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Getting Rid of the Spinner Wheel

Amena Siddiqi

Prior to our current reality in the "new normal," consumers were already reliant on devices to remain connected and carry out daily tasks. With the COVID-19 pandemic, that reliance has grown to dependency, particularly when the app-dependent task is time-sensitive. Indeed, a report by Ericsson found that "delays in video streaming caused stress levels equivalent to the anxiety of taking a math test or watching a horror movie alone, and greater than the stress experienced by standing at the edge of a virtual cliff."

Add a global health pandemic to this predisposition for stress and you have a user group that is less forgiving of the dreaded spinner wheel than ever before. 

To examine how well mobile apps are meeting these high expectations, HeadSpin recently released a new benchmark for measuring app latency. The inaugural report examines the performance of 25 shopping, restaurant and food delivery apps, in five major cities, across popular iOS and Android devices, and multiple service providers. Applications selected for analysis in the report include Target, Amazon, Walmart, Burger King, Grubhub, Uber Eats, and more. The report details which apps are performing best amid the pandemic, and the most crucial contributing factors to user’s overall digital experience.

How Does Your App Stand Up?

The benchmark for contactless e-commerce apps was based on four key performance indicators (KPIs) for the app’s critical user journey: load product time, add to cart time, launch time, and search time. The last two are particularly interesting, so let’s break them down:

Launch- Have you ever gone to open an app, had it take too long, and moved onto another? If an app can’t load at the onset, it's likely a user will move on. In the HeadSpin study, although a few top performing apps took under two seconds to load, a significant proportion of the apps took much longer to load, bringing the average up to 4.1 seconds. According to Google/SOASTA research, as load times progress from one to five seconds, bounce rates increase by 90%.

Search- This is especially important for top retail apps. The report found that top retail apps, such as Walmart and Amazon averaged a search time of 2.4 seconds. Surprisingly, some of the largest retailers featured slow search times (negatively impacting the average), while the relatively new Shop app from Shopify excelled across all metrics, performing 5.5x faster than Amazon in returning search results.

By identifying and optimizing the key performance indicators for their mobile apps, businesses can improve conversions, reduce churn, achieve faster time to market, and publish apps with confidence on day one. 

Top Contributors to App Latency

The study additionally examined the major contributing factors to an app’s slow performance. Notably, the main culprits implicated included:

Slow TLS: Amazon’s iOS app took twice as long to launch compared to Home Depot, Kohl’s, and Best Buy because of slow TLS connections to multiple Amazon hosts.

Duplicate requests: Postmates took four times longer to launch on iOS compared to Uber Eats largely because of numerous connections opened to a Facebook host, and multiple duplicate requests made for the same resource.

SDK bloat: Grubhub was found to be the slowest delivery app to load on Android. This was mainly attributed to multiple calls to 3rd party hosts for initializing SDKs. The app’s performance could be improved by loading SDKs when needed rather than all at once during launch.

Large image files: Pizza Hut’s app launched sluggishly on Android because of large image files and slow server response on the backend. Using a JPEG or WebP file type instead of PNG would allow the screen to load faster with minimal loss of image quality.

Assuring Digital Excellence

Ensuring top quality mobile user experiences is an ongoing process. Businesses can assure optimal digital user experience throughout the app lifecycle by: 

Alerting on high priority issues and detecting build-over-build regressions early.

Testing native/hybrid/web app performance on real devices and real networks before, during, and after launch.

Automating functional, performance, and load testing end-to-end across applications, devices, and networks.

Analyzing performance and UX data with state-of-the-art AI and computer vision technology.

Monitoring and baselining live app KPIs by location, device, OS & carrier networks.

With all the changes that have and will continue to take place around digital connectivity and the app development ecosystem, we are losing patience with the spinner wheel, and have very little tolerance for latency. As brick and mortar businesses begin to open in the wake of the COVID-19 crisis, contactless options will continue to be in high demand as consumers err on the side of caution over in-person shopping. For now, as businesses and consumers remain dependent on digital commerce, more organizations will shift to web and mobile operations, and slow apps that do not deliver usable content promptly will lose out in the long run.

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Getting Rid of the Spinner Wheel

Amena Siddiqi

Prior to our current reality in the "new normal," consumers were already reliant on devices to remain connected and carry out daily tasks. With the COVID-19 pandemic, that reliance has grown to dependency, particularly when the app-dependent task is time-sensitive. Indeed, a report by Ericsson found that "delays in video streaming caused stress levels equivalent to the anxiety of taking a math test or watching a horror movie alone, and greater than the stress experienced by standing at the edge of a virtual cliff."

Add a global health pandemic to this predisposition for stress and you have a user group that is less forgiving of the dreaded spinner wheel than ever before. 

To examine how well mobile apps are meeting these high expectations, HeadSpin recently released a new benchmark for measuring app latency. The inaugural report examines the performance of 25 shopping, restaurant and food delivery apps, in five major cities, across popular iOS and Android devices, and multiple service providers. Applications selected for analysis in the report include Target, Amazon, Walmart, Burger King, Grubhub, Uber Eats, and more. The report details which apps are performing best amid the pandemic, and the most crucial contributing factors to user’s overall digital experience.

How Does Your App Stand Up?

The benchmark for contactless e-commerce apps was based on four key performance indicators (KPIs) for the app’s critical user journey: load product time, add to cart time, launch time, and search time. The last two are particularly interesting, so let’s break them down:

Launch- Have you ever gone to open an app, had it take too long, and moved onto another? If an app can’t load at the onset, it's likely a user will move on. In the HeadSpin study, although a few top performing apps took under two seconds to load, a significant proportion of the apps took much longer to load, bringing the average up to 4.1 seconds. According to Google/SOASTA research, as load times progress from one to five seconds, bounce rates increase by 90%.

Search- This is especially important for top retail apps. The report found that top retail apps, such as Walmart and Amazon averaged a search time of 2.4 seconds. Surprisingly, some of the largest retailers featured slow search times (negatively impacting the average), while the relatively new Shop app from Shopify excelled across all metrics, performing 5.5x faster than Amazon in returning search results.

By identifying and optimizing the key performance indicators for their mobile apps, businesses can improve conversions, reduce churn, achieve faster time to market, and publish apps with confidence on day one. 

Top Contributors to App Latency

The study additionally examined the major contributing factors to an app’s slow performance. Notably, the main culprits implicated included:

Slow TLS: Amazon’s iOS app took twice as long to launch compared to Home Depot, Kohl’s, and Best Buy because of slow TLS connections to multiple Amazon hosts.

Duplicate requests: Postmates took four times longer to launch on iOS compared to Uber Eats largely because of numerous connections opened to a Facebook host, and multiple duplicate requests made for the same resource.

SDK bloat: Grubhub was found to be the slowest delivery app to load on Android. This was mainly attributed to multiple calls to 3rd party hosts for initializing SDKs. The app’s performance could be improved by loading SDKs when needed rather than all at once during launch.

Large image files: Pizza Hut’s app launched sluggishly on Android because of large image files and slow server response on the backend. Using a JPEG or WebP file type instead of PNG would allow the screen to load faster with minimal loss of image quality.

Assuring Digital Excellence

Ensuring top quality mobile user experiences is an ongoing process. Businesses can assure optimal digital user experience throughout the app lifecycle by: 

Alerting on high priority issues and detecting build-over-build regressions early.

Testing native/hybrid/web app performance on real devices and real networks before, during, and after launch.

Automating functional, performance, and load testing end-to-end across applications, devices, and networks.

Analyzing performance and UX data with state-of-the-art AI and computer vision technology.

Monitoring and baselining live app KPIs by location, device, OS & carrier networks.

With all the changes that have and will continue to take place around digital connectivity and the app development ecosystem, we are losing patience with the spinner wheel, and have very little tolerance for latency. As brick and mortar businesses begin to open in the wake of the COVID-19 crisis, contactless options will continue to be in high demand as consumers err on the side of caution over in-person shopping. For now, as businesses and consumers remain dependent on digital commerce, more organizations will shift to web and mobile operations, and slow apps that do not deliver usable content promptly will lose out in the long run.

Hot Topics

The Latest

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

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 ...