Artificial intelligence for marketing : practical applications

Author

• Sterne, Jim

Additional Author(s)

-

Publisher

Hoboken, New Jersey: John Wiley & Sons, Inc, 2017

Language

English

ISBN

9781119406341

Series

Subject(s)

• ARTIFICIAL INTELLIGENCE
• CONSUMER BEHAVIOR
• MARKETING

Notes

• Includes index

. . Includes index

Abstract

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.
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.

Physical Dimension

Number of Page(s)

1 online resource (xix, 344 pages)

Dimension

-

Other Desc.

ill.

Summary / Review / Table of Content

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? --
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? --
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 --
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? --
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 --
5. Using AI to persuade --
The in-store experience --
On the phone --
The onsite experience : web analytics --
Merchandising --
Closing the deal --
Back to the beginning : attribution --
6. Using AI for retention --
Growing customer expectations --
Retention and churn --
Many unhappy returns --
Customer sentiment --
Customer service --
Predictive customer service --
7. The AI marketing platform --
Supplemental AI --
Marketing tools from scratch --
A word about Watson --
Building your own --
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 --
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 --
10. Mentoring the machine --
How to train a dragon --
What problem are you trying to solve? --
What makes a good hypothesis? --
The human advantage --
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.

Exemplar(s)

#	Accession No.	Call Number	Location	Status
1.	00996/19	658.80028563 Ste A	Online !	Available