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An empirical study of dynamic customer relationship management

机译:动态客户关系管理的实证研究

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We apply the Goenuel 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 Goenuel 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.
机译:我们通过研究当地一家超市与其消费者之间的过去交易模式,将Goenuel和Shi(1998)的方法用于分析最佳消息传递和定价策略组合。我们开发了一个动态的客户关系管理模型,并通过修改Goenuel和Shi(1998)中讨论的模型的收益函数来研究客户效用和购买频率之间的关系。特别是,我们将分析扩展为考虑消息传递和定价策略的组合,并在经验估计中使用遗传算法。当将其应用于本地超市中的某些非季节性产品时,我们发现我们的模型是合适的,并且远远优于常用的单阶段模型。我们的动态模型给出了在不同客户状态下的最佳营销组合策略,结果表明该公司可以享受22%的利润增长。

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