Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
"The Freakonomics of big data."
Stein Kretsinger, founding executive of Advertising.com; former lead analyst at Capital One
This book is easily understood by all readers. Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.
You have been predicted by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.
Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.
How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.
Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future lifting a bit of the fog off our hazy view of tomorrow means pay dirt.
In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:
- What type of mortgage risk Chase Bank predicted before the recession.
- Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves.
- Why early retirement decreases life expectancy and vegetarians miss fewer flights.
- Five reasons why organizations predict death, including one health insurance company.
- How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual.
- How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy!
- How companies ascertain untold, private truths how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job.
- How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free.
- What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia.
A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.
Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward but that can be predicted in advance?
Whether you are a consumer of it or consumed by it get a handle on the power of Predictive Analytics.
Foreword Thomas H. Davenport xiii
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
Ten Predictions for the First Hour of 2020
A. Five Effects of Prediction 221
B. Twenty-One Applications of Predictive Analytics 222
C. Prediction PeopleCast of "Characters" 225
About the Author 292
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 professorwho used to sing educational songs to his studentsand a renowned speaker, educator, and leader in the field.
Praise for Predictive Analytics
"What Nate Silver did for poker and politics, this does for everything else. A broad, well-written book easily accessible to non-nerd readers."
DAVID LEINWEBER, author of Nerds on Wall Street: Math, Machines and Wired Markets
"This book is an operating manual for twenty-first-century life. Drawing predictions from big data is at the heart of nearly everything, whether it's in science, business, finance, sports, or politics. And Eric Siegel is the ideal guide."
STEPHEN BAKER, author of The Numerati and Final Jeopardy: Man vs. Machine and the Quest to Know Everything
"Simultaneously entertaining, informative, and nuanced. Siegel goes behind the hype and makes the science exciting."
RAYID GHANI, Chief Data Scientist, Obama for America 2012 Campaign
"This is Moneyball for business, government, and healthcare."
JIM STERNE, founder, eMetrics Summit; chairman, Digital Analytics Association
"Predictive Analytics is not only a deeply informative dive into a topic that is critical to virtually every sector of business today, it is also a delight to read."
GEOFFREY MOORE, author of Crossing the Chasm
"The future is right nowyou're living in it. Read this book to gain understanding of where we are and where we're headed."
ROGER CRAIG, record-breaking analytical Jeopardy! champion; CEO, Cotinga
Everyone has been predicted — by companies, governments, law-enforcement, hospitals and universities. Their computers say, "I knew you were going to do that!" Why? For good reason: Predicting human behavior combats financial risk, fortifies healthcare, reduces spam, toughens crime-fighting and boosts sales. Predictive analytics is the science that unleashes the power of this data.
In his rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction in his new book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (WILEY; February 2013; Hardcover & eBook; $28.00).
“Compelled to grow and propelled to the mainstream, predictive technology is commonplace and affects everyone, every day. It impacts your experiences in undetectable ways as you drive, shop, study, vote, see the doctor, communicate, watch TV, earn, borrow, or even steal,” says Siegel. “This book is about the most influential and valuable achievements of computerized prediction, and the two things that make it possible: the people behind it, and the fascinating science that powers it."
With this technology, computers literally learn from data how to predict the future behavior of individuals. In business, this ability to predict — which is based on patterns found in data — helps businesses make informed decisions and identify risks and opportunities. Predictive Analytics gives the reader a core understanding of how this technology works.
While perfect prediction is not possible, even lousy predictions can be extremely valuable. In this book, Siegel reveals the risks and rewards of prediction with intriguing examples such as:
- What unique form of mortgage risk Chase Bank predicted before the recession
- Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves
- Why early retirement decreases life expectancy and vegetarians miss fewer flights
- Five reasons organizations predict death, including one health insurance company
- How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job
- How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free
- What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia
- The “Anxiety Index” of blogs
- A compendium of 147 examples of how predictive analytics is applied in various aspects of life and business
“Data embodies a priceless collection of experience from which to learn. Every medical procedure, credit application, Facebook post, movie recommendations, spammy e-mail and purchase of any kind – each positive or negative outcome, each successful or failed event or transaction – is encoded as data and warehoused,” adds Siegel. “As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold – data in its raw form is boring crud. The gold is what’s discovered therein. With the new knowledge gained, prediction is possible.”
A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. Whether a consumer of it – or consumed by it – citizens of today's world needs a handle on the power of predictive analytics.