A mixture model to estimate customer value for e‐services

Companies have changed their focus from product oriented within marketing (1960s) to demand oriented within quality improvement (1980s) and, today, to an emphasis on customer service, customer loyalty, and customer profitability. Although the significance of customer‐centric services is well established, much of the research that has investigated the effect of customer lifetime value (CLV) has focused on the lifetime value of existing customers only. The purpose of this paper is to devise a novel customer value model (the CV model) to predict internet‐based customers' value by utilizing historical financial data to predict future value.

This research utilizes the concept of operation research, which deploys scientific methods to solve problems and assists in generating strategies in terms of model construction. The authors construct a prediction model for short‐term CV that is also a type of deterministic model and define e‐services as the coverage of free or charged services over the internet environment.

The simulated results reveal that, over the long‐term, CV decreases as the predictive time moves away from the present because of deviations in perception and expectation. The new CV model complements the existing CLV model by addressing CV from a different perspective and provides clues to CV for e‐service industries.

The proposed CV model and the CLV model both come from the customer perspective, but CLV measures CLV without prediction while the CV model provides an avenue by which to consider customer and enterprise perspective simultaneously. Thus, the CV model not only complements the CLV but also assists enterprises in identifying CV and generating superior benefits.

The proposed model makes three contributions: it constructs an equation to measure CV for internet‐based services; it considers the customer and enterprise perspectives simultaneously; and it observes changes in the CV of any specific internet user.