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.