Consumers today live in a mobile-first world. According to research from App Annie, “consumers logged a record 3.8 trillion hours on their mobiles in 2021 and downloaded some 230 billion apps.”
Further putting a stamp on mobile dominance is that Americans, on average, are now spending less time watching TV and spending more time on their mobile phones.
As we all spend more time on our devices, technology leaders are being pressured to deliver more and better native mobile experiences faster than ever before. From banking to retail, healthcare to transportation, every industry is realizing that offering mobile app experiences is critical to survival.
Technology leaders have a challenging task at hand when it comes to delivering these experiences — especially as app quality, security and business agility are measurements for success. Employing native mobile test automation strategies as part of the development process can help ensure that these requirements are met and that consumers are delighted.
Below, we address some of the top trends driving the need for native mobile app testing and quality assurance (QA). We also explore why adding artificial intelligence (AI) to the testing approach can rapidly create next-gen mobile experiences for customers.
Trends driving the challenges of quality mobile app experiences
While there are numerous reasons and subjective circumstances that make the quality assurance of native mobile apps more difficult than, say, web or desktop applications, the convergence of three trends adds a multiplier effect to the complexity of generating delightful mobile app experiences to consumers.
The vast world of mobile devices
Building a native mobile app has become a top priority for many businesses to win over customers. However, the explosion of different mobile devices used by customers to access native mobile apps is an enormous challenge for QA and Agile software development teams. Not only do these teams need to account for new devices entering the market, but they need to be able to scale their mobile testing practices across multiple device types to validate apps on any device that customers are using them.
According to Statista, In 2021, the number of mobile devices operating worldwide stood at almost 15 billion, up from just over 14 billion in the previous year. The number of mobile devices is expected to reach 18.22 billion by 2025, an increase of 4.2 billion devices compared to 2020. Each new generation of devices between Apple, Samsung, Google and several other original equipment manufacturers (OEMs) means that test coverage must expand quickly and adjust rapidly for market demand.
Furthermore, each device is expected to be different in terms of device resolutions/screen size, operating systems (and versions supported), screen orientations, scroll views and other factors. Most of the time, this creates numerous development challenges that can slow down delivery cycles — and, worse, decrease the quality of the mobile app.
Last but not least, testing native mobile apps is inherently more challenging than testing web applications. Not only is the setup of hardware needed expensive and cumbersome, but the software is usually more difficult to handle.
Faster development cycles impact the scalability of mobile testing
Time to market for getting new digital products, services and features into the hands of consumers is a competitive advantage. Ultimately, businesses that ship more grow faster. However, QA and testing have created lag time and bottlenecks for modern app development as the entire delivery lifecycle has contracted with newer development tools making the build and deployment of applications simpler. Mobile app testing needs to scale in tandem to ensure faster delivery time.
There are many different approaches to scale test automation for native mobile applications today. Options range from running locally with virtual devices (simulators/emulators) or real devices to a local mobile grid/lab to docker containers/virtual machines, or to remote cloud test services.
Testing native mobile applications is a challenging endeavor, given that there are many moving parts and many points of failure involved. To execute successfully, everything needs to work in complete harmony. For example, executing a single Appium test entails the following:
- An Appium server with all required dependencies installed.
- A mobile device or emulator/simulator.
- Valid test code logic.
- A compiled mobile application.
- Application web service APIs running and stable (if applicable).
Not just “hoping for the best”
To scale tests across multiple devices for cross-device validation needs, get ready to introduce more points of failure for each device that is tested. A test on one device may execute just fine, but on another, it may fail for various unknown reasons. This can cause development and QA teams to spend a vast amount of time investigating and debugging these failures to find the root cause.
Adding more devices to the mix means adding even more conditional logic to test code to accommodate these devices and their inherently different characteristics (screen size, operating system, orientation, locators and other factors). This all adds more coded logic to a test suite or framework to maintain and eventually refactor in the future when the app changes.
Oftentimes, for the reasons mentioned above, companies can’t afford to scale their mobile test coverage across different devices due to test maintenance, more test flakiness, longer test execution times or direct access to different devices not being possible. “Hoping for the best” generally doesn’t work out in these situations and ultimately, the app experience suffers, causing customers to opt-out.
Brand = mobile experience
It is not enough for companies to simply deliver mobile apps faster; apps must be visually and functionally perfect at all times. That’s because a company’s relationship with its customers is reflected in how the market perceives every aspect of its own brand experience, particularly on mobile, from identity to positioning, to UI/UX.
Take, for example, a mobile app for a retail company. If the “Add to Cart” button is non-functional or hidden behind another button on certain screen sizes when the user tries to click, or the text is off-center or difficult to read, this company could lose out on not just one sale, but many before the bug gets fixed.
Worse, it could lose potential customers and brand advocates forever. This becomes even more critical when it comes to industries like healthcare, banking, and insurance, where functional and visual issues with an app could have serious consequences for end users, which won’t be tolerated.
If you don’t believe that visual defects, poor UI/UX experiences and other functional miscues on a mobile website or application can tarnish a brand’s reputation in seconds, consider the following stats gathered by uxcam.com:
- 88% of users are less likely to return to a website after a bad user experience.
- Mobile users are five times more likely to abandon a task if the website isn’t optimized for mobile.
- 80% of all internet users own a smartphone.
- 53% of mobile users leave websites in just three seconds.
- 90% of users have stopped using an app due to poor performance.
- Only 55% of companies are currently conducting any user experience testing.
And PWC found that 32% of customers would leave a brand they loved after just one bad experience.
Why visual AI is needed for testing and improving native mobile apps
Companies are trying various approaches to address these challenges, including “shifting left,” where the development team does more testing responsibilities and leveraging AI to accelerate the testing process and achieve higher coverage.
But visual AI is the technology that will bring mobile apps into the next generation of customer experiences and help ensure brand loyalty. Software engineering leaders and development teams can leverage visual AI to better equip themselves to handle the growing challenges of mobile app testing via improved quality engineering tactics and strategies.
Without visual AI, the number of UI/UX permutations for a mobile app is overwhelming and impossible for development and QA teams to navigate. Thankfully, there is a new technological approach powered by visual AI to asynchronously validate a native mobile application in parallel and easily across many different devices in a single test execution (verses dozens or hundreds).
This means that visual AI-powered native mobile testing can deliver instant access and validation to a massive inventory of mobile devices with varying screen sizes/viewports and operating systems. And, since it’s asynchronous, teams are not waiting on the device to connect or for test results, which frees up tests to execute as fast as possible.
The promise of visual AI
Today, visual AI-powered mobile testing technologies can outperform traditional in-house device testing farms and traditional real-device testing clouds; tests that took 8 to 10 minutes are now being run in under two minutes.
Engineering teams that need to ship quality mobile apps quickly are using visual AI-powered technology to cut test execution time by up to 90%. Furthermore, technology teams using these technologies don’t need extensive training. Users can get up and running in a few minutes. Using already built-in advanced computer vision AI algorithms, they can run automated tests across simulated mobile devices in seconds. Teams using this technology report significantly higher test coverage than the benchmark and faster release velocity.
At the end of the day, knowing that visual and functional regression can be immediately spotted with visual AI across all mobile device variations gives peace of mind to those responsible for ensuring that a mobile user experience is exactly as intended for the customer.
The end goal for any company dealing with the challenges of its mobile app delivery and brand experience is to future-proof its approach so that native mobile app testing can finally keep pace with mobile app development. With visual AI, it is now possible to ship mobile apps continuously with the speed and accuracy not seen with traditional mobile testing techniques.
Moshe Milman is cofounder and COO at Applitools.
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