Customer portfolio management in e‐commerce: an analytical model for optimization

Purpose – The purpose of this paper is to present a model that retailers engaged in e‐commerce (e‐tailers) can use for determining the optimal mix of customer segments within a customer portfolio from an integrated risk and return perspective. Design/methodology/approach – Portfolio Selection Theory of Markowitz is applied to find the optimal composition of customer portfolios. The model is developed and discussed for two customer segments (relationship‐ and transaction‐oriented customers) and exemplarily applied to a data set of an e‐tailer. Findings – Portfolio Selection Theory of Markowitz is well‐suited and promising for determining an optimal customer portfolio from a risk‐return perspective. However, since customers vary from financial assets in several aspects, the results of the model have to be interpreted conscientiously and the resulting action options have to be interpreted within the context of customer relationship management (CRM). Research limitations/implications – The model proposes to carry out a sequential set of one‐period optimizations. To reduce complexity, several simplifying assumptions were made within the model regarding the characteristics of customer segments and portfolio as well as the expected risk and return. Practical implications – A current survey among German companies indicates that companies already have broad experiences in customer evaluation. However, it also turned out that evaluating customers' potential and risk simultaneously is still a major challenge. Our new approach facilitates the making of sound investment decisions into single customer relationships with respect to an overall optimal customer portfolio. Thus, a formal link to value‐based management is established. Originality/value – Using CRM for a value‐based management of customer portfolio according to a superordinated risk management objective has so far received little attention in literature. This paper's model is a new approach in customer portfolio management for e‐tailers taking customers' risk and return characteristics simultaneously and in real‐time into consideration.