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UX

by Jeff Sauro, PhD and Jim Lewis, PhD | January 21, 2020

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UX ( 73 )
 Methods ( 62 )
 Usability Testing ( 55 )
 Statistics ( 51 )
 Survey ( 38 )
 NPS ( 34 )
 Benchmarking ( 32 )
 Usability ( 32 )
 Customer Experience ( 31 )
 User Research ( 29 )
 SUS ( 28 )
 Sample Size ( 26 )
 Rating Scale ( 25 )
 Net Promoter Score ( 22 )
 Usability Problems ( 18 )
 Metrics ( 17 )
 Questionnaires ( 16 )
 Measurement ( 16 )
 User Experience ( 14 )
 Satisfaction ( 14 )
 Validity ( 14 )
 Rating Scales ( 14 )
 Surveys ( 13 )
 Usability Metrics ( 13 )
 UMUX-lite ( 12 )
 SUPRQ ( 12 )
 Market Research ( 12 )
 Qualitative ( 11 )
 Reliability ( 11 )
 SUPR-Q ( 11 )
 Navigation ( 10 )
 Task Time ( 8 )
 UX Metrics ( 8 )
 Heuristic Evaluation ( 8 )
 SEQ ( 7 )
 Task Completion ( 7 )
 Questionnaire ( 7 )
 Mobile Usability Testing ( 6 )
 Mobile ( 6 )
 Analytics ( 6 )
 Research ( 6 )
 Unmoderated Research ( 5 )
 Six Sigma ( 5 )
 Usability Problem ( 5 )
 Visualizing Data ( 5 )
 Task Times ( 4 )
 Credibility ( 4 )
 Loyalty ( 4 )
 Confidence ( 4 )
 UX Maturity ( 4 )
 Expert Review ( 4 )
 Confidence Intervals ( 4 )
 Moderation ( 4 )
 Quantitative ( 4 )
 UX Methods ( 4 )
 Usability Lab ( 3 )
 Summative ( 3 )
 Card Sorting ( 3 )
 Lean UX ( 3 )
 Voice Interaction ( 3 )
 sliders ( 3 )
 Customer Segmentation ( 3 )
 Task Metrics ( 3 )
 Key Driver ( 3 )
 ROI ( 3 )
 Desirability ( 3 )
 Data ( 3 )
 TAM ( 3 )
 PURE ( 3 )
 Excel ( 2 )
 Salary Survey ( 2 )
 Findability ( 2 )
 Focus Groups ( 2 )
 Sensitivity ( 2 )
 SUM ( 2 )
 Personas ( 2 )
 Tree Testing ( 2 )
 Tasks ( 2 )
 Branding ( 2 )
 UX Salary Survey ( 2 )
 Errors ( 2 )
 PhD ( 2 )
 Correlation ( 2 )
 Remote Usability Testing ( 2 )
 IA ( 2 )
 A/B Testing ( 2 )
 Star Scale ( 2 )
 Eye-Tracking ( 2 )
 Emoji scale ( 2 )
 slider ( 2 )
 Sample Sizes ( 2 )
 LTR ( 2 )
 Variables ( 2 )
 Marketing ( 2 )
 Prototype ( 2 )
 Cognitive Walkthrough ( 2 )
 Formative ( 2 )
 KLM ( 2 )
 Likert ( 1 )
 consumer software ( 1 )
 Desktop ( 1 )
 Design Thinking ( 1 )
 Latin Squares ( 1 )
 Visual Analog Scale ( 1 )
 b2b software ( 1 )
 User-Centred Design ( 1 )
 Meeting software ( 1 )
 Formative testing ( 1 )
 Margin of Error ( 1 )
 CUE ( 1 )
 RITE ( 1 )
 MUSiC ( 1 )
 Cumulative Graphs ( 1 )
 History of usability ( 1 )
 ISO ( 1 )
 Greco-Latin Squares ( 1 )
 Linear Numeric Scale ( 1 )
 Information Architecture ( 1 )
 Bias ( 1 )
 Contextual Inquiry ( 1 )
 Mean Opinion Scale ( 1 )
 graphic scale ( 1 )
 Probability ( 1 )
 Measure ( 1 )
 coding ( 1 )
 negative scale ( 1 )
 MOS ( 1 )
 Mobile Usability ( 1 )
 Carryover ( 1 )
 Problem Severity ( 1 )
 Within-subjects ( 1 )
 Task Randomization ( 1 )
 Research design ( 1 )
 MOS-R ( 1 )
 Anchoring ( 1 )
 Polarization ( 1 )
 Site Analytics ( 1 )
 AttrakDiff2 ( 1 )
 Effect Size ( 1 )
 Affinity ( 1 )
 Unmoderated ( 1 )
 Z-Score ( 1 )
 User Testing ( 1 )
 Persona ( 1 )
 Software ( 1 )
 Segmentation ( 1 )
 Task Completin ( 1 )
 Design ( 1 )
 Performance ( 1 )
 Sample ( 1 )
 Crowdsourcing ( 1 )
 Random ( 1 )
 Think Aloud ( 1 )
 Five ( 1 )
 Perceptions ( 1 )
 Top Task Analysis ( 1 )
 True Intent ( 1 )
 Visual Appeal ( 1 )
 Certification ( 1 )
 Facilitation ( 1 )
 Microsoft Desirability Toolkit ( 1 )
 Competitive ( 1 )
 Expectations ( 1 )
 PSSUQ ( 1 )
 meCUE2.0 ( 1 )
 UEQ ( 1 )
 Quality ( 1 )
 Hedonic usability ( 1 )
 Trust ( 1 )
 Conjoint Analysis ( 1 )
 Regression Analysis ( 1 )
 Moderating ( 1 )
 Ordinal ( 1 )
 Metric ( 1 )
 protoype ( 1 )
 moderated ( 1 )
 NSAT ( 1 )
 CSUQ ( 1 )
 Delight ( 1 )
 Customer effort ( 1 )
 Test Metrics ( 1 )

Comparing Fully vs. Partially Labeled Five- and Seven-Point Scales

By Jeff Sauro, PhD and Jim Lewis, PhD . January 21, 2020 . Tags: , ,
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 confounding effects when comparing between full labeling and partial labeling—meaning

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The UX of Fitness and Nutrition Websites

By Jeff Sauro, PhD . January 14, 2020 . Tags: ,
Each January millions of people make New Year’s resolutions. One of the most popular is to lose weight and stay in shape. Gyms get packed each January, then around Valentine’s Day the “resolutionary” crowds tend to fade away. It’s not easy to change habits but several websites try to help you build the right fitness habits throughout the year. It can be hard enough to

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The UX of Outdoor Retail Websites

By Jeff Sauro, PhD . October 29, 2019 . Tags: ,
There’s a lot to do outside. Biking, hiking, fishing, hunting, boating, and driving an RV all fall under the umbrella of the outdoor recreation industry. Depending on how broadly it’s defined, it can be anywhere from a $10 billion to $800 billion industry. And all the gear needed for these outdoor activities can be bought in brick-and-mortar and online stores. For now, Amazon has yet

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The UX of Online Job Searching Websites & Apps

By Jeff Sauro, PhD . September 17, 2019 . Tags: ,
Around a quarter of Americans change jobs each year. For most, that job search happens online. Job related websites are a multibillion-dollar business with plenty of competition. They have made finding and applying for jobs more accessible and easier. However, the process isn’t without issues. Job descriptions can be misleading, and the application process can be cumbersome. To better understand the job searching user experience

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Picking the Right Dependent Variables for UX Research

By Jeff Sauro, PhD . July 30, 2019 . Tags: ,
What gets measured gets managed. It’s more than a truism for business executives. It’s also essential for the user experience professional. In business, and UX research in particular, you don’t want to bring focus to the wrong or flawed measure. It can lead to wrong decisions and a misalignment of effort. In an earlier article, I discussed the differences between the most common variables in

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Where Do UX Research Methods Come From?

By Jeff Sauro, PhD . July 23, 2019 . Tags: , , ,
UX professionals use many methods to help understand and improve the user experience. Among the most popular are usability testing, expert reviews, surveys, and card sorting. But where did these methods come from? The field of UX research is relatively new, but its methods are not. And while UX methods may have new names, many of these methods are specialized adaptations of methods with roots

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The UX of Dating Websites & Apps

By Jeff Sauro, PhD . May 21, 2019 . Tags: , ,
Online dating websites are one of the primary ways people find dates and even future spouses. These sites represent the bulk of a 3 billion dollar dating services industry. In fact, around 30% of recent marriages started online, but it’s not like finding a date is as easy as filtering choices on Amazon and having them delivered via drone the next day (not yet at

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Validating a Lostness Measure

By Jeff Sauro, PhD . May 14, 2019 . Tags: , ,
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, frustration, and often the inability to accomplish tasks. But how

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10 Things to Know about the Technology Acceptance Model

By Jeff Sauro, PhD . May 7, 2019 . Tags: ,
A usable product is a better product. But even the most usable product isn’t adequate if it doesn’t do what it needs to. Products, software, websites, and apps need to be both usable and useful for people to “accept” them, both in their personal and professional lives. That’s the idea behind the influential Technology Acceptance Model (TAM). Here are 10 things to know about the TAM.

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Why You Should Measure UX Attitudes

By Jeff Sauro, PhD . April 16, 2019 . Tags: , ,
Watching how people interact with an interface tells you a lot about what works and what needs improvement. And while observing behavior is essential for understanding the user experience, it’s not enough. Just because a product does what it should, is priced right, and is reliable, doesn’t mean it provides a good user experience. Users can think the experience is too complicated or difficult. For

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