Improving the User Experience Through Practical Data Analytics - Info and Reading Options
Gain Meaningful Insight and Increase Your Bottom Line
By Mike Fritz and Paul D. Berger
"Improving the User Experience Through Practical Data Analytics" was published by Elsevier Science & Technology Books in 2015 - Waltham, MA, it has 396 pages and the language of the book is English.
“Improving the User Experience Through Practical Data Analytics” Metadata:
- Title: ➤ Improving the User Experience Through Practical Data Analytics
- Authors: Mike FritzPaul D. Berger
- Language: English
- Number of Pages: 396
- Publisher: ➤ Elsevier Science & Technology Books
- Publish Date: 2015
- Publish Location: Waltham, MA
“Improving the User Experience Through Practical Data Analytics” Subjects and Themes:
- Subjects: ➤ Data mining - User interfaces - Human-computer interaction - Storage & retrieval - General - Professional, career & trade -> computer science -> user interfaces - Professional, career & trade -> computer science -> special topics - Professional, career & trade -> computer science -> system administration
Edition Identifiers:
- The Open Library ID: OL33433868M - OL21099840W
- ISBN-13: 9780128006788
- All ISBNs: 9780128006788
AI-generated Review of “Improving the User Experience Through Practical Data Analytics”:
"Improving the User Experience Through Practical Data Analytics" Description:
Open Data:
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
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