数据驱动设计
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作者(美)罗谢尔·金(Rochelle King),(美)伊丽莎白·F·丘吉尔(Elizabeth F.Churchill),(美)凯特琳·谭(Caitlin Tan) 著
出版社东南大学出版社
ISBN9787564173555
出版时间2017-10
装帧平装
开本16开
定价92元
货号1201590073
上书时间2024-06-09
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作者简介
Rochelle King任职于Spotify，担任其产品设计与洞察(Product Design and Insights)的优选副总裁。她乐于游走在设计与数据的交汇处，在她的职业生涯中曾多次担任技术公司的领导职位。
Elizabeth F．Churchill是一位人机交互(HCI)专家。她在数家很好的硅谷公司致力于以用户为中心的研究。她当前的工作重点是设计人员以及开发者工具。
Caitlin Tan是Spotify的一位用户研究员(User Researcher)，不久前才毕业于MIT。
目录
Foreword
Preface
Chapter 1 Introducing a Data Mindset
Data as a Trend
Three Ways to Think About Data
What Does This Mean for You as a Designer?
Data Can Help to Align Design with Business
With a Little Help from Your Friends
What If You Dont Have Data Friends （Yet）?
Themes Youll See in This Book
Summary
Questions to Ask Yourself
Chapter 2 The ABCs of Using Data
The Diversity of Data
Why Experiment?
Basics of Experimentation
A/B Testing： Online Experiments
Your Hypothesis and Why It Matters
Running Creative A/B Tests
Summary
Questions to Ask Yourself
Chapter3 A Framework for Experimentation
Introducing Our Framework
Three Phases： Definition， Execution， and Analysis，
Examples： Data and Design in Action
Summary
Questions to Ask Yourself
Chapter4 The Definition Phase （How to Frame Your Experiments）
Getting Started： Defining Your Goal
Identifying the Problem You Are Solving
Building Hypotheses for the Problem at Hand．．．
The Importance of Going Broad
Which Hypotheses to Choose?
Summary
Questions to Ask Yourself
Chapter5 The Execution Phase （How to Put Your Experiments into Action）
Designing to Learn
Designing the Best Representation of Your
Hypothesis
Summary
Questions to Ask Yourself
Chapter 6 The Analysis Phase （Getting Answers From Your Experiments）
Vetting Your Designs Ahead of Launch
Launching Your Design
Evaluating Your Results
What Does the Data Say?
Rolling Out Your Experience， or Not
Case Study： Netflix on PlayStation 3
Summary
Questions to Ask Yourself
Chapter 7 Creating the Right Environment for Data-Aware Design
Principle 1： Shared Company Culture and Values
Principle 2： Hiring and Growing the Right People
Principle 3： Processes to Support and Align
Summary
Questions to Ask Yourself
Chapter 8 Conclusion
Ethical Considerations
Last Words
Appendix A： Resources
Index
内容摘要
从表面上来看，设计实践和数据科学似乎并没有什么明显的联系。但这两门学科的目标其实是一样的，都是为了帮助设计人员和产品经理理解用户，以便于打造出良好的数字化体验。数据能够增强设计，同时设计也可以赋予数据更深层次的意义。这本实用指南展示了如何生成数据驱动的A/B测试，用于帮助执行各种设计决策，无论是细小的调校，还是大规模的UX概念。另外还配合真实案例，告诉你怎样完成产品设计流程中数据驱动设计部分的工作。
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