra and it’s founder/CEO Ankit Jain (formerly head of search+discovery for Google Play) to put together some exclusive data/graphs on retention rates** based on anonymized datapoints from over 125M mobile phones. Today, I’m excited to share some real numbers on mobile retention.
The root cause is that the average app has pretty bad retention metrics. In a recent essay covering the Next Feature Fallacy, I explained why shipping “just one more feature” doesn’t fix your product.
Exclusive data on retention curves for mobile apps
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