A common logistical consideration when planning a task-based usability study is how much time you should plan for a task. Many usability studies (especially benchmark studies) suffer from trying to do too many things. That includes asking participants to attempt too many tasks. It’s understandable why tasks get packed in—even low-cost usability testing takes time
If different researchers conduct a study, will they identify different problems? While it was originally controversial, the evaluator effect is now well-established in the field of UX research. The evaluator effect is the finding that, in general, different teams or individuals conducting a usability study will identify and report different problems (Hertzum & Jacobsen, 2003).
If users can’t complete a task, not much else matters. Consequently, task completion is one of the fundamental UX measures and one of the most commonly collected metrics, even in small-sample formative studies and studies of low-fidelity prototypes. Task completion is usually easy to collect, and it’s easy to understand and communicate. It’s typically coded as
One of these things is not like the other. That’s the theme of a segment on the long-running US TV show Sesame Street. As children, we learn to identify similarities and differences. And after seeing a group of things that look similar, we tend to remember the differences. Why? Well, one theory describes something called
Unmoderated testing platforms allow for quick data collection from large sample sizes. This has enabled researchers to answer questions that were previously difficult or cost prohibitive to answer with traditional lab-based testing. But is the data collected in unmoderated studies, both behavioral and attitudinal, comparable to what you get from a more traditional lab setup? Comparing
Small differences in design changes can have large consequences on website purchases. But detecting these small differences (e.g. 2%–10% changes) through behaviors and attitudes has generally not been feasible from traditional lab-based testing due to the time and costs of recruiting and facilitator costs/time. With unmoderated testing, organizations can now collect data from hundreds to
To understand problems on a website, nothing quite beats watching users. The process provides a wealth of information both about what users can or can’t do and what might be causing problems in an interface. The major drawback to watching users live or recordings of sessions is that it takes a lot of focused time.
