An empirical study of dynamic customer relationship management

We apply the Gönül and Shi (1998) approach to the analysis of the optimal messaging and pricing policy mix by studying the past transaction patterns between a local supermarket and its consumers. We develop a dynamic customer relationship management model and investigate the relationship between customer utility and purchasing frequency by modifying the return function of the model discussed in Gönül and Shi (1998). In particular, we extend the analysis to consider a messaging and pricing policy mix, and we use a genetic algorithm in our empirical estimation. When applied to some non-seasonal products in a local supermarket, we find that our model is suitable and far superior to the one-stage model commonly used. Our dynamic model gives the optimal marketing mix strategies in different customer states and the results show that the firm could enjoy a 22% increase in profit.