For a successful business, engaging in an effective campaign is a key task for marketers. Most previous studies used various mathematical models to segment customers without considering the correlation between customer segmentation and a campaign. This work presents a conceptual model by studying the significant campaign-dependent variables of customer targeting in customer segmentation context. In this way, the processes of customer segmentation and targeting thus can be linked and solved together. The outcomes of customer segmentation of this study could be more meaningful and relevant for marketers. This investigation applies a customer life time value (LTV) model to assess the fitness between targeted customer groups and marketing strategies. To integrate customer segmentation and customer targeting, this work uses the genetic algorithm (GA) to determine the optimized marketing strategy. Later, we suggest using C&RT (Classification and Regression Tree) in SPSS PASW Modeler as the replacement to Genetic Algorithm technique to accomplish these results. We also suggest using LOSSYCOUNTING and Counting Bloom Filter to dynamically design the right and up-to-date offer to the right customer.
翻译:对于成功的企业来说,参与有效的运动是市场营销者的一项关键任务。大多数以往的研究在不考虑客户分割和运动之间相互关系的情况下,使用各种数学模型将客户分成部分,而没有考虑客户分割和运动之间的联系。这项工作通过研究客户分割背景下取决于运动的重要变量,提出了一个概念模型。这样,客户分割和选择目标的过程就可以相互连接和解决。本研究的客户分割结果对于市场营销者可能更有意义和相关性。本调查采用客户寿命值模型来评估目标客户群体和营销战略之间的适合性。为了将客户分割和客户选择目标结合起来,这项工作利用基因算法(GA)来确定优化的营销战略。后来,我们建议使用SPSS PASW模型中的C&RT(分类和回归树)来替代遗传阿尔戈蒂姆技术,以取得这些结果。我们还建议使用LOSSYSYCOUNting and Counting Bloom 过滤器来动态地设计对正确的客户提供的权利和最新服务。我们建议使用LSYSYCOUNTV。