Caleb Sponheim Ph.D. is a User Experience Specialist with Nielsen Norman Group. A former computational neuroscientist, his expertise includes quantitative user experience research, statistics, analytics, and data science.
An AI agent pursues a goal by iteratively taking actions, evaluating progress, and deciding next steps. Useful agents must be reliable, adaptive, and accurate.
Looking at and visualizing your raw, primary data is not a waste of time, quite the contrary. In fact, it can be the highest value action and the biggest return on investment that you can do.
To build good products, start by identifying the problem, not the solution. Especially with AI, if you start with a technology, delivering real value to your users and customers will be difficult.
A strong AI strategy is built by answering those three essential questions honestly. What is our core business? Are we chasing real value or just perception? And what specific problem are we actually trying to solve?
Hype happens when messaging becomes divorced from good experiences. Learning from the virtual reality hype cycle can help us avoid future distractions.
Common UX metrics can be grouped into three types: continuous, discrete, and binary. Continuous metrics occur on a smooth spectrum, like time. Discrete metrics have regular intervals between them, such as satisfaction score. Binary metrics have two possible values, like pass or fail.
