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Mining customer knowledge to implement online shopping and home delivery for hypermarkets

机译:挖掘客户知识以为大型超市实施在线购物和送货上门

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摘要

With advances in modern technology, the Internet population has increased year by year globally. For young customers who consider convenience and speed as prerequisites, online shopping has become a new type of consumption. In addition, business-to-customer (B2C) home delivery markets have taken shape gradually, because virtual stores have risen and developed, e.g. mail-order, TV marketing, e-commerce. To integrate the above statements, this study combines online shopping and home delivery, and attempts to use association rules to determine unknown bundling of fresh products and non-fresh products in a hypermarket. Customers are then divided up in clusters by clustering analysis, and the catalog is design based on each of the cluster's consumption preferences. By this method, to increase the catalogue's attraction to customers, hypermarkets are offered an online shopping and home delivery business model for sales services and propositions. With such a model, we can expect to attract more customers open up more broad markets, and earn the higher profits for hypermarkets.
机译:随着现代技术的进步,全球互联网人口逐年增加。对于以便利和速度为先决条件的年轻客户,在线购物已成为一种新型的消费方式。此外,由于虚拟商店的兴起和发展,例如企业对客户(B2C)的送货上门市场已逐渐形成。邮购,电视营销,电子商务。为了整合以上陈述,本研究结合了在线购物和送货上门,并尝试使用关联规则来确定大型超市中新鲜产品和非新鲜产品的未知捆绑。然后,通过聚类分析将客户划分为多个集群,然后根据每个集群的消费偏好来设计目录。通过这种方法,为了增加目录对客户的吸引力,大型超市提供了用于销售服务和主张的在线购物和送货上门业务模型。通过这种模型,我们可以期望吸引更多的客户开放更广阔的市场,并为大卖场赚取更高的利润。

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