Archive for April, 2009

April 12th 2009

Predictive analytics training coming May to San Jose & NYC

I conduct the following training seminar on predictive analytics – here's the 2009 schedule:

Predictive Analytics for Business, Marketing and Web

A two-day intensive seminar brought to you by Prediction Impact, Inc. Dates: May 3-4, May 27-28, Oct 14-15, Oct 18-19, and Nov 11-12, 2009 Locations: San Jose (May), NYC (May), Stockholm (Oct), DC (Oct), San Francisco (Nov) Or access the online training: Predictive Analytics Applied. Immediate access at any time – SNEAK PREVIEW VIDEO 93% rate this program Excellent or Very Good. (details) **The official training program of Predictive Analytics World** **Offered in conjunction with eMetrics events**


About This Seminar Business metrics do a great job summarizing the past. But if you want to predict how customers will respond in the future, there is one place to turn—predictive analytics. By learning from your abundant historical data, predictive analytics provides the marketer something beyond standard business reports and sales forecasts: actionable predictions for each customer. These predictions encompass all channels, both online and off, foreseeing which customers will buy, click, respond, convert or cancel. If you predict it, you own it. The customer predictions generated by predictive analytics deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. For online applications such as e-marketing and customer care recommendations, predictive analytics acts in real-time, dynamically selecting the ad, web content or cross-sell product each visitor is most likely to click on or respond to, according to that visitor's profile. This is AB selection, rather than just AB testing. Predictive Analytics for Business, Marketing and Web is a concentrated training program that includes interactive breakout sessions and a brief hands-on exercise. In two days we cover:

  • The techniques, tips and pointers you need in order to run a successful predictive analytics and data mining initiative
  • How to strategically position and tactically deploy predictive analytics and data mining at your company
  • How to bridge the prevalent gap between technical understanding and practical use
  • How a predictive model works, how it's created and how much revenue it generates
  • Several detailed case studies that demonstrate predictive analytics in action and make the concepts concrete
  • NEW TOPIC: Five Ways to Lower Costs with Predictive Analytics

Instructor: Eric Siegel, Ph.D. No background in statistics or modeling is required. The only specific knowledge assumed for this training program is moderate experience with Microsoft Excel or equivalent. For more information, visit Predictive Analytics for Business, Marketing and Web, e-mail us at training@predictionimpact.com or call (415) 683-1146. Cross-Registration Special: Attendees earn $250 off the Predictive Analytics World Conference $100 off early registration, 3 weeks ahead

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April 11th 2009

New Book: Handbook of Statistical Analysis and Data Mining Applications

A mammoth new must-have data mining book is coming, the Handbook of Statistical Analysis and Data Mining Applications, by Robert Nisbet, PhD, John Elder, PhD, and Gary Miner, PhD.

“The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book for business analysts, scientists, engineers and researchers that brings together in a single resource all the information a beginner will need to rapidly learn how to conduct data mining and the statistical analysis required to interpret the data once mined.”

I previewed the book and wrote this heartfelt testimony:

Data mining practitioners, here is your bible, the complete “driver’s manual” for data mining.  From starting the engine to handling the curves, this book covers the gamut of data mining techniques – including predictive analytics and text mining – illustrating how to achieve maximal value across business, scientific, engineering and medical applications.  What are the best practices through each phase of a data mining project?  How can you avoid the most treacherous pitfalls?  The answers are in here.

Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications.  This way, newcomers start their engines immediately and experience hands-on success.

If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource.  To put it lightly, if this book isn’t on your shelf, you’re not a data miner.

You can pre-order it on Amazon.

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