The "Crash and Burn" Report Findings
January 19, 2017

Andrew Levy
Apteligent

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The correlation between mobile app crashes and increasing churn rates (or declining user retention) has long been suspected. In the report, titled Crash and Churn, Apteligent set out to understand the impact of per user crash rate on churn, using both approaches to the definition of churn. Whereas an app's crash rate is the total number of crashes divided by number of app loads, the analysis employed a per user crash rate to allow us to consider the segments of the population experiencing that issue.

The report contains many key takeaways for digital marketers, product managers, and mobile development teams:

Crashes can increase churn by as much as 534 percent

This represents a six-times increase from your "average" churn rate. The report found a more accurate depiction of crash and churn relation when viewed through Android devices over IOS. IOS displays a lower churn rate compared to Android, but, due to the platform design, users cannot send a crash report until the next time a user opens the app. And, in some cases, the user could use the app, the app crashes and that user may never go back to that app again so, that crash won't be counted as a churn cause.

Crashes have a significant impact on next day app opens by as much as 8x the normal rate

The report calculates how likely a user would be to return the day following a crash taking into consideration that 1.8 percent of users don't return to an app the next day even after a crash-free experience. As the per user crash rate approaches 100 percent, the churn rate increases to almost 15 percent. Again, IOS limitations led us to believe that Android had more accurate data.

Less engaged users, or users with lower app opens per day, tend to churn at higher rates based on crashes

The fewer apps a user engages with, the more sensitive they are to crashes, increasing their churn rate. The report notes that as crashes per day increase, we see a steady stream of churning users, especially those that load an app ten times or fewer per day. Perhaps one of the most interesting behaviors discovered was that the inverse of this is true as well. The more a user uses an app, the more resilient they become with crashes.

The impact of crashes on churn also varies by app store category

Shopping and finance apps, the most revenue-critical, were particularly vulnerable to crashes causing increased churn rates, while games and travel were much more resilient. While the data proves the aforementioned to be true, we cannot prove why users of games and travel are more forgiving of app crashes. We can only speculate that games and travel apps crashing may not be be enough to sway users away from addictive games or travel necessities, regardless of frustration with the experience.

For app owners, the report underscores the immediate return on investment that comes with applying the right resources to app performance. There are immediate and medium term revenue losses associated with churning app users and customers. In addition, the cost of acquiring new users is much higher than those associated with retaining existing users.

In 2017, the organizations who win on mobile will be those that select vendors applying proven data science techniques to big data collection. Data, without insights, is noise.

Andrew Levy is Co-Founder and Chief Strategy Officer of Apteligent.

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