Mining customer knowledge for direct selling and marketing

Authors:
Shu-Hsien Liao;Yin-Ju Chen;Hsin-Hua Hsieh
Affiliations:
Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC;Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC;Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei 251, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Direct marketing is an effective marketing method. To compare with the expensive media advertisements, direct marketing could provide exclusive products and services for specific consumers. Also, this method could reduce transaction costs. The communication channel is diverse because virtual shop stores and online shopping are springing up. Therefore, this study proposes the application of Internet marketing to the direct selling industry and the cosmetics market in Taiwan. This study implements association rules and cluster analysis as approaches for data mining. By doing so, we analyze consumer adumbration, lifestyle habits and purchasing behavior. Finally, this study finds some models including cluster consumer purchase preference and demand in order to generate different marketing alternatives for decisions. These research results can help attract more direct marketing firms to open up broader markets and earn higher profits for direct selling.