Eric Siegel, Ph.D., an author of the acclaimed book “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die”, an Executive Editor of the Predictive Analytics Times and founder of Predictive Analytics World and Text Analytics World, makes the how and why of predictive analytics understandable and captivating. Eric is a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field. 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. Eric 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.
“Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die” is a rich, entertaining primer that reveals the power and perils of predictive analytics, showing how predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime-fighting, and boosts sales.
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 training program, Predictive Analytics for Business, Marketing and Web, and the online version, 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.
SPEECHES:Predictive Analytics: Tapping the Potential of Big Data
The excitement over “big data” has grown so dramatically as to assume the status of a Movement. But what is the the value, the function, the purpose? The most actionable thing 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 effective 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.
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.
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 Eric Siegel describes four ways in which predictive analytics drives better business decisions with the use of social data.
Five Ways to Lower Costs with Predictive Analytics
How does predictive analytics actively deliver increased returns? 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 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
Contact us to book this speakerData 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?
TESTIMONIALS:
— Rayid Ghani, Chief Data Scientist, Obama for America 2012 Campaign
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IN PRESS:
Prediction, Influence, and the Future of Power
Eric Siegel, The Washington Post, May 9, 2013
How Marketers (and Employers) Know So Much About You
Anne Fisher, Fortune Magazine, April 17, 2013
Should You Predict Which Employees Will Quit?
Laura Vanderkam, CBS MoneyWatch, April 5, 2013
Peril, Promise, and the Price of Predictive Technology
Eric Siegel, The Wall Street Journal’s MarketWatch, March 22, 2013
Radio Interview: The Hays Advantage on Bloomberg Radio
Kathleen Hays & Vonnie Quinn, Bloomberg’s The Hays Advantage, March 25, 2013
Book: HP Piloted Program to Predict Which Workers Would Quit
Joel Schectman, The Wall Street Journal, March 14, 2013
Predictive Analytics is a Goldmine for Startups
Martin Zwilling, Forbes, March 11, 2013
The Big Data Advantage Can Republicans Catch Up?
Maureen Mackey, The Fiscal Times, March 6, 2013
Interview With Predictive Analytics Author Eric Siegel
Phil Simon, The Huffington Post, March 6, 2013
Data Expert Siegel: Digital Analytics Helped Obama Get Re-Elected
Newsmax, January 25, 2013 (this article includes a video interview)
Predictive Analytics: The Power to Predict Human Behavior
Joe Wolverton, The New American, June 9, 2013
What the NSA Can’t Do with Your Data (Probably)
Adam Mazmanian, Federal Computer Week, Jun 12, 2013
Why Data Analysts Can Peer Into Your Future
Maureen MacKey, The Fiscal Times, June 12, 2013
Will Predictive Analytics Decide September’s Federal Election (in Australia)?
Matt Shea, The Vine (Australia), June 17, 2013
Big Data a Gold Mine for Jacksonville Startup (see sidebar)
Carole Hawkins, Jacksonville Business Journal, Apr 12, 2013
Half-Hour Audio Interview: Deploying Predictive Analytics Responsibly
Moe Abdou, 33voices, May 2013
Helping Educational Institutions: Predictive Analytics Head to Class
James Connolly, Big Data Republic, May 17, 2013
The Power of Prediction: Turning Predictive Analytics into Meaningful Metrics
Nancy Pekala, American Marketing Association, March 2013
Predictive Analytics Provides Way To ‘Proactively Pounce’
Stephanie Overby, CMO.com, April 11, 2013
The Rise of Predictive Analytics: Inside Scoop with Eric Siegel
Bob Thompson, CustomerThink, April 2, 2013
Predictive Power: Who Will Click, Buy, Lie or Die? – Overviews PA’s Five Effects
Beth Schultz, All Analytics, April 4, 2013
Merging Big Data Streams Could Create Mission Control for Healthcare
Mark Tobias, MedCity News, May 29, 2013
How Predictive Analytics Rule Our World
Fahmida Rashid, Slashdot, May 23, 2013
Why Predictive Analytics Matters
Nadia Cameron, CMO (Australia), April 30, 2013
Predictive Analytics Unlocks Big Data
Ned Smith, Business News Daily, April 12, 2013
Obama Digital Team Heads to Private Sector (free membership required)
Emily Steel, The Financial Times, March 27, 2013
Best Sellers on Predictive Analytics
Mike Gualtieri, Information Management and Forrester, March 21, 2013
Big Data Equals Big Innovation
Todd Schnick & Todd Youngblood, Business Transformation Radio, March 27, 2013
A Hunch on Predictive Analytics
Justin Kern, Information Management, February 28, 2013
Businessweek’s haiku poem about Eric Siegel’s book Predictive Analytics
Business Book Haiku, Businessweek, February 14, 2013
Marketers Get Some Machine Learning
Al Urbanski, Direct Marketing News, March 28, 2013
EHR Oracles: Merging Big Data Streams Could Create Mission Control for Healthcare
Mark Tobias, MedCity News, May 29, 2013
Predictive Analytics: Changing the Game Without the Hype and Spin
Don Tennant, ITBusinessEdge, March 18, 2013
The Surprising Predictive Power of Analytics
Skip Prichard, Leadership Insights, April 18, 2013
Predictive Analytics: Making Data Valuable
Michael McKinney, LeadershipNow, March 7, 2013
Your Favorite Stores Know You All Too Well
Steven Cherry, IEEE Spectrum Techwise Conversations, March 30, 2012
Targeted Marketing In Your Womb, Digital Product Placement, Pervasive Gaming
Marc Fennell, Australian Broadcasting Corporation’s Radio National, February 26, 2012
Will Big Data and Big Money Mean Big Trouble?
Warren Olney, KCRW (NPR affiliate), April 2, 2012
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