Data defines the model by dint of genetic programming, producing the best decile table.


Building a CRM Model for Identifying Profitable Leads:
 The Genetic Contact-Profit Model

Bruce Ratner, Ph.D.

A fundamental component of a customer relationship management (CRM) strategy is determining which leads are most responsive to the initial sales call (contact), and assessing their potential revenue from future relationships (profit), namely, identifying profitable leads. For example, in the Health Care Industry where a diverse portfolio of innovative products is virtually mandated by the consumer, an effective lead generation system can be quite profitable. One wants to identify which individuals are most receptive to their salespeople and yield well-paid profits from the best-pairing of product and prospect. The lead generation system provides tactical intelligence in developing a strategy to customize the prospect-salespeople interaction, preventing the loss of profitable leads.

The purpose of this article is to introduce the new Genetic Contact-Profit (GCP) Model - an extension of the GenIQ Model© - as the desired lead generation system. The GCP GenIQ Model simultaneously addresses two important objectives facing database marketers: maximizing contact and maximizing profit. The GCP GenIQ Model, which is based on the assumption-free, nonparametric genetic paradigm inspired by Darwin's Principle of Survival of the Fittest, balances the two objectives directly yielding a single score that identifies successful leads. The GCP GenIQ Model is theoretically optimal, and easy to build and validate. I discuss two real CRM case studies to highlight the characteristics of the new method.

For more information about this article, call me at 516.791.3544, or e-mail, br@dmstat1.com.
My publisher owns the copyright of the article, about which this abstract addresses. The article will appear in my forthcoming book.
My publisher has granted me permission to discuss orally the article's content, but by no means provide an outline, a draft or proof-ready of the article.

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