Archive for August, 2013

August 26th 2013

Chatting with your Computer: How the iPhone’s Siri Compares with IBM’S Watson

big think

I originally published this article in Big Think. The article relates to my book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

Chatting with your Computer: How the iPhone's Siri Compares with IBM'S Watson

IBM's Watson computer, which defeated the two all-time human champs on the TV quiz show Jeopardy! in 2011, is a glowing example of the heights achievable by predictive analytics. This is a machine that answers questions—about any of a broad, open range of topics. The same core technology that companies use to predict whether you'll buy and which ad you'll click is employed under Watson's hood to predict, given a question, whether a candidate answer is correct. With this capability in place, Watson can "cast a wide net" by collecting thousands of candidate answers for a question, and then narrow down to the correct answer by predicting for each, "Is this the right answer?"

But, given that many of us have Siri, the iPhone's eager-to-please personal assistant, right in our pocket, what's so special about IBM's one-of-a-kind, multi-refrigerator-sized monstrosity that cost tens of millions of dollars to build? How do the two compare?

First introduced as the main selling point to distinguish the iPhone 4S from the preceding model, Siri responds to a broad, expanding range of voice commands and inquiries directed toward your iPhone.

Siri handles simpler language than Watson does: Users tailor requests for Siri knowing that they’re speaking to a computer, whereas Watson fields Jeopardy!’s clever, wordy, information-packed questions that have been written with only humans in mind, without regard or consideration for the possibility that a machine might be answering. Because of this, Siri’s underlying technology is designed to solve a different, simpler variant of the human language problem.

Click here to read the full article in

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August 21st 2013

Video Clips Expound Upon Predictive Analytics

Since February's launch of my book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, I have participated in a number of video interviews that explore the topic and field of predictive analytics. Here is a sampling:


Bloomberg TV – Predictive Analytics in Four Minutes:



Forrester – where are we in predictive analytics' adoption?

Forrester – persuasion modeling for Obama and for marketing:



Forrester – Will privacy concerns stunt the power of predictive analytics?



Interview on Big Think:



Interview on The Street:



Social Media Today – Trends, big data, and the future of predictive analytics: 



Interview on Israel National Radio:



Thanks for watching! For several more videos, click here


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August 19th 2013

Five Reasons Siegel’s Book “Predictive Analytics” Matters to Experts

Book Cover 2


Five Reasons Siegel’s Book “Predictive Analytics” Matters to Experts

My new book – Predictive Analytics:  The Power to Predict Who will Click, Buy, Lie, or Die   – is a revealing, accessible primer positioned to appeal well outside our industry.

But, if you’re already an expert, here are five reasons to read it nonetheless:

        New detailed case studies

        Advanced topics (ensembles, uplift, etc.)

        An in-depth, startling treatise on privacy

        A compendium of 147 mini-case studies

        A means to share your field with your family, friends, or supervisor

I took on a rewarding challenge: Sharing with layreaders at large a complete picture of predictive analytics, from the  way in which it serves actionable value to organizations, down to the inner workings of predictive modeling. It’s high time the predictive power of data — and how to analytically tap it — be demystified to reveal its intuitive yet awe–inspiring nature. As you and I know, learning from data to predict human behavior is not arcane. Rather, it is a broadly applicable no–brainer. If we spread the word with an appropriately friendly overview, we’ll readily earn broad buy in, much to the benefit of our blossoming  industry.

More than a string of anecdotes, this book delivers complete conceptual coverage of the field and places predictive analytics into a worldview perspective, defining its societal and even cultural context. Although packaged with catchy chapter titles and brand name stories, the conceptual outline is fundamental:

1) deployment, 2) civil liberties, 3) data, 4) core modeling, 5) ensembles, 6) IBM’s Watson, and 7) uplift modeling (aka net lift or persuasion modeling).

Although this pop science, mathless introduction is readable by everyone, you as an expert will also benefit from reading it. While some endorsers proclaim it is “The Freakonomics of big data“ that “reads like a thriller!”, others speak to the practitioner:

“The definitive book of this industry has arrived. Dr. Siegel has achieved what few have even attempted: An accessible, captivating tome on predictive analytics that is a  ‘must read’ for all interested in its potential — and peril.”

Mark Berry, VP, People Insights, ConAgra Foods


“Written in a lively language, full of great quotes, real-world examples, and case studies, it is a pleasure to read. The more technical audience will enjoy chapters on The Ensemble Effect and uplift modeling — both very hot trends. I highly recommend this book!”

Gregory Piatetsky-Shapiro, Editor, KDnuggets;

Founder, KDD Conferences


Here’s a bit more on the five reasons this book matters to you:

1. New case studies. Find detailed stories you have  never before heard from Hewlett-Packard, Chase, and the Obama Campaign. And did you know that John Elder once invested all his  own personal money into a blackbox stock market system of his own design? That’s the opening story of Chapter 1.

2. Advanced topics. Dive into ensemble models, crowdsourcing predictive analytics, uplift modeling (aka net lift or persuasion modeling), text analytics, and social media-based financial indicators. Plus, enjoy a fun yet fairly deep chapter on IBM’s Jeopardy!-playing Watson computer.

3. Privacy and other civil liberty concerns. This ethical realm is so intractable and inconstant, no one is a true expert, in a sense. My treatise on it, a chapter entitled “With Power Comes Responsibility,” addresses the questions: In what ways does predictive analytics fuel the contentious flames surrounding data privacy, raising its already-high stakes? What civil liberty concerns arise beyond privacy per se? What about predictive crime models that help decide who stays in prison?

4. A cross-industry compendium of 147 cases. This comprehensive collection of mini-case studies serves to illustrate just how wide the field’s reach extends. This color insert includes a table for each of the verticals: Personal Life, Marketing, Finance, Healthcare, Crime Fighting, Reliability Modeling, Government and Nonprofit, Human Language and Thought, and Human Resources. One PhD-level technical book reviewer complimented me by saying, “The tables alone are worth the price of admission.”

5. Share your field of expertise. Would you like your colleagues and manager to better understand the value and potential of your work? Would you enjoy seeing your loved ones   not only learn what the heck it is you do and why it’s so important, but enjoy it and get excited? Give this book to your family, friends, and boss.

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August 12th 2013

Review of “Predictive Analytics” by Pierre DeBois

Small Business Trends

Review of “Predictive Analytics”

I was honored to have my book, Predictive Analytics:  The Power to Predict Who Will Click, Buy, Lie, or Die, reviewed by Pierre DeBois in Smart Business Trends–Check it out:

“I knew you’d say that.” –Sylvester Stallone as Judge Dredd

That may have been Stallone’s catch phrase in the movie Judge Dredd, but these days a CMO (Chief Marketing Officer) or even your marketing strategist could easily say that phrase as well. 

These days analytic solutions are breaking down more data from many sources, creating more accurate sales and operational models.  Businesses are learning to compete through innovation, but how does one model the volume of analysis and concepts presented?

Predictive Analytics:  The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel, PhD serves as a clarion call for business managers to understand the possibilities and myths.

Siegel is the Founding Conference Chair of Predictive Analytics World and President of Prediction Impact, an analytics services firm. 

I was really excited when I came across the book.  Several new analytics books are being released this year, so I asked Wiley for a review copy. 

Click here to read the full article

Pierre DeBois is the founder of Zimana a consultancy providing strategic analysis to small and medium sized businesses that rely on web analytics data. A Gary, Indiana native, Pierre is currently based in Brooklyn. He blogs about marketing, finance, social media, and analytics at Zimana blog.

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August 6th 2013

Prediction, Influence and the Future of Power

The Washington Post

I originally published this article in The Washington Post.  The article relates to my book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

Prediction, Influence and the Future of Power

The role prediction played in the 2012 presidential election taught both the political and business worlds an important lesson:  True power comes from influencing the future rather than merely predicting it.

Blogger Nate Silver may have successfully forecast the election results, but President Obama’s team quietly used predictive analytics to sway which way the winds would blow, discovering which individual voters were more likely to be positively influenced by campaign contact.

But this is only one example of how the prediction of individuals’ wants, needs and behaviors holds the power to change outcomes.

Businesses, much like political campaigns, benefit from moving beyond the forecasting of broad trends to the forming of individual, per-person predictions. In the business world, these predictions drive the detailed operations of marketing, risk management, and fraud detection one customer at a time.

Now, rest assured, a doctorate isn’t required to understand how computers churn out tens of thousands—or even millions—of predictions. The principles behind predictive analytics are relatively easy to understand.

Click here to read the full article in

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