Mining Consumer Knowledge from Shopping Experience: TV Shopping Industry
Journal: The International Arab Journal of Information Technology (Vol.15, No. 6)Publication Date: 2018-11-01
Authors : Chih-Hao Wen; Shu-Hsien Liao; Shu-Fang Huang;
Page : 1043-1051
Keywords : Consumer knowledge; data mining; TV shopping; association rules; clustering;
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
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