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Artificial Intelligence for Marketing: Practical Applications

ISBN: 978-1-119-40633-4
368 pages
August 2017
Artificial Intelligence for Marketing: Practical Applications (1119406331) 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 Davenport

Preface

Acknowledgments

Chapter 1: Welcome to the Future

Welcome to Autonomic Marketing

Welcome to Artificial Intelligence for Marketers

Whom Is This Book For?

The Bright, Bright Future

Is AI So Great If It’s So Expensive?

What’s All This AI Then?

The AI Umbrella

The Machine that Learns

Are We There Yet?

AI-Pocalypse

Machine Learning’s Biggest Roadblock

Machine Learning’s Greatest Asset

Are We Really Calculable?

Chapter 2: Introduction to Machine Learning

Three Reasons Data Scientists Should Read This Chapter

Every Reason Marketing Professionals Should Read This Chapter

We Think We’re So Smart

Define Your Terms

All Models Are Wrong

Useful Models

Too Much to Think About

Machines Are Big Babies

Where Machines Shine

Strong versus Weak AI

The Right Tool for the Right Job

Make Up Your Mind

One Algorithm to Rule Them All?

Accepting Randomness

Which Tech Is Best?

For the More Statistically Minded

What Did We Learn?

Chapter 3: Solving the Marketing Problem

One-to-One Marketing

One-to-Many Advertising

The Four Ps

What Keeps a Marketing Professional Awake?

The Customer Journey

We Will Never Really Know

How Do I Connect? Let Me Count the Ways

Why Do I Connect? Branding

Market Mix Modeling (MMM)

Econometrics

Customer Lifetime Value

One-to-One Marketing—The MemeSeat-of the-Pants Marketing

Marketing in a Nutshell

What Seems to Be the Problem?

Chapter 4: Using AI to Get Their Attention

Market Research: Whom Are We After?

Marketplace Segmentation

Raising Awareness

Social Media Engagement

In Real Life

The B2B World

Chapter 5: Using AI to Persuade

The In-store Experience

The On-site Experience—Web Analytics

Merchandising

Closing the Deal

Back to the Beginning: Attribution

Chapter 6: Using AI for Retention

Growing Customer Expectations

Retention and Churn

Many Unhappy Returns

Voice of the Customer

Customer Service

Predictive Customer Service

Chapter 7: The AI Marketing Platform

Supplemental AI

Marketing Tools from Scratch

A Word about Watson

Building Your Own

Chapter 8: Where Machines Fail

A Hammer Is Not a Carpenter

Machine Mistakes

Human Mistakes

The Ethics of AI

Solution?

What Machines Haven’t Learned Yet

Chapter 9: Your Strategic Role Onboarding AI

Getting Started, Looking Forward

AI to Leverage Humans

Collaboration at Work

Your Role as Manager

Know Your Place

AI for Best Practices

Chapter 10: Mentoring the Machine

How to Train a Dragon

What Problem Are You Trying to Solve?

What Makes a Good Hypothesis?

The Human Advantage

Chapter 11: What Tomorrow May Bring

The Path to the Future

Machine, Train Thyself

Intellectual Capacity as a Service

Data as a Competitive Advantage

How Far Will Machines Go?

Your Bot Is Your Brand

My AI Will Call Your AI

Computing Tomorrow

About the Author

Index

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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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