When I began my career as a UX designer, many product developers shared the aspiration of building great products with numerous features. While building great products is a worthy goal, teams often paid little attention to users’ real needs when deciding what features to build, which is a great shame. App development is not just about creating a product but about solving a problem for users. As an essential part of human-centered design, user research helps us to crystallize users’ problems and create solutions that directly address them.
As a design lead, I make user research an integral part of my team’s design process. We use various approaches to interacting with users to help us tailor the end product to the audience’s needs. In this article, I’ll share some of my experiences conducting different types of user research, focusing mainly on in-depth user interviews, usability testing, and surveys, but we’ve used all of the approaches that Figure 1 depicts. You’ll learn how to use each of these types of user research and discover useful methods of collecting and analyzing users’ thoughts. Read More
Metrics are the signals that show whether your UX strategy is working. Using metrics is key to tracking changes over time, benchmarking against iterations of your own site or application or those of competitors, and setting targets.
Although most organizations are tracking metrics like conversion rate or engagement time, often they do not tie these metrics back to design decisions. The reason? Their metrics are too high level. A change in your conversion rate could relate to a design change, a promotion, or something that a competitor has done. Time on site could mean anything. Read More
Usability testing has long been a cornerstone of the design and development of software products, ensuring that user interfaces meet the needs and expectations of users. Traditionally, the testing process has relied heavily on human insights, often involving UX research methods such as usability studies, A/B testing, user interviews, and surveys. But these approaches, while effective, are time consuming and often limited in their scope and scalability.
Enter the age of artificial intelligence (AI) and machine learning (ML). These technologies are revolutionizing the field of usability testing, offering new dimensions of efficiency and accuracy. Through the integration of usability testing with AI and ML, the software industry is witnessing a paradigm shift from conventional, manual testing to more sophisticated, data-driven approaches. Machine learning—with its ability to analyze vast amounts of user data and learn from user interactions—is not just enhancing usability testing; it’s reshaping it. AI and ML are also empowering product teams to create more personalized user experiences and making software more user centric than ever before. Read More