Do Too Many Response Options Confuse People?

Advice on rating scale construction is ubiquitous on the internet and in the halls of organizations worldwide. The problem is that much of the advice is based not on solid data but rather on conventional wisdom and what’s merely thought to work. Even published papers and books on survey design can present a perspective that

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Rating Scales: Myth vs. Evidence

There’s a lot of conventional wisdom floating around the Internet about rating scales. What you should and shouldn’t do. Best practices for points, labels, and formats. It can be hard to differentiate between science-backed conclusions and just practitioner preferences. In this article, we’ll answer some of the more common questions that come up about rating

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Is Usability Testing Effective?

Questioning the effectiveness of usability testing may sound like a relic from the past. In the early years of industrial usability engineering, there was a constant need to justify the activity of (and your job in) usability testing. The book Cost-Justifying Usability (Bias & Mayhew, 2005) speaks to this. Usability testing has since gained significant

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10 Things to Know about the Microsoft Desirability Toolkit

Who, as a person, doesn’t want to be desirable? And if you’re in the business of developing products or services, who doesn’t want those to be desirable? There is a deep satisfaction beyond the monetary rewards of providing something that people want (and of course, the money’s nice, too). While we’ve found wide interest in

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What Is a Strong Correlation?

Smoking causes cancer. Warnings on cigarette labels and from health organizations all make the clear statement that smoking causes cancer. But how do we know? Smoking precedes cancer (mostly lung cancer). People who smoke cigarettes tend to get lung and other cancers more than those who don’t smoke. We say that smoking is correlated with cancer.

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Do Attitudes Predict Behavior?

Should you ask what people think? Are thoughts and feelings reliable indicators of future behavior? Asking about people’s attitudes—especially about their intentions (likelihood to use, recommend, or purchase)—gets a bad rap in UX research. There’s a sort of folk wisdom in User Experience research: People are poor predictors of their future behavior. And this distrust

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The Importance of Replicating Research Findings

You’ve probably heard of the infamous Stanford Prison Experiment by Philip Zimbardo (especially if you took an intro psych class). The shocking results had similar implications to the notorious Milgram experiment and suggested our roles may be a major cause for past atrocities and injustices. You might have also heard about research from Cornell University that found,

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Do Promoters Actually Recommend More? A Longitudinal Analysis

The Net Promoter Score introduced a new language of loyalty. At center stage are the promoters and detractors. These designations are given to respondents who answer the How Likely Are You to Recommend (LTR) question as shown below.   But what is the justification for the designations? Were they just arbitrarily created? Do they just

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Validating a Lostness Measure

No one likes getting lost. In real life or digitally. One can get lost searching for a product to purchase, finding medical information, or clicking through a mobile app to post a social media status. Each link, button, and menu leads to decisions. And each decision can result in a mistake, leading to wasted time,

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Linking UX Attitudes to Future Website Purchases

Users’ attitudes about an experience affect their future behavior. People who think a website is less usable or less attractive will probably visit less, purchase less, and recommend the website less. Understanding users’ attitudes now (easier to measure) can help predict users’ behavior in the future (harder to measure). At least that’s the idea behind using

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