Contextual Marketing Based on Customer Buying Pattern in Grocery E-Commerce: The Case of Bigbasket.com (India)

Nesya Vanessa, Arnold Japutra
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引用次数: 3

Abstract

The objectives of this research are to identify customer purchase behavior, obtain the number of customer clusters, and form customer profile in order to find situation-based customer purchase be - havior pattern. From the given data, the RFM method and K-Means clustering are used to identify the customer purchase behavior and profiles. The result of this research showed that the customer clusters are formed differently in every product category based on the RFM value and K-Means clustering. There are also differences in peak hour for each customer cluster. The best time to deliver notifica - tions and personal messages is near the peak hour. Indeed, this matter is useful to create contextual marketing and targeted advertising that is designed based on customer cluster and purchase behavior.
基于顾客购买模式的情境营销在杂货电子商务中的应用——以Bigbasket.com(印度)为例
本研究的目的是识别顾客的购买行为,获得顾客集群的数量,并形成顾客档案,以寻找基于情境的顾客购买行为模式。从给定的数据中,使用RFM方法和K-Means聚类来识别客户的购买行为和特征。研究结果表明,基于RFM值和K-Means聚类,每个产品类别的客户聚类形成不同。每个客户集群的高峰时间也存在差异。发送通知和个人信息的最佳时间是在高峰时段。事实上,这个问题对于创建基于客户群和购买行为的情境营销和目标广告是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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