Applying data mining for online CRM marketing strategy: An empirical case of coffee shop industry in Taiwan

被引:0
|
作者
Chiang, Wen-Yu [1 ]
机构
[1] Aletheia Univ, Taipei, Taiwan
来源
BRITISH FOOD JOURNAL | 2018年 / 120卷 / 03期
关键词
Fuzzy association rules; Apriori algorithm; Coffee shops; Data mining approach; Fuzzy clustering algorithm; Online CRM marketing systems; PERFORMANCE; SERVICES;
D O I
10.1108/BFJ-02-2017-0075
中图分类号
F3 [农业经济];
学科分类号
0202 ; 020205 ; 1203 ;
摘要
Purpose The purpose of this paper is to propose a data mining approach for mining valuable markets for online customer relationship management (CRM) marketing strategy. The industry of coffee shops in Taiwan is employed as an empirical case study in this research. Design/methodology/approach Via a proposed data mining approach, the study used fuzzy clustering algorithm and Apriori algorithm to analyze customers for obtaining more marketing and purchasing knowledge of online CRM systems. Findings The research found three hard markets and one fuzzy market. Furthermore, the study discovered two association rules and two fuzzy association rules. Originality/value However, industry of coffee shops has been always a fast-growing and competitive business around the world. Thus, marketing strategy is important for this industry. The results and the proposed data mining approach of this research can be used in the industry of coffee shop or other retailers for their online CRM marketing systems.
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页码:665 / 675
页数:11
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