Skip to main content

Apps That Crash? How App Stability Impacts User Experience and Affects a Business's Bottom Line

James Smith
SmartBear

Mobile apps play an increasingly central role in the interactions between customers and brands. We know that users spent about $34 billion on apps in Q2 of 2021 , breaking last year's Q2 record by a whopping $7 billion. With nearly 1.8 million apps on the Apple app store and more than 1,000 new apps released every day, the modern smartphone user has endless choice and variety, translating to higher user experience standards.

B2C apps allow customers to engage with both new and staple brands alike, driving revenue growth opportunities for businesses. B2B apps, on the other hand, give organizations the opportunity to modernize things like training, employee engagement, workflow management, logistics and planning, and more, without the need for technical experts on staff.

One of the strongest indicators we have of smooth, error-free user experiences is app stability. As a vital business metric, an app's stability score translates directly to customer conversion, engagement and retention. The importance of app stability cannot be overstated.

Bugsnag recently released the results of its second app stability report: Application Stability Index (ASI): Characteristics of Leading Mobile Apps. The report analyzed app stability scores in industry verticals such as B2B SaaS, eCommerce, consumer goods, finance & banking, gaming, technology and travel & hospitality. The goal of the ASI is to help organizations understand how their app is performing compared to others and what level of stability it needs to achieve a leader status in its industry.

The results of the ASI highlight the need for regular and proactive error monitoring and stability management, meaning how often an app crashes. Overall, the data showed that of the ten verticals analyzed, travel and hospitality earned the highest median app stability score (99.90%), followed by a three-way tie among B2B sales, eCommerce and finance and banking, with each scoring 99.85%. Media and entertainment was at the bottom (99.65%).

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users.

Higher Stability Score = Higher App Store Ratings

The median stability score across all of the apps analyzed in the ASI was 99.8%. The ASI found that just a 1% lower stability score can lead to a drop of almost 1 whole star in the app stores. That fact alone has huge implications for developers and app engineers. More stable apps drive more exceptional user experiences, maximize retention and build competitive advantage, which is critical to an app's long-term growth and success. To secure higher app store ratings, an app must deliver on usefulness, design, engagement and stability. Being able to balance all four of those elements is key to growing the app's reputation and rating, and thus, gaining users and boosting an app's profitability.

Higher Stability Score = Higher Interaction Volume and Value

While we typically define app stability as a calculation of crash-free sessions, it is also impacted by business decisions. Organizations must analyze the value and volume of interactions in order to get an accurate representation of their app stability. In terms of value, that means the interest showed by a customer for a certain product or service and their overall experience with the app, which can translate into brand loyalty, referrals to friends and family and more in-app purchases. Volume, on the other hand, looks sheerly at the number of interactions with a specific app. While value and volume are both indicators of higher app stability, value of the interaction may be the strongest predictor of app stability because it can help circle resources back into the improvement of an app. Since interaction value determines product and pricing models, that carries over to an engineering teams' incentives to roll out bug fixes and feature releases.

Weekly Release Cadence Will Become the Norm

Software engineers are adopting a weekly release cadence to replace the bi-weekly norm. Data across industries indicate that apps are being updated with a new version on average four times within a thirty-day time span. This is important because it tells us there is a greater push by developers to regularly deliver features and, most importantly, address software bugs that decrease stability scores. The direct correlation between app store ratings and accelerated release cadences tells us that, with the right tools, developers can increase release frequency without sacrificing quality. It's worth noting here that some bugs are inevitable in any app release. Software engineers must only worry about fixing the bugs that matter — that is, the ones that tangibly impact the user experience. To identify which bugs matter, comprehensive diagnostic tools are essential, enabling engineers to prioritize errors and make data-drive decisions.

The ASI also indicated that higher frequency of release helps app developers improve the dynamic with their customers and ultimately build more confidence in their development strategy. Adopting a progressive delivery strategy, defined by phased rollouts, feature flags and A/B testing, is a key part of enabling these quicker app release cycles.

Conclusion

Apps play an increasingly prominent role in our personal and professional lives, and users are coming to expect smoother and more dynamic app experiences. Even though app stability is a KPI owned by engineers and developers, its impact is felt throughout the larger organization through brand reputation and the ability to compete with similar apps. Having a stronger focus on app stability will enable engineering teams to build healthier apps that deliver superior customer experiences.

James Smith is SVP of the Bugsnag Product Group at SmartBear

Hot Topics

The Latest

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Apps That Crash? How App Stability Impacts User Experience and Affects a Business's Bottom Line

James Smith
SmartBear

Mobile apps play an increasingly central role in the interactions between customers and brands. We know that users spent about $34 billion on apps in Q2 of 2021 , breaking last year's Q2 record by a whopping $7 billion. With nearly 1.8 million apps on the Apple app store and more than 1,000 new apps released every day, the modern smartphone user has endless choice and variety, translating to higher user experience standards.

B2C apps allow customers to engage with both new and staple brands alike, driving revenue growth opportunities for businesses. B2B apps, on the other hand, give organizations the opportunity to modernize things like training, employee engagement, workflow management, logistics and planning, and more, without the need for technical experts on staff.

One of the strongest indicators we have of smooth, error-free user experiences is app stability. As a vital business metric, an app's stability score translates directly to customer conversion, engagement and retention. The importance of app stability cannot be overstated.

Bugsnag recently released the results of its second app stability report: Application Stability Index (ASI): Characteristics of Leading Mobile Apps. The report analyzed app stability scores in industry verticals such as B2B SaaS, eCommerce, consumer goods, finance & banking, gaming, technology and travel & hospitality. The goal of the ASI is to help organizations understand how their app is performing compared to others and what level of stability it needs to achieve a leader status in its industry.

The results of the ASI highlight the need for regular and proactive error monitoring and stability management, meaning how often an app crashes. Overall, the data showed that of the ten verticals analyzed, travel and hospitality earned the highest median app stability score (99.90%), followed by a three-way tie among B2B sales, eCommerce and finance and banking, with each scoring 99.85%. Media and entertainment was at the bottom (99.65%).

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users.

Higher Stability Score = Higher App Store Ratings

The median stability score across all of the apps analyzed in the ASI was 99.8%. The ASI found that just a 1% lower stability score can lead to a drop of almost 1 whole star in the app stores. That fact alone has huge implications for developers and app engineers. More stable apps drive more exceptional user experiences, maximize retention and build competitive advantage, which is critical to an app's long-term growth and success. To secure higher app store ratings, an app must deliver on usefulness, design, engagement and stability. Being able to balance all four of those elements is key to growing the app's reputation and rating, and thus, gaining users and boosting an app's profitability.

Higher Stability Score = Higher Interaction Volume and Value

While we typically define app stability as a calculation of crash-free sessions, it is also impacted by business decisions. Organizations must analyze the value and volume of interactions in order to get an accurate representation of their app stability. In terms of value, that means the interest showed by a customer for a certain product or service and their overall experience with the app, which can translate into brand loyalty, referrals to friends and family and more in-app purchases. Volume, on the other hand, looks sheerly at the number of interactions with a specific app. While value and volume are both indicators of higher app stability, value of the interaction may be the strongest predictor of app stability because it can help circle resources back into the improvement of an app. Since interaction value determines product and pricing models, that carries over to an engineering teams' incentives to roll out bug fixes and feature releases.

Weekly Release Cadence Will Become the Norm

Software engineers are adopting a weekly release cadence to replace the bi-weekly norm. Data across industries indicate that apps are being updated with a new version on average four times within a thirty-day time span. This is important because it tells us there is a greater push by developers to regularly deliver features and, most importantly, address software bugs that decrease stability scores. The direct correlation between app store ratings and accelerated release cadences tells us that, with the right tools, developers can increase release frequency without sacrificing quality. It's worth noting here that some bugs are inevitable in any app release. Software engineers must only worry about fixing the bugs that matter — that is, the ones that tangibly impact the user experience. To identify which bugs matter, comprehensive diagnostic tools are essential, enabling engineers to prioritize errors and make data-drive decisions.

The ASI also indicated that higher frequency of release helps app developers improve the dynamic with their customers and ultimately build more confidence in their development strategy. Adopting a progressive delivery strategy, defined by phased rollouts, feature flags and A/B testing, is a key part of enabling these quicker app release cycles.

Conclusion

Apps play an increasingly prominent role in our personal and professional lives, and users are coming to expect smoother and more dynamic app experiences. Even though app stability is a KPI owned by engineers and developers, its impact is felt throughout the larger organization through brand reputation and the ability to compete with similar apps. Having a stronger focus on app stability will enable engineering teams to build healthier apps that deliver superior customer experiences.

James Smith is SVP of the Bugsnag Product Group at SmartBear

Hot Topics

The Latest

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...