In math class, we spend a lot of time learning fractions because they are so important in everyday life (e.g., budgeting, purchasing at the grocery store). Fractions are also used extensively in UX research (e.g., the fundamental completion rate is a fraction), typically expressed as percentages or proportions. Unfortunately, fractions are also hard to learn,
How hard is it to figure out the total cost of a mobile phone service plan? Have you had trouble finding the customer support number for your cable provider? How do you quantify these experiences? What words would you use to describe them? While we have ways of measuring perceived ease using numeric scales, rating
UX research is geared primarily toward understanding how to improve the experience of products, websites, and software. The intent is not to assess people but to use people to assess product experiences. But people’s ability to solve technical problems—what we often loosely refer to as tech savviness—can confound our research findings. That is, including only
How do we know what a good measure is? We have written extensively about the benefits of using standardized measures such as questionnaires to measure the user experience. We have also written about the processes and methods used to build a standardized questionnaire. But where do these methods come from? Are they the best ones?
Think Aloud (TA) usability testing is a popular UX research method. Having participants speak their thoughts as they attempt tasks helps researchers understand possible sources of misunderstandings so they can identify and potentially fix problems. The signature method of having users think aloud can trace its roots back to psychoanalysis and work from Freud (psychoanalysis),
Changing the number of response options in the survey might confuse participants. Over the years, we’ve heard variations on this concern articulated a number of different ways by clients and fellow researchers. Surveys and unmoderated UX studies commonly contain a mix of five-, seven-, and eleven-point scales. That leads some to express concern. Why are
Over the past few months, we’ve conducted several studies with different versions of the seven-point Single Ease Question (SEQ®), a popular task-level metric for perceived ease-of-use. As we’ve seen with other research on rating scales, response means tend to be rather stable despite often salient changes to formatting. In our earlier SEQ research, we found
We use the seven-point Single Ease Question (SEQ®) frequently in our practice, as do many other UX researchers. One reason for its popularity is the body of research that started in the mid-2000s with the comparison of the SEQ to other similar short measures of perceived ease-of-use, the generation of a normative SEQ database, and
A social media platform, a GPS heads-up display, a video streaming platform: all are examples of viable products … that failed. The failure came despite often substantial financial funding and putatively useful features. Their failures were blamed on poor product-market fit. Predicting a prospective product’s success in the market isn’t easy. But there’s a strong
Statistics doesn’t have a Magna Carta, constitution, or bill of rights to enumerate laws, guiding principles, or limits of power. There have been attempts to articulate credos for statistical practice. Two of the most enduring ones are based on the work by Robert P. Abelson, a former statistical professor at Yale. If Abelson wasn’t the
