A Guide to Study-Based UX Metrics

For quantifying the user experience of a product, app, or experience, we recommend using a mix of study-level and task-based UX metrics. In an earlier article, we provided a comprehensive guide to task-based metrics. Tasks can be included as part of usability tests or UX benchmark studies. They involve having a representative set of users

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How to Report Product Experience Data

How often do you use your phone? How about a streaming service you subscribe to, like Hulu or Netflix? What about software, like Microsoft Excel? In an earlier article, we discussed the importance of measuring prior experience. Prior experience is a strong predictor of UX metrics. People who are familiar with a product and use

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Sample Sizes for Comparing SUS to a Benchmark

The System Usability Scale (SUS) has been used in industrial user experience research since the mid-1980s. Despite its age, the SUS is still a popular measure, widely used in benchmark tests of software products to measure perceived usability. One reason for its popularity is the extent to which its measurement properties have been comprehensively studied

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Why Collect Task- and Study-Level Metrics?

In Quantifying the User Experience, we recommend using a mix of task-level and study-level metrics, especially in benchmarking studies. But what, exactly, are task-level and study-level metrics, how do they differ, and why should you collect them both? In this article, we’ll explore this common practice of collecting both types of metrics to understand the

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49 UX Metrics, Methods, and Measurement Articles from 2021

Happy New Year from all of us at MeasuringU®! In 2021 we posted 49 articles and welcomed several new clients to our UX testing platform MUIQ®, where we continue to add new features to reduce the friction in developing studies. We hosted our eighth UX Measurement Bootcamp, again as a virtual event. Going virtual still

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Three Ways to Measure a User’s Prior Experience

Individual differences in behavior and attitude often overshadow the differences in designs. There are many ways to characterize how people differ. But one characteristic that drives both attitudinal and behavioral UX metrics is prior experience. Beyond the more superficial aspects of demographic variables such as age, gender, income, and geography, a person’s experience with an

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Why Do People Hate the Net Promoter Score?

The Net Promoter Score is ubiquitous, with many large organizations using it as a key metric. But despite its widespread adoption, there are vocal critics. It’s been called snake oil, deceptive, fake science, and harmful. In our webinar series and on our website, we’ve addressed several aspects of the NPS, including the enmity toward it.

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How to Compare a Net Promoter Score with a Benchmark

We recently described how to compare two Net Promoter Scores (NPS) statistically using a new method based on adjusted-Wald proportions. In addition to comparing two NPS, researchers sometimes need to compare one NPS with a benchmark. For example, suppose you have data that the average NPS in your industry is 17.5%, and you want to

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“Does What I Need It to Do”: Assessing an Alternate Usefulness Item

The UMUX-Lite is a two-item standardized questionnaire that, since its publication in 2013, has been adopted more and more by researchers who need a concise UX metric. Figure 1 shows the standard version with its Perceived Ease-of-Use (“{Product} is easy to use”) and Perceived Usefulness (“{Product}’s capabilities meet my requirements”) items.   Figure 1: Standard

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Confidence Intervals for Net Promoter Scores

The Net Promoter Score (NPS) is a widely used metric, but it can be tricky to work with statistically. One of the first statistical steps we recommend that researchers take is to add confidence intervals around their metrics. Confidence intervals provide a good visualization of how precise estimates from samples are. They are particularly helpful

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