Designing with Data: Improving the User Experience with A/B Testing
On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data.

This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow.

  • Understand the relationship between data, business, and design
  • Get a firm grounding in data, data types, and components of A/B testing
  • Use an experimentation framework to define opportunities, formulate hypotheses, and test different options
  • Create hypotheses that connect to key metrics and business goals
  • Design proposed solutions for hypotheses that are most promising
  • Interpret the results of an A/B test and determine your next move
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Designing with Data: Improving the User Experience with A/B Testing
On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data.

This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow.

  • Understand the relationship between data, business, and design
  • Get a firm grounding in data, data types, and components of A/B testing
  • Use an experimentation framework to define opportunities, formulate hypotheses, and test different options
  • Create hypotheses that connect to key metrics and business goals
  • Design proposed solutions for hypotheses that are most promising
  • Interpret the results of an A/B test and determine your next move
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Designing with Data: Improving the User Experience with A/B Testing

Designing with Data: Improving the User Experience with A/B Testing

Designing with Data: Improving the User Experience with A/B Testing
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Designing with Data: Improving the User Experience with A/B Testing

Designing with Data: Improving the User Experience with A/B Testing

Overview

On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data.

This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow.

  • Understand the relationship between data, business, and design
  • Get a firm grounding in data, data types, and components of A/B testing
  • Use an experimentation framework to define opportunities, formulate hypotheses, and test different options
  • Create hypotheses that connect to key metrics and business goals
  • Design proposed solutions for hypotheses that are most promising
  • Interpret the results of an A/B test and determine your next move

Product Details

ISBN-13: 9781449334833
Publisher: O'Reilly Media, Incorporated
Publication date: 04/20/2017
Pages: 367
Product dimensions: 5.90(w) x 8.90(h) x 0.90(d)

About the Author

Rochelle King is Global VP of Design and User Experience at Spotify where she is responsible for the teams that oversee user research and craft the product experience at Spotify. Prior to Spotify, Rochelle was VP of User Experience and Product Services at Netflix. where she managed the Design, Enhanced Content, Content Marketing, and Localization teams at Netflix. Collectively, these groups were responsible for the UI, layout, meta-data (editorial and visual assets), and presentation of the Netflix service internationally across all platforms. Rochelle has over 14 years of experience working on consumer-facing products. You can find her on Twitter @rochelleking.

Dr. Elizabeth Churchill is a Director of User Experience at Google. Her work focuses on the connected ecosystems of the Social Web and Internet of Things. For two decades, Elizabeth has been a research leader at well-known corporate R&D organizations including Fuji Xerox's research lab in Silicon Valley (FXPAL), the Palo Alto Research Center (PARC), eBay Research Labs in San Jose, and Yahoo! in Santa Clara, California.



Elizabeth has contributed groundbreaking research in a number of areas, publishing over 100 peer reviewed articles, coediting 5 books in HCI-related fields, contributing as a regular columnist for the Association of Computing Machinery's (ACM) Interactions magazine since 2008, and publishing an academic textbook, Foundations for Designing User-Centered Systems. She has also launched successful products, and has more than 50 patents granted or pending.

Caitlin Tan is a User Researcher at Spotify, and a recent graduate from MIT.

Table of Contents

Foreword ix

Preface xi

Chapter 1 Introducing a Data Mindset 1

Data as a Trend 1

Three Ways to Think About Data 3

What Does This Mean for You as a Designer? 9

Data Can Help to Align Design with Business 10

With a Little Help from Your Friends 15

What If You Don't Have Data Friends (Yet)? 20

Themes You'll See in This Book 21

Summary 21

Questions to Ask Yourself 23

Chapter 2 The ABCs of Using Data 25

The Diversity of Data 26

Why Experiment? 32

Basics of Experimentation 38

A/B Testing: Online Experiments 45

Your Hypothesis and Why It Matters 63

Running Creative A/B Tests 68

Summary 78

Questions to Ask Yourself 79

Chapter 3 A Framework for Experimentation 81

Introducing Our Framework 82

Three Phases: Definition, Execution, and Analysis 89

Examples: Data and Design in Action 92

Summary 95

Questions to Ask Yourself 96

Chapter 4 The Definition Phase (How to Frame Your Experiments) 97

Getting Started: Defining Your Goal 99

Identifying the Problem You Are Solving 114

Building Hypotheses for the Problem at Hand 120

The Importance of Going Broad 130

Which Hypotheses to Choose? 143

Summary 153

Questions to Ask Yourself 154

Chapter 5 The Execution Phase (How to Put Your Experiments into Action) 155

Designing to Learn 157

Designing the Best Representation of Your Hypothesis 163

Summary 203

Questions to Ask Yourself 204

Chapter 6 The Analysis Phase (Getting Answers From Your Experiments) 207

Vetting Your Designs Ahead of Launch 208

Launching Your Design 211

Evaluating Your Results 224

What Does the Data Say? 226

Rolling Out Your Experience, or Not 243

Case Study: Netflix on PlayStation 3 254

Summary 262

Questions to Ask Yourself 264

Chapter 7 Creating the Right Environment for Data-Aware Design 267

Principle 1 Shared Company Culture and Values 268

Principle 2 Hiring and Growing the Right People 280

Principle 3 Processes to Support and Align 287

Summary 301

Questions to Ask Yourself 303

Chapter 8 Conclusion 305

Ethical Considerations 308

Last Words 317

Appendix A Resources 321

Index 329

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