Artificial intelligence for marketing : practical applications / Jim Sterne.

Format:

Book

Author/Creator:

Sterne, Jim, author.

Series:

THEi Wiley ebooks.

Wiley & SAS business series

THEi Wiley ebooks

Language:

English

Subjects (All):

Artificial intelligence--Marketing applications.

Artificial intelligence.

Physical Description:

1 online resource (345 pages)

Edition:

1st edition

Place of Publication:

Wiley 2017

System Details:

text file

Summary:

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.

Contents:

Cover

Title Page

Copyright

Contents

Foreword

Preface

Acknowledgments

Chapter 1: Welcome to the Future

Welcome to Autonomic Marketing

Welcome to Artificial Intelligence for Marketers

Detect

Decide

Develop

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

Guess the Animal

The Machine that Programs Itself

Are We There Yet?

AI-pocalypse

The AI that Ate the Earth

Intentional Consequences Problem

Unintended Consequences

Will a Robot Take Your Job?

Machine Learning's Biggest Roadblock

Machine Learning's Greatest Asset

How We Used to Dive into Data

Variety of Data Is the Spice of Life

Open Data

Data for Sale

But Wait-There's More

A Collaboration of Datasets

A Customer Data Taxonomy

Are We Really Calculable?

Notes

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

High Cardinality

High Dimensionality

Strong versus Weak AI

The Right Tool for the Right Job

Classification versus Regression

Supervised Machine Learning

Unsupervised Learning

Neural Networks

Reinforcement Learning

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

Marketing Mix Modeling

Econometrics

Customer Lifetime Value

One-to-One Marketing-The Meme

Seat-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?

Machine Learning in Market Research

Marketplace Segmentation

Social Media Monitoring

Competitive Analysis

Raising Awareness

Public Relations

Direct Response

Database Marketing

Advertising

Pay-per-Click (PPC) Search

Search Optimization (aka Content Marketing)

Social Media Engagement

Social Snooping

Socialbots

Social Posting

In Real Life

The B2B World

Lead Scoring

Sales Management Advisory

DIY-Some Models Are Useful

Chapter 5: Using AI to Persuade

The In-Store Experience

Shopping Assistance

Restaurants

Store Operations

On the Phone

The Onsite Experience-Web Analytics

Landing Page Optimization

A/B and Multivariate Testing

Onsite User Experience

Recommendation Engines

Personalization

Merchandising

Pricing

Market Basket Analysis

Closing the Deal

Remarketing

E-mail Marketing

Back to the Beginning: Attribution

Chapter 6: Using AI for Retention

Growing Customer Expectations

Retention and Churn

Many Unhappy Returns

Customer Sentiment

Customer Service

Call Center Support

Bots

Predictive Customer Service

Chapter 7: The AI Marketing Platform

Supplemental AI

Salesforce

Adobe

Marketing Tools from Scratch

Communicating Insightsâ€"Narratives from Data

Customer Journey Journal

Recommender in Chief

Build a Whole Website

A Word about Watson

Hey, Check This Out

That Was Easy.

Lucy-Watson's Progeny

Better Together

Building Your Own

Chapter 8: Where Machines Fail

A Hammer Is Not a Carpenter

Target-A Cautionary Tale

Machine Mistakes

Data Is Difficult

Just Following Orders

Human Mistakes

Optimizing the Wrong Thing

Correlation Is Not Causation

The Ethics of AI

Privacy

Follow Your Heart

Intentional Manipulation

Trumped-Up Charges?

Unintended Bias

Solution?

What Machines Haven't Learned Yet

Chapter 9: Your Strategic Role in Onboarding AI

Getting Started, Looking Forward

Testing the Waters versus Boiling the Ocean

Automate These Processes First

How Much Should You Spend?

AI to Leverage Humans

Collaboration at Work

Your Role as Manager

Working with Data Scientists

Taking the Right Steps

Expressing the Value of Marketing

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

Judgment

Imagination

Empathy

Trust Your Gut

The Smell Test

Chapter 11: What Tomorrow May Bring

The Path to the Future

Machine, Train Thyself

Intellectual Capacity as a Service

Conscience Support System

What If We're All Just as Smart?

Data as a Competitive Advantage

Data as a Business

Data as a Sideline

Insight Automation

How Far Will Machines Go?

Like a Boss

Pretending to Be a Human

Beyond Human

Your Bot Is Your Brand

My AI Will Call Your AI

Your Personal AI Ecosystem

Your Personal Shopper

Computing Tomorrow

About the Author

Index

EULA.

Notes:

Includes bibliographical references at the end of each chapters and index.

Access using campus network via VPN at home (THEi Users Only).

Description based on print version record.

ISBN:

9781119406372

1119406374

9781119406365

1119406366

9781119406341

111940634X

OCLC:

992798734