The marketing mix modeling problem – organizations determining the right offer, right time, and right channel – is as complex as ever, as the messages increase and the frequencies multiply. Although purposefully arranged, the "mix" is lacking uniformity. Accordingly, the burden of proof is to improve response rates and revenues from campaigns. 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. The purpose of this article to introduce a simple application of regression trees (CHAID) and genetic trees (GenIQ Model©) to “idealize” the outbound customer marketing-mix information – right offer, right time, and right channel – to produce optimal response rates and revenues from campaigns. Two cases studies are discussed that show the “mixed” tree solution to the marketing-mix problem is quite promising.