As calculus is used to derive statistical regression models, genetic programming is used to evolve the GenIQ model. Thus, the webcast for a Gentle Introduction of Genetic Programming(GP) provides a model builder with a comfort level needed to accept the GenIQ model building process.

The GenIQ Model© is a machine learning alternative model to the statistical ordinary least squares and logistic regression models. GenIQ lets the data define the model – automatically data mines for new variables, performs variable selection, and then specifies the model equation – so as to "optimize the decile table," to fill the upper deciles with as much profit/many responses as possible. Put differently, GenIQ seeks to maximize cum lift, a measure of model predictiveness of identifying the upper performing individuals often displayed in a decile table. GenIQ produces models that outdo statistical models, and is a different model: unsuspected equation, ungainly interpretation, and easy implementation.GenIQ requires no programming, produces models that outdo statistical models, and is a different model: unsuspected equation, ungainly interpretation, and easy implementation.