Archive for February, 2013

February 25th 2013

“Predictive Analytics” Book Gets a High Rank and a Haiku

 

Here's an update on my book – just released last week – Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

I am pleased to report the book is the #1 Best Seller in both "Business Planning & Forecasting" and "Econometrics" on Amazon.

Businessweek boiled down the book into the following haiku (a short poem of three lines with 5, 7, and 5 syllables, respectively):

 

Companies agree

With what your ex always said:

You're predictable.

 

 

Video: eight answers about predictive analytics – Did Nate Silver use it, is it a "big data" thing, etc 

 

See excerpts – Preface, Intro, Foreword by Davenport, and more

 

View the annotated Table of Contents


Five reasons this book matters to experts


39 colleagues who loved this book


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February 25th 2013

The Future of Prediction: Predictive Analytics in 2020

 

The Future of Prediction: Predictive Analytics in 2020

 

What's next is what's next… Predictive analytics is where business intelligence is going. 

— Rick Whiting, InformationWeek  

 

Ten Predictions for the First Hour of 2020

 

Good morning. It's January 2, 2020, the first workday of the year. As you drive to the office, the only thing predictive analytics doesn't do for you is steer the car (yet that's coming soon as well).

 

1. Anti-theft. As you enter your car, a predictive model establishes your identity based on several biometric readings, rendering it virtually impossible for an imposter to start the engine.

 

2. Entertainment. Pandora plays new music it predicts you will like.

 

3. Traffic. Your navigator pipes up and suggests alternative routing due to predicted traffic delays. Because the new route has hills and your car's battery—its only energy source—is low, your maximum acceleration is decreased.

 

4. Breakfast. An en-route drive-through restaurant is suggested by a recommendation system that knows its daily food preference predictions must be accurate or you will disable it.

 

5. Social. Your Social Techretary offers to read you select Facebook feeds and Match.com responses it predicts will be of greatest interest. Inappropriate comments are accurately filtered out. CareerBuilder offers to read job postings to which you're predicted to apply. When playing your voicemail, solicitations such as robo call messages are screened by predictive models just like email spam.

 

6. Deals. You accept your smartphone's offer to read to you a text message from your wireless carrier. Apparently, they've predicted you're going to switch to a competitor, because they are offering a huge discount on the iPhone 13.

 

7. Internet search. As it's your colleague's kid's birthday, you query for a toy store that's en route. Siri, available through your car's audio, has been greatly improved—better speech recognition and proficiently tailored interaction.

 

8. Driver inattention. Your seat vibrates as internal sensors predict your attention has wavered—perhaps you were distracted by a personalized billboard a bit too long.

 

9. Collision avoidance. A stronger vibration plus a warning sound alert you to a potential imminent collision—possibly with a child running toward the curb or another car threatening to run a red light.

 

10. Reliability. Your car says to you, "Please take me in for service soon, as I have predicted my transmission will fail within the next three weeks."

 

Predictive analytics not only enhances your commute—it was instrumental to making this drive possible in the first place:

 

·         Car loan. You could afford this car only because a bank correctly scored you as a low credit risk and approved your car loan.

 

·         Insurance. Sensors you volunteered to have installed in your car transmit driving behavior readings to your auto insurance company, which in turn plugs them into a predictive model in order to continually adjust your premium. Your participation in this program will reduce your payment by $30 this month.

 

·         Wireless reliability. The wireless carrier that serves to connect to your phone—as well as your car—has built out its robust infrastructure according to demand prediction.

 

·         Cyber-security. Unbeknownst to you, your car and phone avert crippling virus attacks by way of analytical detection.

 

·         Road safety. Impending hazards such as large potholes and bridge failures have been efficiently discovered and preempted by government systems that predictively target inspections.

 

·         No reckless drivers. Dangerous repeat moving violation offenders have been scored as such by a predictive model to help determine how long their licenses should be suspended.

 

·         Your health. Predictive models helped determine the medical treatments you have previously received, leaving you healthier today.

 

Tomorrow's Just a Day Away

 

All the preceding capabilities are available now or have similar incarnations actively under development. Many are delayed more by the (now imminent) integration of your smartphone with your car than by the development of predictive technology itself. The advent of mobile devices built into your glasses, such as Google Glass, will provide yet another multiplicative effect on the moment-to-moment integration of prediction, as well as further accelerating the accumulation of data with which to develop predictive models.

 

Today, predictive analytics' all-encompassing scope already reaches the very heart of a functioning society. Organizations—be they companies, governments, law-enforcement, charities, hospitals or universities—undertake many millions of operational decisions in order to enact services. Prediction is key to guiding these decisions. It is the means with which to improve the efficiency of massive operations.

 

Several mounting ingredients promise to spread prediction even more pervasively: bigger data, better computers, wider familiarity, and advancing science. A growing majority of interactions between the organization and the individual will be driven by prediction.

 

The Future of Prediction 

 

Of course, the details and timing of these developments are up to conjecture; predictive analytics has not conquered itself.  But we can confidently predict more prediction. Every few months another big story about predictive analytics rolls off the presses. We're sure to see the opportunities continue to grow and surprise. Come what may, only time will tell what we'll tell of time to come.

 

Excerpted with permission of the publisher, Wiley, from Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (February 2013) by Eric Siegel, PhD. Dr. Siegel is the founder of Predictive Analytics World (www.pawcon.com), coming in 2013 to Toronto, San Francisco, Chicago, Washington D.C., Boston, Berlin, and London. For more information about predictive analytics, see the Predictive Analytics Guide .

 

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February 25th 2013

On-Demand Webinar Introduces Predictive Analytics

In this on-demand webinar hosted by UC Irvine, I introduce predictive analytics, its power and value, how it works in some quick detail, and privacy issues it brings up. At the end, I field questions about bootstrapping a career in this field

 

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February 18th 2013

Video: Eight Answers About Predictive Analytics

With my book on the topic releasing this week, here's an interview in which I answer eight questions about predictive analytics:

 


In the video I answer these questions:

1. What is predictive analytics?

2. Why is predictive analytics important?

3. Isn't prediction impossible?

4. Is predictive analytics a big data thing?

5. Did Nate Silver use predictive analytics to forecast Obama's elections?

6. Does predictive analytics invade privacy?

7. What are the hottest trends in predictive analytics?

8. What is the coolest thing predictive analytics has done?
 

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February 12th 2013

Excerpts and Table of Contents for “Predictive Analytics”

My book launches one week from today – Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (published by Wiley)

View the detailed table of contents

Excerpts: access the Foreword (by Thomas Davenport), preface, and full Introduction – plus other articles and excerpts

5 reasons this book matters to experts

39 colleagues who loved this book

More information and how to order the book

_______________________________

TABLE OF CONTENTS – a couple sample chapters:

INTRODUCTION: THE PREDICTION EFFECT

How does predicting human behavior combat risk, fortify healthcare, toughen crime fighting, and boost sales? Why must a computer learn in order to predict? How can lousy predictions be extremely valuable? What makes data exceptionally exciting? How is data science like porn? Why shouldn't computers be called computers? Why do organizations predict when you will die?

CHAPTER 4:
THE MACHINE THAT LEARNS: A LOOK INSIDE CHASE'S PREDICTION OF MORTGAGE RISK

What form of risk has the perfect disguise? How does prediction transform risk to opportunity? What should all businesses learn from insurance companies? Why does machine learning require art in addition to science? What kind of predictive model can be understood by everyone? How can we confidently trust a machine's predictions? Why couldn't prediction prevent the global financial crisis?

View the complete, detailed table of contents

More information and how to order the book
 

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February 4th 2013

Last Chance – Free Online Training with Preorder of My Book

This offer expires Wednesday so I'm reposting:

 

 

To drive early orders for my about-to-launch book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (published by Wiley Feb. 18), we're providing the following offer:

 

Preorder now ($15 on Amazon, currently) and receive:

Instructions:

  1. Order the book by Feb 6 (from any online vendor)
  2. Forward your email receipt to admin12@predictionimpact.com

 

Within two business days, you will receive three months of on-demand access to the training module (68 minute video – view a sneak preview now), as well as a 40% discount code for further training (must be used by March 20).

About the book, Predictive Analytics: In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction.

Five reasons this book matters to experts

Read the preface

39 of your colleagues who loved this book

More info

 
Happy reading!

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