Estimating campaign benefits and modeling lift
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A Data Mining Approach for Retailing Bank Customer Attrition Analysis
Applied Intelligence
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In this paper, we present a data mining approach for analyzing retailing bank customer attrition. We discuss the challenging issues such as highly skewed data, time series data unrolling, leaker field detection etc, and the procedure of a data mining project for the attrition analysis for retailing bank. We explain the advantages of lift as a proper measure for attrition analysis and compare the lift of data mining models of decision tree, boosted na茂ve Bayesian network, selective Bayesian network, neural network and the ensemble of classifiers of the above methods. Some interesting findings are reported. Our research work demonstrates the effectiveness and efficiency of data mining in attrition analysis for retailing bank.