How do you measure tech savviness? Abstract constructs such as usability, trustworthiness, intelligence, and desirability can be difficult to measure. The same applies to tech savviness. But to paraphrase Potter Stewart, we know a tech-savvy person when we see one. Tech savviness should matter to UX researchers. When we measure an experience, we don’t want
What is the impact if you sample a lot of your population in a survey? Many statistical calculations—for example, confidence intervals, statistical comparisons (e.g., the two-sample t-test), and their sample size estimates—assume that your sample is a tiny fraction of your population. But what if you have a relatively modest population size (e.g., IT decision-makers
What is tech savviness? While it might be hard to define, you probably know someone whom you consider tech savvy—they might even be your go-to person for solving tech issues. Or maybe you know people who aren’t tech savvy and struggle with all technology. But why should UX researchers care? The concept of tech savviness
Surveys are one of the most popular methods in applied research. While many have argued that surveys are overused, it’s hard to believe that surveys have no place in multi-method UX research. When conducting survey-based research, you’ll often encounter the terms census, poll, and questionnaire used in conjunction with—and often interchangeably with—the term survey. But
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
