ERIC SIEGEL
Former Columbia University professor founder of Predictive Analytics World and Text Analytics World, author of 'Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
MEET ERIC SIEGEL
The president of Prediction Impact, Inc., author of the acclaimed book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Executive Editor of the Predictive Analytics Times, and the founder of Predictive Analytics World and Text Analytics World, Eric Siegel is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won the engineering school's award for teaching, including graduate-level courses in machine learning and intelligent systems - the academic terms for predictive analytics. After Columbia, Dr. Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies.
Dr. Siegel is the instructor of the acclaimed online training program, Predictive Analytics Applied. He has published over 20 papers and articles in data mining research and computer science education and has served on 10 conference program committees.
He has appeared on Bloomberg TV and Radio, Fox News, BNN (Canada), Israel National Radio, Radio National (Australia), The Street, Newsmax TV, and NPR affiliates.
Dr. Eric Siegel and his book have been featured in Businessweek, CBS MoneyWatch, The Financial Times, Forbes, Forrester, Fortune, The Huffington Post, The New York Times, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.
Dr. Siegel is the instructor of the acclaimed online training program, Predictive Analytics Applied. He has published over 20 papers and articles in data mining research and computer science education and has served on 10 conference program committees.
He has appeared on Bloomberg TV and Radio, Fox News, BNN (Canada), Israel National Radio, Radio National (Australia), The Street, Newsmax TV, and NPR affiliates.
Dr. Eric Siegel and his book have been featured in Businessweek, CBS MoneyWatch, The Financial Times, Forbes, Forrester, Fortune, The Huffington Post, The New York Times, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.
ERIC SIEGEL SPEAKING TOPICS
Predictive Analytics: Delivering on the Promise of Big Data
The excitement over “big data” has grown dramatically. But what is the value, the function, the purpose? The most actionable win to be gained from data is prediction. This is achieved by analytically learning from data how to render predictions for each individual. Such predictions drive more effectively the millions of operational decisions that organizations make every day. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel reveals how predictive analytics works, and the ways in which it delivers value to organizations across industry sectors.
Four Ways Predictive Analytics Leverages Social Media
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer decisions. But prediction is the ultimate challenge; predictive analytics can use all the help -- and all the data -- it can get. No data predicts a customer’s behavior like social data: who the customer knows, what sentiment he or she expresses, and which things the customer Likes. In this session, Predictive Analytics World founder and Predictive Analytics author Eric Siegel describes four ways in which predictive analytics drives better business decisions with the use of social data.
Segmentation and Personalization with Predictive Analytics
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer decisions. But prediction is the ultimate challenge and the ultimate mystery. How does predictive analytics work? At the heart of this technology is segmentation. It’s a kind of automated, hyper-segmentation on overdrive that leverages the best of machine learning and big data technology. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel shows how predictive analytics works and serves to personalize marketing.
Customer Conversion with Predictive Analytics and Social Media
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer interactions. But prediction is the ultimate challenge; predictive analytics can use all the help -- and all the data -- it can get. No data predicts a customer’s behavior like social data: who the customer knows, what sentiment he or she expresses, and which things the customer Likes. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel describes four ways in which predictive analytics drives better marketing engagement with the use of social data.
Predictive Analytics for Marketing: Learning from Data to Predict
Prediction is the holy grail of marketing. Foreseeing each customer purchase, click, and cancellation is the ultimate means to drive more effective, per-customer decisions. And today’s enterprise has a wealth of marketing experience from which to learn to predict - aka, data.
This learning process is called predictive analytics. In this keynote session, Predictive Analytics author and Predictive Analytics World founder Eric Siegel describes how this technology leverages big data, learning from it in order to drive more effective marketing.
Five Ways to Lower Costs with Predictive Analytics
Question: How does predictive analytics actively deliver increased returns? Answer: By driving operational decisions with predictive scores - one score assigned to each customer. In this way, an enterprise optimizes on what customers WILL do. But, in tough times, our attention turns away from increasing returns, and towards decreasing costs. On top of boosting us up the hill, can predictive analytics pull us out of a hole? Heck, yes. Marketing more optimally means you can market less. Filtering high risk prospects means you will spend less. And, by retaining customers more efficiently, well, a customer saved is a customer earned - and one you need not acquire. In this keynote, Eric Siegel will demonstrate five ways predictive analytics can lower costs without decreasing business, thus transforming your enterprise into a Lean, Mean Analytical Machine. You’ll want to run back home and break the news: We can’t afford not to do this.
Persuasion by the Numbers: Optimize Marketing Influence by Predicting It
Data driven marketing decisions are meant to maximize impact - right? Well, the only way to optimize marketing influence is to predict it. The analytical method to do this is called uplift modeling. This is a completely different animal from what most models predict: customer behavior. Instead, uplift models predict the influence on customer behavior gained by choosing one marketing action over another. The good news is case studies show ROI going where it has never gone before. The bad news? You need a control set... But you should have been using one anyway! The crazy part is that “marketing influence” can never be observed for any one customer, since it literally involves the inner workings of the customer’s central nervous system. If influence can’t be observed, how can we possibly model and predict it?
The Prediction Effect, the Data Effect, and the Persuasion Effect
What are the underlying principles that make predictive analytics effective? Why is data predictive, why is imperfect prediction valuable, and what type of prediction succeeds to persuade? You have heard of the butterfly, Doppler, and placebo effects. In this session, PAW founder Eric Siegel covers the Prediction, Data, and Persuasion Effects. Each of these Effects encompasses the fun part of science and technology: an intuitive hook that reveals how it works and why it succeeds.
Driving Decisions with Predictive Analytics: The Top Five Business Applications
The value proposition is straight-forward and proven: Predictive analytics produces business rules that deliver. The customer predictions generated by predictive analytics’ business rules deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. Harnessing value with predictive analytics depends on some careful choices: What kind of customer behavior you predict and which operational decisions you automate with it. This session will guide you in making these choices, and cover
a healthy dose of the core technology along the way - in a “user-friendly” manner that makes the concepts intuitive, illustrating with detailed case studies.
What you will learn:
• How predictive analytics automatically derives rules for decision automation by learning from experience
• The top five business applications of analytically optimized rules
• What business rules produced by predictive analytics look like and how they work
How Predictive Analytics Fortifies Healthcare
Predictive analytics addresses today’s pressing challenges in healthcare effectiveness and economics by improving operations across the spectrum of healthcare functions, including:
• Clinical services and other healthcare management operations such are targeting screening and compliance intervention
• Insurance pricing and management
• Healthcare product marketing
Applied in these areas, predictive analytics serves to improve patient care, reduce cost, and bring greater efficiencies. In this keynote address, Eric Siegel will cover today’s rapidly emerging movement to fortify healthcare with big data’s biggest win: the power to predict.
The excitement over “big data” has grown dramatically. But what is the value, the function, the purpose? The most actionable win to be gained from data is prediction. This is achieved by analytically learning from data how to render predictions for each individual. Such predictions drive more effectively the millions of operational decisions that organizations make every day. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel reveals how predictive analytics works, and the ways in which it delivers value to organizations across industry sectors.
Four Ways Predictive Analytics Leverages Social Media
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer decisions. But prediction is the ultimate challenge; predictive analytics can use all the help -- and all the data -- it can get. No data predicts a customer’s behavior like social data: who the customer knows, what sentiment he or she expresses, and which things the customer Likes. In this session, Predictive Analytics World founder and Predictive Analytics author Eric Siegel describes four ways in which predictive analytics drives better business decisions with the use of social data.
Segmentation and Personalization with Predictive Analytics
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer decisions. But prediction is the ultimate challenge and the ultimate mystery. How does predictive analytics work? At the heart of this technology is segmentation. It’s a kind of automated, hyper-segmentation on overdrive that leverages the best of machine learning and big data technology. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel shows how predictive analytics works and serves to personalize marketing.
Customer Conversion with Predictive Analytics and Social Media
Prediction delivers the ultimate payoff by driving millions of more effective, per-customer interactions. But prediction is the ultimate challenge; predictive analytics can use all the help -- and all the data -- it can get. No data predicts a customer’s behavior like social data: who the customer knows, what sentiment he or she expresses, and which things the customer Likes. In this keynote, Predictive Analytics World founder and Predictive Analytics author Eric Siegel describes four ways in which predictive analytics drives better marketing engagement with the use of social data.
Predictive Analytics for Marketing: Learning from Data to Predict
Prediction is the holy grail of marketing. Foreseeing each customer purchase, click, and cancellation is the ultimate means to drive more effective, per-customer decisions. And today’s enterprise has a wealth of marketing experience from which to learn to predict - aka, data.
This learning process is called predictive analytics. In this keynote session, Predictive Analytics author and Predictive Analytics World founder Eric Siegel describes how this technology leverages big data, learning from it in order to drive more effective marketing.
Five Ways to Lower Costs with Predictive Analytics
Question: How does predictive analytics actively deliver increased returns? Answer: By driving operational decisions with predictive scores - one score assigned to each customer. In this way, an enterprise optimizes on what customers WILL do. But, in tough times, our attention turns away from increasing returns, and towards decreasing costs. On top of boosting us up the hill, can predictive analytics pull us out of a hole? Heck, yes. Marketing more optimally means you can market less. Filtering high risk prospects means you will spend less. And, by retaining customers more efficiently, well, a customer saved is a customer earned - and one you need not acquire. In this keynote, Eric Siegel will demonstrate five ways predictive analytics can lower costs without decreasing business, thus transforming your enterprise into a Lean, Mean Analytical Machine. You’ll want to run back home and break the news: We can’t afford not to do this.
Persuasion by the Numbers: Optimize Marketing Influence by Predicting It
Data driven marketing decisions are meant to maximize impact - right? Well, the only way to optimize marketing influence is to predict it. The analytical method to do this is called uplift modeling. This is a completely different animal from what most models predict: customer behavior. Instead, uplift models predict the influence on customer behavior gained by choosing one marketing action over another. The good news is case studies show ROI going where it has never gone before. The bad news? You need a control set... But you should have been using one anyway! The crazy part is that “marketing influence” can never be observed for any one customer, since it literally involves the inner workings of the customer’s central nervous system. If influence can’t be observed, how can we possibly model and predict it?
The Prediction Effect, the Data Effect, and the Persuasion Effect
What are the underlying principles that make predictive analytics effective? Why is data predictive, why is imperfect prediction valuable, and what type of prediction succeeds to persuade? You have heard of the butterfly, Doppler, and placebo effects. In this session, PAW founder Eric Siegel covers the Prediction, Data, and Persuasion Effects. Each of these Effects encompasses the fun part of science and technology: an intuitive hook that reveals how it works and why it succeeds.
Driving Decisions with Predictive Analytics: The Top Five Business Applications
The value proposition is straight-forward and proven: Predictive analytics produces business rules that deliver. The customer predictions generated by predictive analytics’ business rules deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. Harnessing value with predictive analytics depends on some careful choices: What kind of customer behavior you predict and which operational decisions you automate with it. This session will guide you in making these choices, and cover
a healthy dose of the core technology along the way - in a “user-friendly” manner that makes the concepts intuitive, illustrating with detailed case studies.
What you will learn:
• How predictive analytics automatically derives rules for decision automation by learning from experience
• The top five business applications of analytically optimized rules
• What business rules produced by predictive analytics look like and how they work
How Predictive Analytics Fortifies Healthcare
Predictive analytics addresses today’s pressing challenges in healthcare effectiveness and economics by improving operations across the spectrum of healthcare functions, including:
• Clinical services and other healthcare management operations such are targeting screening and compliance intervention
• Insurance pricing and management
• Healthcare product marketing
Applied in these areas, predictive analytics serves to improve patient care, reduce cost, and bring greater efficiencies. In this keynote address, Eric Siegel will cover today’s rapidly emerging movement to fortify healthcare with big data’s biggest win: the power to predict.
 
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
The #1 bestseller in multiple Amazon categories for months on end |
"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, Nerds on Wall Street: Math, Machines and Wired Markets |
WHITE PAPER
White PapersSeven Reasons You Need Predictive Analytics TodayThank you for your interest in the white paper, “Seven Reasons You Need Predictive Analytics Today,” written by PAW Conference Chair Eric Siegel, Ph.D., and sponsored by IBM.
Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This definitive white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.
Download the free white paper here:www.predictiveanalyticsworld.com/seven_reasons_whitepaper.php
Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This definitive white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.
Download the free white paper here:www.predictiveanalyticsworld.com/seven_reasons_whitepaper.php
