Surveys are an essential method for collecting data. But like all research methods, surveys have their limitations. Unless the survey is administered by a facilitator, a respondent has only the survey’s instructions, questions, and response options for guidance. Earlier we wrote about ways to improve the clarity of your questions and certain words to watch
Like in all research methods, many things can go wrong in surveys, from problems with sampling to mistakes in analysis. To draw valid conclusions from your survey, you need accurate responses. But participants may provide inaccurate information. They could forget the answers to questions or just answer questions incorrectly. One common reason respondents answer survey
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
Fifteen minutes could save you 15%. Nationwide is on your side. You’re in good hands with Allstate. Auto insurance commercials are ubiquitous. It’s no wonder, considering the market. In 2020, the population of the United States was 331,000,000, and 230,000,000 Americans were licensed drivers. If you drive, you should have auto insurance. Until recently, most
Are people more likely to select response options that are on the left side of a rating scale? About ten years ago, we provided a brief literature review of the published evidence, which suggested that this so-called left-side bias not only existed but also was detected almost 100 years ago in some of the earliest
The COVID-19 pandemic has led to significant changes in how people have vacationed in 2020. To get away from it all without spending time in crowded places, vacationers have turned to vacation rental websites and have planned longer stays. For example, Airbnb recently reported a year-to-year doubling of long-term (>28 days) rentals and a shift
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
Human: Computer, can you recognize speech? Computer: I think you said, can you wreck a nice beach? Both the quality of synthesized speech and the capability of communicating with a computer using your voice have come a long way since the debut of this technology in the 1970s. One of the most famous synthetic voices
In our earlier article, Jim Lewis and I reviewed the published literature on labeling scales. Despite some recommendations and “best practice” wisdom, we didn’t find that fully labeled scales were measurably superior to partially labeled scales across the 17 published studies that we read. In reviewing the studies in more detail, we found many had
