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Customer-oriented catalog segmentation: Effective solution approaches

机译:面向客户的目录细分:有效的解决方案方法

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We consider in this paper the customer-oriented catalog segmentation problem that consists of designing K catalogs, each of size r products that maximize the number of covered customers. A customer is covered if he/she has interest in at least the specified minimum number of products in one of the catalogs. The problem addresses the crucial issue of the design of the actual contents of the catalogs that serves as a back-end to catalog production for the purpose of more focused design of catalogs as a targeted marketing tool. We developed two algorithms to solve the problem. Results of an extensive computational study using real and synthetic data sets show that one of the proposed algorithms outperforms the state-of-the-art algorithm found in the literature in terms of customer coverage, resulting potentially in significant increase in organization profit. In the spirit of the guidance role that a Decision Support System (DSS) should play by recommending alternative, satisfactory solutions to the decision maker, the prototype of a DSS integrating all three algorithms is presented to provide the decision maker with an easy-to-use, yet powerful tool to examine various catalog design options and their implications on the contents of the catalogs and the clusters of covered customers.
机译:我们在本文中考虑了面向客户的目录细分问题,该问题包括设计K个目录,每个目录的大小为r的产品可以最大程度地覆盖所覆盖的客户数量。如果客户对至少一个目录中指定的最小数量的产品感兴趣,则覆盖该客户。该问题解决了目录实际内容设计的关键问题,该目录充当目录生产的后端,目的是更集中地设计目录作为目标营销工具。我们开发了两种算法来解决该问题。使用真实和合成数据集进行的广泛计算研究的结果表明,就客户覆盖率而言,所提出的算法之一优于文献中的最新算法,从而有可能显着提高组织利润。本着决策支持系统(DSS)通过向决策者推荐其他令人满意的解决方案应发挥的指导作用的精神,提出了集成了这三种算法的DSS原型,以为决策者提供易于使用的解决方案使用功能强大的工具来检查各种目录设计选项及其对目录内容和涵盖客户群的影响。

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