The purpose of this paper is to propose a method to help firms assess lifetime profitability of customers whose buying behaviors are characterized by purchasing cycles, which are determined by both intrinsic purchasing cycles and cumulative effects of firms’ marketing solicitations.
This paper first proposes a probability model to predict customers’ responses to firms’ marketing solicitations in which a customer’s inter-purchase times are assumed to follow a Poisson distribution, whose parameters vary across customers and follow a gamma distribution. The paper then proposes a customer profitability scoring model that uses customers’ responses as an input to assess their lifetime profitability at a given point of time.
The paper illustrates the proposed method using individual-level purchasing data of 529 customers from a catalog firm. The paper shows that the proposed model outperforms the benchmark model in terms of both explaining and predicting customers’ purchases. The paper also demonstrates significant profit consequences to the firm if incorrect methods are used instead of the proposed method.
The proposed method can help firms select or eliminate customers based on their lifetime profitability so that firms can focus their marketing efforts in a more targeted manner to increase total profits.
The proposed Gamma-Poisson probability model and the profitability scoring method are easy to implement due to the attractive conjugacy property. It is valuable for firms’ customer relationship management applications from the standpoint of making customer selection and inventory management decisions.
Zhang, Q. and Seetharaman, P. (2018), "Assessing lifetime profitability of customers with purchasing cycles", Marketing Intelligence & Planning, Vol. 36 No. 2, pp. 276-289. https://doi.org/10.1108/MIP-03-2017-0059Download as .RIS
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