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http://dx.doi.org/10.20465/KIOTS.2019.5.2.007

Open Market Sales Trend Analysis System Using Online Shopping Mall Data  

Cha, Seung-yeon (Department of Computer Engineering, Mokpo National University)
Kim, Kang-ryeol (Department of Computer Engineering, Mokpo National University)
Shrestha, Labina (Department of Computer Engineering, Mokpo National University)
Kim, Yeong-ju (Department of Computer Engineering, Mokpo National University)
Choi, Jongmyung (Department of Computer Engineering, Mokpo National University)
Publication Information
Journal of Internet of Things and Convergence / v.5, no.2, 2019 , pp. 7-13 More about this Journal
Abstract
As online shopping is activated by the development of the Internet, consumers' purchase form is changing from the traditional face-to-face purchase method to online purchase method. Many sellers have flowed into shopping malls, and competition among sellers is very intense. Therefore, sellers in shopping malls need to establish rational marketing strategies by analyzing consumer purchase patterns and product sales trends. In this paper, we analyzed the purchase price of consumers by analyzing the product price, rating, and sales quantity of competitors who sell the same product in open shopping malls by time zone. In addition, the collected information was visualized in a chart so that the company's and competitors' sales trends could be easily compared. Using the above system, it is possible to predict the sales volume through the analyzed purchasing pattern and to select the reasonable price of the product by grasping the sales trend.
Keywords
Big Data; Online Shopping; Marketing Strategy; Sales Trend;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
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