论文标题
将正确的报价与电信行业的合适客户联系起来
Dynamically Tie the Right Offer to the Right Customer in Telecommunications Industry
论文作者
论文摘要
对于成功的业务而言，从事有效的活动是营销人员的关键任务。以前的大多数研究都使用各种数学模型来细分客户，而无需考虑客户细分与广告系列之间的相关性。这项工作通过研究客户细分环境中客户定位的重要依赖于广告系列的变量来提出概念模型。这样，可以将客户细分和定位的过程链接和解决。这项研究的客户细分结果可能对营销人员更有意义和相关。这项调查应用了客户寿命价值（LTV）模型，以评估目标客户群和营销策略之间的适应性。为了整合客户细分和客户目标，本工作使用遗传算法（GA）来确定优化的营销策略。后来，我们建议在SPSS PASW建模器中使用C＆RT（分类和回归树）作为替代遗传算法技术来完成这些结果。我们还建议使用LossyCounting和Counting Bloom过滤器，以动态地设计向正确客户的正确和最新优惠。
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.
