Is not recommending the same as discouraging or recommending others to not use or purchase from a brand? While a lack of recommending seems like it would correlate with NOT recommending, we suspect there may be a difference but are unsure how much. In our previous article, we looked to the published literature and found
One box, two box, red box, blue box … Box scoring isn’t just something they do in baseball. Response options for rating scale data are often referred to as boxes because, historically, paper-administered surveys displayed rating scales as a series of boxes to check, like the one in Figure 1. Figure 1: Illustration of “boxes”
Response scales are a basic type of interface. They should reflect the attitude of the respondent as precisely as possible while requiring as little effort as possible to answer. When collecting data from participants, some wished they could have picked a value between two numbers, for example, 5.5 or 6.5, which can be done with
Few things seem to elicit more opinions, exaggerations, and accusations than rating scale response options. From the “right” number of points, the use (or not) of labels, and the presentation order (to name a few), it seems we all have thoughts on what to do (or not to do) regarding conventions and “rules” when selecting
Like with writing an article or book, it can be a challenge to sit down and write survey items. Few professionals have taken a formal course in survey development. Instead, most rely on their experiences or best practices. To help with the process, we wrote Surveying the User Experience. In this article, we take you
The System Usability Scale (SUS) is one of the oldest standardized UX questionnaires. John Brooke is now retired; should the questionnaire he developed almost 40 years ago accompany him on the beach with a piña colada? After all, the SUS was developed when there were green-screen computer monitors. How can it possibly apply to mobile
In 1916, a leading periodical called The Literary Digest polled its large subscriber base of hundreds of thousands of readers and successfully predicted the winner of that year’s presidential election. The magazine repeated the poll in 1920, 1924, 1928, and 1932, correctly predicting the winner each time—five successful election predictions in a row. In 1936,
In a typical week, we are asked to complete surveys on everything: our most recent restaurant experience, our interaction with an airline’s customer service department, and our recollection of our last online purchase, to name just a few. Surveys are ubiquitous. Not surprisingly, many people hold strong opinions about their proper usage in applied research
Some participants in usability studies complete a task effortlessly, while others struggle with the same task. In retrospective UX surveys, some respondents report having an easy time using a website and strongly recommend it to others, but others report having a much poorer website experience. Why? What explains the discrepancy between experiences, especially when the
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
