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In an earlier article, we examined the folk wisdom that three-point scales were superior to those with more, such as five, seven, ten, or eleven response options. Across twelve published studies we found little to suggest that three-point scales were better than scales with more points and, in fact, found evidence to show that they performed much worse than scales with more points. Almost all

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Five-point scales are the best. No, seven points. Never use a ten-point scale. Eleven points “pretend noise is science.” You never need more than three points. Few things seem to elicit more opinions (and misinformation) in measurement than the “right” number of scale points to use in a rating scale response option. For example, here is a discussion on Twitter by Erika Hall making the

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It seems like each year introduces a new measure or questionnaire. Like a late-night infomercial, some are even touted as the next BIG thing, like the NPS was. New questionnaires and measures are a natural part of the evolution of measurement (especially measuring difficult things such as human attitudes). It’s a good thing. I’ll often help peer review new questionnaires published in journals and conference

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It seems like there are endless ways to ask questions of participants in surveys. Variety in question types can be both a blessing and a curse. Having many ways to ask questions provides better options to the researcher to assess the opinion of the respondent. But the wrong type of question can fail to capture what’s intended, confuse respondents, or even lead to incorrect decisions.

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What does 4.1 on a 5-point scale mean? Or 5.6 on a 7-point scale? Interpreting rating scale data can be difficult in the absence of an external benchmark or historical norms. A popular technique used often by marketers to interpret rating scale data is the so-called “top box” and “top-two box” scoring approach. For example, on a 5-point scale, such as the one shown in Figure

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Know your data. When measuring the customer experience, one of the first things you need to understand is how to identify and categorize the data you come across. It's one of the first things covered in our UX Boot Camp and it's something I cover in Chapter 2 of Customer Analytics for Dummies. Early consideration of your data types enables you to do the following:

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The Single Ease Question (SEQ) is a 7-point rating scale to assess how difficult users find a task. It's administered immediately after a user attempts a task in a usability test. After users attempt a task, ask them this simple question: Overall, how difficult or easy was the task to complete? Use the seven point rating scale format below. Labels and values: We typically label

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What makes a successful website?There are some obvious metrics like revenue, traffic and repeat visitors. But these are outcome measures. They don't tell you why revenue or traffic is higher or lower.  Key drivers of these outcomes are how the users perceive and interact with your website. Selling a product that has demand or information that is valuable is of course essential. But it's rare

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It's fine to compute means and statistically analyze ordinal data from rating scales. But just because one rating is twice as high as another does not mean users are really twice as satisfied. When we use rating scales in surveys, we're translating intangible fuzzy attitudes about a topic into specific quantities. Overall, how satisfied are you with your cell-phone service? Very Unsatisfied 1 2 3

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Few things tend to generate more heated debate than the format of response options used in surveys. Right in the middle of that debate is whether the number of options should be odd or even. Odd numbered response scales include a neutral response whereas even ones do not. Research generally shows that including a neutral response will affect the distribution of responses and sometimes lead

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