Top 5 Things I Learned From Odyssey
Adam Creamer
As the dust settles on the first retail battle of the holiday season, app designers and testers alike aren’t granted much time to reflect before prepping for the next onslaught of shopping and booking alike. The two months concluding months of the year are devoted to fixes on the fly, and with time at a premium, it can be relatively easy for software and mobile app testers to keep their nose to the grind and try to push through the rush.
Today, we’re suggesting a slightly modified approach. While it can be easy to lose yourselves in the gusto of the holiday season, filling holes in the boat as you try desperately to row to the shore that is the new year, perhaps a moment to pause and reflect may remind you that there’s a liferaft waiting for you under the seat within the hull.
We’re going to rewind on the Black Friday and Cyber Monday that just were, and consider some more immediate tweaks and subtle responses that we can make as the holiday season marches onward. Just as well, we’re going to note some potential takeaways for next holiday season as we round the turn into the new year and renew our focus on subsequent versions and rollouts of our mobile apps.
The first noteworthy movement in the testing realm that’s been vaulted into the forefront in the wake of this year’s Black Friday is the prevalence and newfound reliance on automation via AI tech. Testers across the industry are doubling down on utilizing AI-centered testing platforms to augment their quality assurance automation on the fly as the holiday season carries onward.
The manual QA of the past would require teams to essentially wait until after the holiday season to even address modest concerns plaguing the performance of their mobile apps, possibly identifying and patching catastrophic occurrences on the fly just to make it through. AI has transformed QA diagnostics, allowing teams to prioritize certain types of testing as they see fit and optimizing overall test coverage as necessary.
The other component of this exercise is the way in which AI and machine learning principles are creating testing spaces of exponential performance over time. The early adopters are now reaping the benefits of artificial intelligence’s ability to forecast and develop predictive analytics on performance and data, refining itself with each iteration. What this means is that with increased usage comes a greater propensity for AI testing to reform itself and operate in a manner that maximizes time allocation to certain testing procedures and focuses on likely problem areas that are learned over time. In this way, the lessons learned from the early stages of the holiday season are already being digested, processed and addressed by testing teams that rely on artificial intelligence and machine learning to automate their testing procedures.
As the retail and travel boom continues, it’s critical for mobile app designers and testers to look ahead at ways they can utilize the dominant trends that are setting the tone this holiday season. Leveraging trends like wayfinding and in-store purchases as we look ahead at the remainder of this holiday season is a crucial way to stay current with industry standards and set your app to perform at its peak.
The first method we’re going to consider is implementing wayfinding software into retail and travel apps, and considering how the holiday season may affect their utilization for testers and app designers. Wayfinding features in mobile apps are an excellent investment for physical companies, such as retail stores like Walmart and Target, to make as the holiday season is upon us. Interactive wayfinding encourages shoppers to rely on their screen for self-navigation and a wealth of services, freeing up employees to ensure that the shelves are stocked and the register lanes operate smoothly.
Implementing wayfinding requires regular vigilance on the behalf of testing teams that must consider the ever-changing needs and layout of stores, developing tests that support these ongoing measures. Retail wayfinding operates as a sort of go-between in the realm of navigation and content management systems, providing direction and interior layouts that rely on elements of GIS technology to function, but operate in a retail-driven manner that accommodates information otherwise delivered via map, brochures, coupon-coding or employee assistance. The entire point of wayfinding is to increase accessibility and confusion, which means that a smooth operation on behalf of the testing team is a key point of emphasis as the holiday season continues.
Just as well, retail mobile apps during the holiday season are increasingly turning to in-store purchase functions to drive commerce. Using data collection to drive customized shopping experiences, complex user profiles can be employed via your mobile app to deliver in-store purchase incentives that drive holiday commerce. Facilitating this type of commerce is a vital facet of mobile app testers in the midst of the holiday rush, and supporting in-store purchase features is a must to thrive this holiday season.
For testers, that can mean a number of focus points. Building out a rapid feedback channel may be an endeavor to develop for the subsequent holiday season, but it can be crucial for retail app teams looking to respond to QA concerns via a variety of different user devices, networks, and locations. Recognizing location-based reactions, particularly in retail settings, is key for a proper rapid feedback channel. Along those lines, this can be a good time to utilize AI to clean up complex data, so often a problem for retail mobile apps. With a variety of inputs from users, including demographic information, shopping habits and purchase points, waypoint geographic data, and a multitude of other areas that tests will comb, using AI testing software to clean up data and represent it in clear visualizations can assist with ongoing testing efforts as the holidays continue onward. Losing the signal to the noise is a surefire way to complicate a tester’s life, so recognizing the power of AI-driven testing apps (not unlike what Kobiton provides) will expedite the debugging process and spread a little bit of holiday joy to your testing team.