How much did you spend last month on clothing? What grocery stores have you visited in the last three months? How helpful are your Netflix recommendations? Surveys and other research methods (such as in-depth interviewing) often rely on participants recalling prior events or behaviors. For example, these could be about purchasing a product or service
In architecture, form follows function. In survey design, question format follows content. Earlier we described four classes of survey questions. These four classes are about the form, or format, of the question (e.g., open- vs. closed-ended). But before you can decide effectively on the format, you need to choose the content of the question and
When we conduct a survey, we want the truth, even if we can’t handle it. But standing in the way of our dreams of efficiently collected data revealing the unvarnished truth about customers, prospects, and users are the four horsemen of survey errors. Even a well-thought-out survey will have to deal with the inevitable challenge
Post-mortems and retrospective accounts are valuable for understanding what went well and what went poorly. This applies not only to investigations of critical events, such as crimes and plane accidents, but also to experiences with products and services. But the usefulness of people’s recollections of events and experiences rests on the accuracy of their memories.
In UX research, both studies and surveys contain a lot of questions. Getting those questions right can go a long way in improving the clarity and quality of the findings. For example, we’ve recently written about how to make survey questions clearer. And while there are many stories of how the change of a single
The first questionnaires appeared in the mid–18th century (e.g., the “Milles” questionnaire). Scientific surveys have been around for almost a hundred years. Consequently, there are many sources of advice on how to make surveys better. The heart of each survey is the questions asked of respondents. Writing good survey questions involves many of the principles
There is plenty of debate about the best way to quantify attitudes and experiences with rating scales. And among those debates, perhaps the most popular question is the “right” number of response options to use for rating scales. For example, is an eleven-point scale too difficult for people to understand? Is a three-point scale insufficient
UX research and UX measurement can be seen as an extension of experimental design. At the heart of experimental design lie variables. Earlier we wrote about different kinds of variables. In short, dependent variables are what you get (outcomes), independent variables are what you set, and extraneous variables are what you can’t forget (to account
To have a reliable and valid response scale, people need to understand what they’re responding to. A poorly worded question, an unclear response item, or an inadequate response scale can create additional error in measurement. Worse yet, the error may be systematic rather than random, so it would result in unmodeled bias rather than just
In an earlier article, we reviewed five competing models of delight. The models differed in their details, but most shared the general idea that delight is composed of an unexpected positive experience. Or, for the most part, delight is a pleasant surprise. However, there is disagreement on whether you actually need surprise to be delighted.