Essentials of Modeling Seminar:
An Introduction for the Busy Direct Marketer

Predictive models: You won’t leave this session a statistician - but you will know what questions to ask when a model comes across your desk.

• When to use Ordinary Least Squares Regression
• Logistic regression – fundamental concepts you need to know
• When and how to use overlay data to evaluate models
• Variable reduction techniques to avoid "over-fitting"
• How and when to use CHAID
• RFM vs. Regression
• How to identify and correct for non-linearity and co-linearity
• How to determine the number of models to build
• FAQ about regression
• Case Studies: Go behind the scenes to how others use predictive models

Segmentation: If you think your customer file is made up of different demographic and behavioral segments, you’re right. You’ll learn how to identify the segments in this session.

• Factor and cluster analysis – explained in plain English
• When and how to use Principal Components Analysis
• Selecting the right number of PCA’s
• Commercial vs. custom segmentations
• How to select the right data for a custom segmentation
• Using survey data to build customer segmentation
• How to segment a customer database based on survey data results
• Case Studies – learn from the mistakes and successes of others

The economics of modeling: How to apply what you learn in this seminar to improve your bottom line.

• The basics of Decile Analyses and the “cutoff decision”
• Gains Charts demystified
• Acquisition models using Zip Code data
• How to balance front-end response models with back-end performance models

Testing: No direct marketers can afford to be without these most basic skills.

• Determining accurate sample size
• Confidence intervals – how they are calculated
• Tests of significance – what important questions they are used to address

Summary: Any questions? Now’s the time to ask them!

• Examples of modeling applications in the real world