Retail

"CART is an important statistical analysis tool that we use to segment our databases and predict risk factors for the Sears Card. The advantage of the decision tree format is that our results are easy to interpret; especially with CART, we are able to see a great deal of detail about each of the nodes, such as the node's misclassification costs, the count of data assigned to that node, and a display of the surrogate values substituted for the node."

Steven Li, Senior Manager, Risk Technology, Sears, Roebuck and Co

Telecommunications

"When we purchased CART, it was the only comprehensive classification and segmentation software available that could handle the large data sets we use for credit card risk management. In addition, CART provides us with a great deal of flexibility by allowing us, for example, to specify a higher penalty for misclassifying a certain data value."

Feng Xu, Senior Manager, AT&T Universal Card Services

Banking/Finance

"CART offers two distinctive advantages that other database segmentation tools do not. First, it allows the analyst to identify the smallest target segment possible, such as ten out of tens of thousands, with exceptional precision. In addition, CART allows us to specify a higher penalty for misclassifying a potentially poor prospect than for rejecting a good one; this makes us more confident that, for products with very thin margins, our segmentation models avoid prospects who would likely be non-profitable. CART is an invaluable data mining and modeling tool for Fleet Financial Group."

Terence Mak, VP, Lead Analytic Consultant, Fleet Financial Group

Government

"I use CART to provide Canadian meteorologists with dynamic statistical models for predicting lake effect snowfall, ozone levels and other weather issues that affect Canada. The optimal tree models I create in CART have proven their accuracy many times over when the tree is used with independent data."

William Burrows, Meteorological Research Scientist, Atmospheric Environment Service

"As a statistician in the Naval environment, I have been involved in the field of data mining for the past four years. Classification trees have become one of the primary tools with which I extract useful information from large data bases. I have used various different classification tree software, and have found CART to be the superior product. What I find particularly useful are the following:

• The colour codes of the nodes which one can use to pick the most important branches (or rules).
• The relative cost vs number of nodes graph which I always use to select the "least complicated" with "low" relative cost.
• The Gains chart provides a good graphical view for assessing tree performance.

Dr. Martin Kidd, IMT, South Africa

Marketing

"PreVision Marketing's clients include Fortune 500 companies from telecommunications, automotive, retail and packaged goods industries. We apply our database marketing and analysis expertise to turn our clients' usual wealth of customer information into beneficial marketing information and customer relationship programs. At PreVision, this typically includes developing models of customer and prospective customer behavior. CART's recursive partitioning abilities give us a proven statistical method for generating marketing models in an easy-to-understand decision tree format. This format is accessible to all of our clients, even those with limited statistical backgrounds, and the clarity of the decision tree display gives our clients added confidence in the validity and utility of the models we create."

Marsha Wilcox, Ed.D., Vice President, PreVision Marketing

Industrial

"At Chevron, we conduct a lot of exploratory work for oil well drilling. Instead of taking many expensive core samples, we can use stet monitoring tools to characterize geographic areas; data capture generates small data sets with variables that are complex and interrelated rather than independent. CART, with its v-fold cross-validation capability, is our tool of choice for analyzing these small, complex data sets."

Wesley Johnston, Chevron Information Technology Co.

Academic

"As a research scientist in both academic and professional environments, I work with databases too large and complex to process manually. CART, unlike multiple linear programming and other methods that are constrained by functional forms, shows me truer characterizations of interrelationships between the data. CART is also a robust program that can support a diverse set of applications ranging, in my case, from food security analyses to pattern recognition and remote sensing problems."

Eric Weiss, Ph.D., Consultant; Arid Lands Resource Sciences, University of Arizona