While task completion and task time are the default choices for measuring task effectiveness and task efficiency, the methods used to capture people’s feelings about an experience certainly seem more varied. But after measuring post-task perceptions for decades, we’ve found that a simple seven-point item does a good job of capturing not only perceptions of
Satisfaction is different than ease of use. But they are both attitudes. We provided the conceptual foundation for what satisfaction is, how it differs from perceived ease of use, and how both can be collected at the overall product level (also called the study level) or at the task level. So, while we know they
“Satisfaction” is used rather broadly in vernacular speech. We can feel satisfied with a meal, a movie, or a moment. Our feeling of satisfaction blends utility (it fed me), affect (I enjoyed it), and expectation (it lived up to or exceeded what I wanted). The dessert, the movie ending, or the moment can all be
The last couple of years have not been easy for those in the UX profession. With an increase in layoffs and AI disruption, uncertainty has grown about job security and even whether to leave the profession entirely. How has this uncertainty affected the current satisfaction that UX professionals feel about their job? What you do
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
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.
In a famous Harvard Business Review article published in 2003, Fred Reichheld introduced the Net Promoter Score (NPS). The NPS uses a single likelihood-to-recommend (LTR) question (“How likely is it that you would recommend our company to a friend or colleague?”) with 11 scale steps from 0 (Not at all likely) to 10 (Extremely likely).
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
Like in all research methods, many things can go wrong in surveys, from problems with sampling to mistakes in analysis. To draw valid conclusions from your survey, you need accurate responses. But participants may provide inaccurate information. They could forget the answers to questions or just answer questions incorrectly. One common reason respondents answer survey
Five-star reviews. Whether you’re rating a product on Amazon, a dining experience on Yelp, or a mobile app in the App or Play Store, you can see that the five-star rating system is quite ubiquitous. Does the familiarity of stars offer a better rating system than traditional numbered scales? We recently reported a comparison between standard
