Mining customer knowledge for direct selling and marketing
Mining customer knowledge for direct selling and marketing
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DOI：
10.1016/j.eswa.2010.11.007
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发表时间：
2011-05
期刊：
影响因子：
--
通讯作者：
S. Liao;Yin-ju Chen;Hsin-hua Hsieh
中科院分区：
文献类型：
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作者：
S. Liao;Yin-ju Chen;Hsin-hua Hsieh
直接营销是一种有效的营销方式。与昂贵的媒体广告相比，直接营销可以为特定的消费者提供独家的产品和服务。此外，该方法还可以降低交易成本。随着虚拟商店和网上购物的兴起，沟通渠道变得多样化。因此，本研究提出网路行销在台湾直销业与化妆品市场的应用。本研究将关联规则和聚类分析作为数据挖掘的方法。通过这种方式，我们分析了消费者的心理、生活习惯和购买行为。最后，本研究发现了一些模型，包括集群消费者的购买偏好和需求，以产生不同的营销决策选择。这些研究结果有助于吸引更多的直销企业开拓更广阔的市场，为直销赚取更高的利润。
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.