Predictive Marketing. Levin Dominique

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      Published by John Wiley & Sons, Inc., Hoboken, New Jersey

      Published simultaneously in Canada

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       Library of Congress Cataloging-in-Publication Data:

      Artun, Omer, 1969–

      Predictive marketing: easy ways every marketer can use customer analytics and big data / Omer Artun, Dominique Levin.

      pages cm

      Includes index.

      ISBN 978-1-119-03736-1 (hardback)

      ISBN 978-1-119-03732-3 (ePDF)

      ISBN 978-1-119-03733-0 (ePub)

      1. Marketing. I. Levin, Dominique, 1971– II. Title.

      HF5415.A7458 2015

      658.8 – dc23

      2015013473

      Cover image: Wiley

      Cover design: Abstract Shoppers © Maciej Noskwoski/GettyImages

      Introduction: Who Should Read this Book

      This book is for everyday marketers who want to learn what predictive marketing is all about, as well as for those marketers who are ready to use predictive marketing in their organizations. Whether you are just getting started with your research, or have already begun to implement predictive marketing, you will find many practical tips in this book.

      We share what marketers at companies large and small should know about predictive marketing. We show you how to achieve the same large returns as early adopters such as Harrah's Entertainment, Amazon, and Netflix. We also give you a practical guidebook to help you get started with this new way of marketing. And above all, we share stories from companies small and large, from retail to publishing, to software to manufacturing. All of these marketers have achieved revolutionary returns, and so can you.

      About This Book

      We are passionate about improving the quality of marketing and about arming marketers with the knowledge and tools they need to make marketing relevant again. We hope that the chapters that follow give marketers the vocabulary and the inspiration to start to understand and use big data and machine learning–powered marketing. We believe this will lead to a win-win for customers, businesses, and marketers. Customers will have more relevant and meaningful experiences, businesses will be able to build more profitable customer relationships, and marketers will gain visibility and respect within their organizations. We look forward to continuing the dialogue on our website www.predictivemarketingbook.com, the “Predictive Marketing Book” LinkedIn group (https://www.linkedin.com/groups?gid=8292127), or via twitter.com/agilone.

      This book is divided in three main parts. The first part, “A Complete Predictive Marketing Primer,” introduces many of the foundational elements in predictive marketing, including what is happening under the hood of predictive marketing software, how data science and predictive analytics work, and what are fundamentals behind the customer lifetime value concept. The second part of the book, “Nine Easy Plays to Get Started with Predictive Marketing,” is a playbook with concrete strategies to get you started with predictive marketing. The last part of the book, “How to Become a True Predictive Marketing Ninja,” gives an overview of predictive marketing technologies, some career advice for marketers, and looks at privacy and the future of predictive marketing. Many of the chapters can be read as stand-alone essays, so use the executive summary below to jump to the chapters that are most relevant to you.

      What Is in This Book

      Predictive marketing is a new way of thinking about customer relationships, powered by new technologies in big data and machine learning, which we collectively call predictive analytics. Marketers better pay attention to predictive analytics. Applying predictive analytics is the biggest game-changing opportunity since the Internet went mainstream almost 20 years ago. Although some large brands have been using pieces of predictive marketing for many years now, we are still in the early stages of adoption, and this is the right time to get started. The adoption of predictive marketing is accelerating among companies large and small because: (a) customers are demanding more meaningful relationships with brands, (b) early adopters show that predictive marketing delivers enormous value, and (c) new technologies are available to make predictive marketing easy.

      Many marketers want to at least understand what is happening in the predictive analytics black box, to more confidently apply these models or to be able to communicate with data scientists. After reading this chapter marketers will have a good understanding of the entire predictive analytics process. There are three types of predictive analytics models that marketers should know about: unsupervised learning, supervised learning, and reinforcement learning. Many marketers don't realize