Improving the User Experience through Practical Data Analytics (e-bog) af Berger, Paul D.
Berger, Paul D. (forfatter)

Improving the User Experience through Practical Data Analytics e-bog

329,95 DKK (inkl. moms 412,44 DKK)
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 inqui...
E-bog 329,95 DKK
Forfattere Berger, Paul D. (forfatter)
Udgivet 3 marts 2015
Længde 396 sider
Genrer Management decision making
Sprog English
Format epub
Beskyttelse LCP
ISBN 9780128006788
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 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