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Fast Facts

Predictive Analytics for Business, Marketing and Web (Chicago)

Customer Prediction: Who's coming back, Who"s not. And why.

Sep 24, 2008 - Sep 25, 2008
Morton's The Steakhouse 65 East Wacker Place Chicago, Illinois United States 60601
 

Highlights

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

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 and Marketing, or e-mail us at training@predictionimpact.com. You may also call (415) 683-1146.


See review

Event Profiles

Sponsors: Prediction Impact, Inc.
Speakers: Eric Siegel, Ph.D.

Contact Details

Contact person: Prediction Impact, Inc.
Email address:
Event website: http://www.predictionimpact.com/predictive-analytics-training.html
Phone: (415) 683-1146

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