Nicolas Glady, Bart Baesens and Christophe Croux
Faculty of Economics and Management, K.U.Leuven
School of Management, University of Southampton
Abstract
Valuing customers is a central issue for any commercial activity. The customer lifetime value (CLV) is the discounted value of the future profits that this customer yields to the company. In order to compute the CLV, one needs to predict the future number of transactions a customer will make and the pro¯t of these transactions. With the Pareto/NBD model, the future number of transactions of a customer can be predicted, and the CLV is then computed as a discounted product between this number and the expected profit per transaction. Usually, the number of transactions and the future profits per transaction are estimated separately. This study proposes an alternative. We show that the dependence between the number of transactions and
their probability can be used to increase the accuracy of the prediction of the CLV. This is illustrated with a new empirical case from the retail banking sector.
Valuing customers is a central issue for any commercial activity. The customer lifetime value (CLV) is the discounted value of the future profits that this customer yields to the company. In order to compute the CLV, one needs to predict the future number of transactions a customer will make and the pro¯t of these transactions. With the Pareto/NBD model, the future number of transactions of a customer can be predicted, and the CLV is then computed as a discounted product between this number and the expected profit per transaction. Usually, the number of transactions and the future profits per transaction are estimated separately. This study proposes an alternative. We show that the dependence between the number of transactions and
their probability can be used to increase the accuracy of the prediction of the CLV. This is illustrated with a new empirical case from the retail banking sector.
Keywords: Customer lifetime value; Value; Yield; Companies; Order; Model; Product; Expected.
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