文章基本信息

标题：広域の消費者購買データに基づくオリーブオイル購買の傾向分析と地域実店舗への適用
本地全文：下载
作者：坂井明日香 ; 丸橋弘明 ; 羽室行信等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2021
卷号：36
期号：1
页码：1-12
DOI：10.1527/tjsai.36-1_WI2-I
出版社：The Japanese Society for Artificial Intelligence
摘要：Recently, data-driven sales management is widely recognized and sales at the real super-market is not the exception. For designing such strategies, first of all, we have to analyze consumers’ behavior. However, such an analysis is difficult, especially for the managers of the real shops, since they only have customers’ data of their own shops. Generally, the customers buy things not only from the managers’ shops but also other shops. The goal of this research is to develop a general method to transfer sales promotion strategy, derived from analysis on wide area, to local real shop. The authors analyzed such consumers’ characteristics who buy olive oils in Kansai region. For the analysis, we used QPR(Quick Purchase Report system, developed and managed by MACROMILL, Inc). Firstly, we divided the consumers on the QPR into five clusters, according to the simultaneous buying pattern. Then, we analyzed each of the clusters and found some emerging patterns of the purchasing behavior. Observing the patterns, we designed a marketing strategy for the real shop in Hyogo prefecture belonging Kansai district. Finally, we carried out an experiment at the shop to evaluate whether the strategy promotes the sales of the olive oil or not for six weeks. The result of the experiment showed that the marketing strategy is effective in one view. At the same time, we learned many lessons from the research, especially difficulty of the evaluation at the real shop.
关键词：data mining;marketing;sales promotion;physical shop;consumer’s behavior