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Customer Reviews:Average Customer Rating: Outstanding Text Focus of the Book: The text discusses the different types of metrics garnered from usability testing (including performative metrics, issues-based metrics, self-reported data, web navigation and logging data, derived metrics, and behavioral/psychological metrics), and explains how best to analyze and present numerical usability information for stakeholders, with a few tips on how to make a Bo Schembechler blow horn. Excellent practical guide Tullis and Albert have written a very readable and very practical guide to UX metrics that will be be appreciated by readers at any experience level with regard to UX design. Particularly useful is the distinction made between issues-based and performance-based metrics, and the role of statistics and statistical validity in these two types of metrics. The primer on statistical analysis focused exclusively on how it can be applied in UX research is also a highlight for those working in UX design without a background in statistics. Overall, a valuable contribution to the UX literature. I learned some great new metrics As a professional usability researcher working in a large corporation, I need to be able to 'tell the ROI story' convincingly. I learned some great things in this book that made me go Wow! e.g I'm loving the "lostness" metric, as a quantatitive way to measure how easy it is to find things on a site. Finally, a way to measure the user experience you're designing before you ship it! As a professional User Experience Product Designer and PhD student in an HCI field, I am amazed by the lack of information out there with regard to measuring the relative success of a specific user experience. Worse yet, it's nearly impossible to find any well-described, proven methods for measuring a user experience that is still in the process of being designed. Most other sources talk about post-hoc measurement schemes. Best stats book for usability...ever One of the most useful books in my usability library. The statistical analysis discussions (and the rest of the book) are extremely easy to follow. Unlike most books on statistical analysis that I've come across, this book is written with statistical novices in mind. Although the book is primarily about what the title implies, as a bonus there are chapters about how to design a usability study to accommodate data collection and analysis. I recommend this book to anyone who has to analyze usability data. | | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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