Quantitative User Experience Research - Chapman, Chris;Rodden, Kerry
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This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience.
Organizations today have more data about user needs and…mehr

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Produktbeschreibung
This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience.

Organizations today have more data about user needs and behaviors than ever before. With this large-scale data, Quant UX researchers work to understand usage patterns, measure the impact of design changes, and inform strategic decisions. In the Quant UX role, interdisciplinary researchers apply analytical skills to uncover user needs, inform engineering and design, answer strategic business questions, and optimize software and hardware products for human interaction. This book provides guidance around customer satisfaction surveys, understanding user behavior from log analysis, and the statistical methods that are commonly used to assess user outcomes.

What You Will LearnDiscover the role of Quantitative User Experience (Quant UX) researchUnderstand how Quant UX research differs from other disciplines such as data sciencePlan common research projects and know how to achieve successPosition Quant UX activities in product development, engineering, and UX organizationsApply the HEART framework to measure user experience outcomesEvaluate your skills and potential to be hired as a Quant UX researcherKnow what to expect during job interviewsFind examples of common Quant UX projects with shared R code and data sets
Who This Book Is For
Practitioners and managers who seek a comprehensive guide to the new field of Quantitative User Experience Research. Readers will understand the Quant UX role, build research skills, find examples of hands-on code and analyses, learn about UX organizations and stakeholders, and receive advice on job interviews and career paths. Data scientists, social scientists, and other researchers will learn how their skills transfer to Quant UX, where they can help teams build better, more successful products.
Autorenporträt
Jason Schwarz PhD is a Quantitative Researcher at Google and a former systems neurobiologist. His areas of research include perception, attention, motivation, behavioral pattern formation, and data visualization which he studies at scale at Google. Prior to joining Google, he was a data scientist at a startup where he ran analytics and developed and deployed production machine learning models on a Python stack. Chris Chapman PhD is a Quantitative Researcher at Google, and an author of Chapman & Feit, R for Marketing Research and Analytics (Springer, 2015). In the broader industry, he has served as President of the American Marketing Association's Practitioner Council, chaired the AMA Advanced Research Techniques Forum in 2012 and 2017, and is a member of several conference and industry committees. Chris regularly presents research innovations and teaches workshops on R, conjoint analysis, strategic modeling, and other analytics topics. EleaMcDonnell Feit is an Assistant Professor of Marketing at Drexel University and a Senior Fellow of Marketing at The Wharton School. She enjoys making quantitative methods accessible to a broad audience and teaches workshops and courses on advertising measurement, marketing experiments, marketing analytics in R, discrete choice modeling and hierarchical Bayes methods. She is an author of Chapman & Feit, R for Marketing Research and Analytics (Springer, 2015).