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Artificial Intelligence for Marketing: Practical Applications

ISBN: 978-1-119-40636-5
368 pages
August 2017
Artificial Intelligence for Marketing: Practical Applications (1119406366) cover image

Description

A straightforward, non-technical guide to the next major marketing tool

Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way.

Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you:

  • Speak intelligently about Artificial Intelligence and its advantages in marketing
  • Understand how marketers without a Data Science degree can make use of machine learning technology
  • Collaborate with data scientists as a subject matter expert to help develop focused-use applications
  • Help your company gain a competitive advantage by leveraging leading-edge technology in marketing

Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.

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Table of Contents

Foreword by Tom Davenport xiii

Preface xvii

Acknowledgments xix

Chapter 1 Welcome to the Future 1

Welcome to Autonomic Marketing 3

Welcome to Artificial Intelligence for Marketers 3

Whom Is This Book For? 5

The Bright, Bright Future 6

Is AI So Great if It’s So Expensive? 7

What’s All This AI Then? 9

The AI Umbrella 9

The Machine that Learns 10

Are We There Yet? 14

AI-pocalypse 15

Machine Learning’s Biggest Roadblock 23

Machine Learning’s Greatest Asset 24

Are We Really Calculable? 56

Chapter 2 Introduction to Machine Learning 59

Three Reasons Data Scientists Should Read This Chapter 59

Every Reason Marketing Professionals Should Read

This Chapter 60

We Think We’re So Smart 60

Define Your Terms 61

All Models Are Wrong 62

Useful Models 64

Too Much to Think About 66

Machines Are Big Babies 68

Where Machines Shine 69

Strong versus Weak AI 71

The Right Tool for the Right Job 72

Make Up Your Mind 88

One Algorithm to Rule Them All? 89

Accepting Randomness 92

Which Tech Is Best? 94

For the More Statistically Minded 94

What Did We Learn? 101

Chapter 3 Solving the Marketing Problem 103

One-to-One Marketing 105

One-to-Many Advertising 107

The Four Ps 108

What Keeps a Marketing Professional Awake? 109

The Customer Journey 111

We Will Never Really Know 111

How Do I Connect? Let Me Count the Ways 114

Why Do I Connect? Branding 117

Marketing Mix Modeling 119

Econometrics 121

Customer Lifetime Value 121

One-to-One Marketing—The Meme 122

Seat-of-the-Pants Marketing 123

Marketing in a Nutshell 124

What Seems to Be the Problem? 126

Chapter 4 Using AI to Get Their Attention 128

Market Research: Whom Are We After? 128

Marketplace Segmentation 131

Raising Awareness 141

Social Media Engagement 155

In Real Life 158

The B2B World 158

Chapter 5 Using AI to Persuade 165

The In-Store Experience 168

On the Phone 178

The Onsite Experience—Web Analytics 179

Merchandising 186

Closing the Deal 188

Back to the Beginning: Attribution 193

Chapter 6 Using AI for Retention 200

Growing Customer Expectations 200

Retention and Churn 202

Many Unhappy Returns 204

Customer Sentiment 208

Customer Service 209

Predictive Customer Service 216

Chapter 7 The AI Marketing Platform 218

Supplemental AI 218

Marketing Tools from Scratch 221

A Word about Watson 224

Building Your Own 230

Chapter 8 Where Machines Fail 232

A Hammer Is Not a Carpenter 232

Machine Mistakes 235

Human Mistakes 241

The Ethics of AI 247

Solution? 258

What Machines Haven’t Learned Yet 260

Chapter 9 Your Strategic Role in Onboarding AI 262

Getting Started, Looking Forward 264

AI to Leverage Humans 272

Collaboration at Work 274

Your Role as Manager 276

Know Your Place 282

AI for Best Practices 286

Chapter 10 Mentoring the Machine 289

How to Train a Dragon 290

What Problem Are You Trying to Solve? 291

What Makes a Good Hypothesis? 294

The Human Advantage 297

Chapter 11 What Tomorrow May Bring 305

The Path to the Future 307

Machine, Train Thyself 308

Intellectual Capacity as a Service 308

Data as a Competitive Advantage 310

How Far Will Machines Go? 316

Your Bot Is Your Brand 319

My AI Will Call Your AI 321

Computing Tomorrow 325

About the Author 327

Index 329

 

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Author Information

JIM STERNE is founder of the eMetrics Summit and cofounder and Board Chair of the Digital Analytics Association. An internationally known speaker and consultant, he is the author of numerous books, including 101 Things You Should Know About Marketing Optimization Analysis, Social Media Metrics, and The Devil's Data Dictionary.

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