Description
Improving the User Experience through Practical Data Analytics
Gain Meaningful Insight and Increase Your Bottom Line
Authors: Fritz Mike, Berger Paul D.
Language: English
Subjects for Improving the User Experience through Practical Data...:
Keywords
Analysis of variance (ANOVA); ANOVA; Bell-curve; Binary logistic regression; Chi-square test of independence; Cochran Q test; Confidence intervals; Correlation analysis; Excel; Fisher's exact test; Hypothesis testing; Independent samples; Interaction effects; Least-squares line; Logistic regression analysis; Maximum likelihood estimation; McNemar test; Multiple comparison testing; Multiple regression analysis; Natural log of the odds; Newman-Keuls test; Normal distribution; Odds; One-factor ANOVA; Paired data; Paired samples; Probability distribution of the mean; Regression analysis; Repeated measures designs; SPSS; Stepwise regression analysis; Student-Newman-Keuls test; T-test; Testing for equality of means; Testing nominal/categorical data; The adjusted Wald method; The binomial process/distribution; Two-factor designs; Two-sample testing; Within-subject designs; Within-subject experiments
396 p. · 19x23.3 cm · Paperback
Description
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/li>Biography
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Improving the User Experience through Practical Data Analytics shows you how to make UX design decisions based on data?not hunches. Authors Fritz and Berger help the UX professional recognize the enormous potential of user data that is collected as a natural by-product of routine UX research methods, including moderated usability tests, unmoderated usability tests, surveys, and contextual inquiries. Then, step-by-step, they explain how to utilize both descriptive and predictive statistical techniques to gain meaningful insight with that data. By mastering the use of these techniques, you?ll delight your users, increase your bottom line and gain a powerful competitive advantage for your company?and yourself.
Key features include:
- Practical advise on choosing the right data analysis technique for each project.
- A step-by-step methodology for applying each technique, including examples and scenarios drawn from the UX field.
- Detailed screen shots and instructions for performing the techniques using Excel (both for PC and Mac) and SPSS.
- Clear and concise guidance on interpreting the data output.
- Exercises to practice the techniques
Chapter 1: The Changing World of UX
Chapter 2: Data to the Rescue
Chapter 3: Stats! It’s Easier Than You Think
Chapter 4: Unmoderated Remote Usability Tests
Chapter 5: Surveys
Chapter 6: Good Old Usability Tests
Chapter 7: Persona Development
Chapter 8: Field Studies
Chapter 9: Live Website Data
Chapter 10: Card Sorting Data
Chapter 11: Case Studies – Tips from the Real World
Paul D. Berger is a Visiting Scholar and Professor of Marketing at Bentley University, where he is also the director of the Master of Science in Marketing Analytics (MSMA) program. He earned his S.B., S.M., and Ph.D. degrees from the Massachusetts Institute of Technology, Sloan School of Management. He has published several books, including Internet Marketing and Experimental Design, and won the Metcalf Award, a university-wide award for teaching excellence, and the John R. Russell award for excellence in executive teaching.
- Practical guidance on choosing the right data analysis technique for each project.
- Real-world examples to build a theoretical and practical understanding of key concepts from consumer and financial verticals.
- A step-by-step methodology for applying each predictive technique, including detailed examples.
- A detailed guide to interpreting the data output and examples of how to effectively present the findings in a report.
- Exercises to learn the techniques
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