Most data-mining projects involve classification for gaining insight into existing data and turning that knowledge into a predictive model. Typical classification projects include sifting profitable from unprofitable; detecting fraudulent claims; identifying repeat buyers; profiling high-value customers who are likely to churn; and flagging high-risk credit applications. CART is a state-of-the-art classification tool that, as a standalone package, can investigate any classification task and provide a robust, accurate predictive model. The software tackles the core data-mining challenges by accommodating classification for categorical variables, such as responder and non-responder, and regression for continuous variables, such as sales revenue.

In addition to delivering accuracy, CART offers three distinct advantages over other data-mining tools. First, CART is easily accessible to beginning users and does not require a high level of technical expertise to operate. CART's new, user-friendly GUI and reference manual guide users through a quick process. In addition, the default settings perform so well that many highly experienced experts do not change them. Second, CART results are extremely easy to interpret; the tree-shaped flow chart easily identifies the most important predictors. Lastly, CART costs thousands of dollars less than a data-mining suite, while handling classification projects comparably.