Predictive Analytics for Business, Marketing & Web

Predictive Analytics for Business, Marketing and Web is a concentrated
training program that includes interactive breakout sessions.

Dates: May 8-9 and June 5-6, 2008
Location: San Francisco (May), New York City (June)
Sponsor: Prediction Impact, Inc.
Instructor: Eric Siegel, Ph.D.

100% of October 2007 attendees rated this program Excellent or Very
Good.

(This seminar is offered in conjunction with the eMetrics Marketing
Optimization Summit.)

**Early-bird special: Sign up one month ahead for $100 off the
registration fee

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.

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 数据挖掘研究院
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
Excel.