Mining Consumer Knowledge from Shopping
Experience: TV Shopping Industry
Chih-Hao Wen1,
Shu-Hsien Liao2, and Shu-Fang Huang2
1Department
of Logistics Management, National Defense University, Taiwan
2Department of Management Sciences and Decision Making, Tamkang
University, Taiwan
Abstract:
TV shopping becomes far much popular in recent years. TV nowadays is almost
everywhere. People watch TV; meanwhile, they are more and more accustomed to
buy goods via TV shopping channel. Even in recession, it is thriving and has
become one of the most important consumption modes. This study uses cluster
analysis to identify the profiles of TV shopping consumers. The rules between
TV Shopping spokespersons and commodities from consumers are recognized by
using association analysis. Depicting the marketing knowledge map of
spokespersons, the best endorsement portfolio is found out to make
recommendations. By the analysis of spokespersons, period, customer profiles
and products, fourbusiness modes of TV shopping are proposed for consumers: new
product, knowledge, low price and luxury product; the related recommendations
are also provided for the industry reference.
Keywords: Consumer
knowledge, data mining, TV shopping, association rules, clustering.