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The "Crash and Burn" Report Findings

Andrew Levy

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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The "Crash and Burn" Report Findings

Andrew Levy

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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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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