The use of mobile apps has risen sharply in recent years, and so too has their importance to many businesses and organizations. Driven by the prevalence of smart phones, tablets and mobile internet connections, recent data revealed that since 2008, 100 billion apps have been downloaded from Apple’s App Store alone.
Once an app has been successfully developed and launched, it’s sink or swim time as it enters a crowded and highly competitive market place. A recent study by Google and Ipsos found that as many as one in four downloaded apps are never used. And even when they are, poor user experience can be responsible for missed conversions, and, in the case of e-commerce apps, lost sales and revenue. Understanding and perfecting the mobile app experience is therefore essential for any business when it comes to ensuring repeat engagement with returning users.
Mobile device users utilize apps on the go (as “mobile” suggests) and can often use multiple apps at once. However, the tasks they are likely to execute via an app are probably different from what they would do on your website.
In the context of multitasking and being on the go, the expectation for any app is an effective, efficient and satisfying experience. Businesses or organizations looking to assess the performance of their live app should be mindful of this customer expectation and should, in the first instance, look to understand the following from mobile analytics: 1) what is happening on the app, 2) which tasks are being executed on an end to end journey and 3) which tasks appear to be unfulfilled.
To develop a full understanding of an app, it’s vital to obtain a more detailed understanding of the user experience. Task-based app testing allows organisations to observe how an app is being used in a particular scenario and where improvements to the user experience can be made. Here’s a look at how it works in practice.
Step 1: Getting an overview of your app
Imagine you’re working on behalf of a betting company and have just launched a new app including updated functionality e.g. in-play live betting. Naturally, you’ll want to know how it’s performing and if there’s any particular areas that need attention. Of course, the monetization of the new functionality will be obvious based on daily bets recorded via the in play live betting function.
There are a number of quick-fire ways to gauge how your app is performing. The first, and perhaps most obvious indication, is the number of times the app has been downloaded. This will often depend on a number of factors, including the size of the business and how the app has been marketed. For example, it’s often assumed that the majority of apps are found through an app store. In fact, just 40% of smartphone users browse for apps in app stores, with others hearing about new offerings through social media, search engines, and websites as well as through a variety of other traditional sources.
However, it’s important to avoid attaching too much significance to this figure – an app with a high number of downloads may score equally poorly when it comes to attracting repeat visitors. To take the example of the betting company – if you’ve achieved your download target, but are finding fewer bets are being placed than expected, it’s clear the app isn’t fulfilling its purpose.
Step 2: Developing user insights
While there are a number of analytic tools that can help to track user patterns, and in particular returning user patterns, this data can often lack the context that task-based app testing provides. For example, the launch of the new app may have seen a noticeable drop in the amount of bets placed during football games. To get a true sense of why this is occurring, a group of test users can be asked to perform a test task through testing software that can be integrated into the app itself. Test users can then be invited to take part through the app too, meaning the betting company can be assured it is recruiting participants who represent its target audience.
Once the participants have completed the task, both quantitative and qualitative data will have been gathered through the process. The betting firm will have information indicating task success rates, task error rates, abandonment rates and timeouts. They will also be able to see how much time is spent on tasks and overall ratings of satisfaction. This quantitative data can be enhanced through presentation, with clickstreams and video session data (masking the recording of personal confidential information) all indicating how users are interacting with the app, as well as user feedback comments, which provide an insightful qualitative aspect to the research.
Step 3: Making amends
Once the data is in, it’s time to analyze the findings and consider the changes that may need to be made. Are customers interacting with the app as predicted? To take the example of the betting company, the app may have been developed with a specific section linking customers to betting opportunities on live football matches. But, if users completing the task weren’t scrolling down to the section or were taking a while to locate it, this flaw would be reflected in data such as completion times and abandonment rates. Task-based app testing’s ability to gather feedback comments from the user may further reinforce this issue, providing the evidence needed to consider redesigning the app layout.
In this instance, the live betting options may want to be placed more prominently within the app, or even integrated into other sections if users were shown to be instinctively visiting these areas during the task instead. Once changes have been made, the process can be repeated to see if a redesign has had the desired effect and improved key metrics such as task success rates.
Regardless of the nature of the app itself, all businesses and organizations must strive to keep customers engaged. Key to this is understanding the strengths and weaknesses of the app and how customers respond when using it. Task-based testing provides an approach that allows companies to gather both quantitative and qualitative feedback from a target audience who are testing the app in a real-life setting. The outcome is the detailed and contextual understanding needed to drive the development and promotion of a top-class app.