文章基本信息

标题：A CLASSIFICATION APPROACH FOR NAÏVE BAYES OF ONLINE RETAILERS
本地全文：下载
作者：Aida Mustapha ; Shazwani Mustapa ; Nurfarahim Md.Azlan 等
期刊名称：Acta Informatica Malaysia
印刷版ISSN：2521-0874
电子版ISSN：2521-0505
出版年度：2017
卷号：1
期号：1
页码：26-28
DOI：10.26480/aim.01.2017.26.28
出版社：Zibeline International
摘要：Many small online retailers and new entrants to the online retail sector are keen to practice data mining and consumer-centric marketing in their businesses yet technically lack the necessary knowledge and expertise to do so. In this article a case study of using data mining techniques in customer-centric business intelligence for an online retailer is presented. The main purpose of this analysis is to help the business better understand its customers and therefore conduct customer-centric marketing more effectively. On the basis of the Recency, Frequency, and Monetary model, customers of the business have been segmented into various meaningful groups using the classification and naïve bayes algorithm, and the main characteristics of the consumers in each segment have been clearly identify ed. Accordingly a set of recommendations is further provided to the business on consumer-centric marketing.
关键词：consumer-centric marketing; online retailer