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数据驱动设计

数据驱动设计

1星价 ¥33.1 (3.6折)
2星价¥33.1 定价¥92.0

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  • ISBN:9787564173555
  • 装帧:一般胶版纸
  • 册数:暂无
  • 重量:暂无
  • 开本:23cm
  • 页数:27,337页
  • 出版时间:2017-10-01
  • 条形码:9787564173555 ; 978-7-5641-7355-5

本书特色

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。

内容简介

表面上看,设计技巧和数据科学是两件无关的事情,但是这些原则*终的目的是一致的,就是帮助设计者和产品经理更好地理解客户需求。数据能推动设计,设计能赋予数据更多意义。这本实用的指南能告诉你如何指导数据驱动的A/B测试,并给出具体实例。

目录

ForewordPrefaceChapter 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 Don't Have Data Friends (Yet) Themes You'll See in This Book Summary Questions to Ask YourselfChapter 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 YourselfChapter3 A Framework for Experimentation Introducing Our Framework Three Phases: Definition, Execution, and Analysis, Examples: Data and Design in Action Summary Questions to Ask YourselfChapter4 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 YourselfChapter5 The Execution Phase (How to Put Your Experiments into Action) Designing to Learn Designing the Best Representation of Your Hypothesis Summary Questions to Ask YourselfChapter 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 YourselfChapter 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 YourselfChapter 8 Conclusion Ethical Considerations Last Words Appendix A: Resources Index
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