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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.

Hot Topics

The Latest

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...