Empirical comparison and evaluation of classifier performance for data mining in customer relationship management

In competitive consumer markets, data mining for customer relationship management faces the challenge of systematic knowledge discovery in large data streams to achieve operational, tactical and strategic competitive advantages. Methods from computational intelligence, most prominently artificial neural networks and support vector machines, compete with established statistical methods in the domain of classification tasks. As both methods allow extensive degrees of freedom in the model building process, we analyse their comparative performance and sensitivity towards data pre-processing in a real-world scenario.