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

Marketing Optimization: Regression-tree Approach for Outbound Campaigns
Bruce Ratner, Ph.D.

The marketing optimization problem – maximizing outbound-campaign outcomes by determining the best marketing mix of the key factors, namely, communication, channel, strategy, and timing, for an individual customer – is as complex as ever: as the communications increase, the frequencies multiply, and the timings of executing the campaigns heighten. The solution provides the optimal marketing ROI by determining the best offers for the individual customers with the best channel capacities and contact strategies. CRM campaign management applications, which are plentiful, are good at improving campaign efficiency and execution, but they are limited in determining the ideal marketing mix of the key factors. The purpose of this article to introduce a simple application of the everready statistical regression tree CHAID, and the newbie genetic regression tree GenIQ Model© [5, 6] to idealize the outbound campaigns – affecting optimal marketing ROI, and concurrently response rates. Two cases studies are discussed that show the newer GenIQ Model tree solution to the marketing optimization problem is quite promising.

For more information about this article, call me at 516.791.3544, or e-mail,
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.

Sign-up for a free GenIQ webcast: Click here.