Future Trends in User-Centric Testing

Traditional testing methods continue to give way to testing embedded with technology, including AI and ML. These technologies drive data-driven methods that make testing more accurate and efficient.

With more time to prioritize the user’s experience and preferences, we can expect growth in user-centric testing, including increased adoption and implementation throughout the SDLC. When testing begins while the code is still in design and development, organizations can make actionable progress on meeting accessibility and usability goals. Development teams must embrace creating digital products that resonate with an inclusive and diverse set of customers. 

Let’s explore the trends that will shape user-centric testing in the near future, affecting application usability, digital accessibility and overall end-user quality. 

#1: Increased investment in user-centric testing 

Expect an increased focus on the user, including user-centric testing and ensuring customer satisfaction for an inclusive and diverse customer set. As digital competition increases, so does the need to please a broader set of customers to build profitability.

Testing teams, whether Agile or traditional, have discovered that many beautiful and expertly designed applications fail to meet customer needs. Why is that? Along the development and testing life cycle, the priority for deploying software becomes focused on the release schedule — how to deliver the best quality within a specified timeframe. In these instances, teams plan on making some percentage of corrections post-release. Essentially, application users become caught up in a continuous release process to receive the features they need or want. 

In future iterations, focus on the customer rather than the regression testing priorities. Usability, user acceptance and accessibility are critical to broaden customer reach. Incorporate the core principles of user-centric testing into development teams by: 

• adopting a user-centric mindset to manage the testing lifecycle
• prioritizing customer wants over technical or provider preferences
• involving customers in testing for ongoing feedback
• validating real-world situations rather than preparing test environments
• testing with a customer focus throughout every development cycle
• embracing diverse perspectives
• expanding test coverage.

As organizations deepen their commitment to user-centric testing, they will strive to get the customer involved as soon as possible. Build the development and testing team’s awareness with an intimate and complete understanding of the widest range of customer’s preferences and expectations. Find out what makes customers use and recommend a product. 

#2: AI continues to influence testing

If you haven’t heard, AI and ML technology are significantly affecting software development and QA testing — and just about everything else too. Some of the ways in which AI influences user-centric testing include: 

• enabling automatic test case creation
• providing improved test automation 
• using customer analytics
• making use of biometric data
• using sentiment or emotional analysis

AI tools provide the entire product development team with advanced data analysis tools, which affect how teams design and test applications in accordance with a user-centered focus. If enough historical data exists, AI tools can track customer patterns and trends when the application is in use. Use that real customer workflow data that otherwise sits in your existing database. Visualize and analyze how all customers use an application to gather feedback that influences design, code and quality. 

AI tools also provide enhanced abilities to include user-centric, usability and user acceptance testing in an automated testing strategy. Additionally, many AI tools enable testing teams to use predictive analytics to simulate user actions and predict usability and accessibility issues. For user-centric testing, AI improves the ability to understand how a wider group of customers uses an application or product.

QA teams also use AI when performing user research or user testing. By using biometric and emotional analysis data, testers can see how an application functions and how defects affect a user. Factoring in biometrics and emotion analysis increase the probability that an application meets the needs and usage of all customers. 

#3: Implementing user-centric testing throughout development

Expect user-centric testing to become part of the testing process throughout the entire software development lifecycle. Development teams and testers can leverage user-centric testing data to create a continuous customer feedback loop. When customer feedback is included, it is then automatically incorporated into dev team processes. 

Crowdtesting is a simple and effective way to reap the benefits of user-centric testing without overloading internal teams. Crowdtesting can occur without slowing development work or even a release schedule — no need to overload internal testers or other team members. Simply schedule a crowdtesting run using known customer characteristics or preferences, such as OSes, devices and customer roles. If preferred, the internal testing team may then review the test results and raise issues for the team to address.