Predictive Analytics : The Power to Predict Who Will Click, Buy, Lie, or Die

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  • Format: Hardcover
  • Copyright: 2013-02-19
  • Publisher: Wiley
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Predictive analytics uses statistical techniques to analyze current and historical facts to make predictions about future events. In business, analytics use patterns found in data to identify risks and opportunities and the results are then used to help businesses make informed and beneficial decisions. Predictive analytics is used in a variety of business fields, including, finance, insurance, telecommunications, retail, and healthcare. The Prediction Effect is a functional, practical book that helps readers gain maximal value from predictive analytics as well as learn what is fascinating about the core technology and how it works. The book will deliver a palatable serving of substance regarding the core technology to give executives and managers a concrete sense of how predictive analytics functions. The book will demonstrate how to use predictive analytics to assess a borrower's potential and ability to pay before granting a loan predict how expensive an insurance enrollee is likely to be by predicting the chances of illness, default, and bankruptcy predict store level demand for inventory management purposes reduce a business's exposure to fraud identify the most effective combination of products and marketing material that should be used to target consumers determine the likelihood of a customer wanting to terminate service analyze customers' spending and usage to help sell the right product at the right time determine which patients are at risk of developing certain conditions, like diabetes, asthma, and heart disease predict customers' buying habits in order to promote relevant products

Author Biography

ERIC SIEGEL, PhD, founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. Eric is a former Columbia University professor—who used to sing educational songs to his students—and a renowned speaker, educator, and leader in the field.

Table of Contents

Foreword Thomas H. Davenport xiii

Preface xv

What is the occupational hazard of predictive analytics?

Introduction: The Prediction Effect 1

Chapter 1: Liftoff! Prediction Takes Action (deployment) 17

Chapter 2: With Power Comes Responsibility: Hewlett-Packard, Target, and the Police Deduce Your Secrets (ethics) 37

Chapter 3: The Data Effect: A Glut at the End of the Rainbow (data) 67

Chapter 4: The Machine That Learns: A Look Inside Chase’s Prediction of Mortgage Risk (modeling) 103

Chapter 5: The Ensemble Effect: Netflix, Crowdsourcing, and Supercharging Prediction (ensembles) 133

Chapter 6: Watson and the Jeopardy! Challenge (question answering) 151

Chapter 7: Persuasion by the Numbers: How Telenor, U.S. Bank, and the Obama Campaign Engineered Influence (uplift) 187

Afterword 218

Ten Predictions for the First Hour of 2020


A. Five Effects of Prediction 221

B. Twenty-One Applications of Predictive Analytics 222

C. Prediction People—Cast of "Characters" 225

Notes 228

Acknowledgments 290

About the Author 292

Index 293

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