eMetrics Marketing Optimization Summit
London, 20-21 May, 2008
Predictive Analytics Training

Calculate your customers’ future response.

Program:	An Introduction to Predictive Analytics
Dates:	London: Thursday, 22^nd May, 2008
Training Schedule:	9:00 am to 4:00 pm There will be a one-hour lunch break and two 20-minute coffee breaks.
Location:	Hotel Russell, 1-8 Russell Square, Bloomsbury Southwark Room
Instructors:	Neil Mason John McConnell
Pricing:	£795 Early Bird (until April 11th); £895 thereafter
Sign up:	Click here to register

An Introduction to Predictive Analytics

An Introduction to Predictive Analytics is a one day workshop covering the foundations of this innovation marketing analytics discipline. During the course of the day you will gain a thorough familiarisation with some of the key principles and methodologies of data mining and predictive analytics and learn how to apply them to common marketing problems such as:

How can I predict campaign response?
How do I segment my website visitors or customers?
How can I anticipate possible customer defections?

In this one day interactive course we will cover the following topics:

Introduction:

What is data mining and how is that different to predictive analytics?
How organisations are currently using data mining and predictive analytics across their businesses and to solve particular marketing problems

Processes and implementation

How to go about a data mining/predictive analytics project
An overview of a standard industry process (CRISP-DM)

Methods and applications

An overview of the main types of data mining and predictive analytics applications:
- Forecasting
- Segmentation
- Classification
An introduction to main methodologies such as:
- Time-series forecasting
- Regression analysis
- Decision trees (CHAID, CART and so on)
- Cluster analysis
- Neural networks
Case studies and examples of how these techniques are used and deployed in both online and offline marketing is areas such as:
- Retention modelling
- Conversion propensity modelling
- Visitor segmentation