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Open Market Sales Trend Analysis System Using Online Shopping Mall Data

온라인 쇼핑몰 데이터를 활용한 판매동향 분석 시스템

  • 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)
  • Received : 2019.09.20
  • Accepted : 2019.12.11
  • Published : 2019.12.31

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.

인터넷의 발전으로 온라인 쇼핑이 활성화 되면서 소비자들의 구매 형태가 기존의 대면 구매방식에서 온라인 구매방식으로 변하고 있다. 이에 수많은 판매자가 쇼핑몰로 유입되었고, 판매자들 간의 경쟁이 매우 치열한 실정이다. 따라서 쇼핑몰 내 판매자들은 소비자의 구매 패턴 및 제품 판매동향을 분석하여 합리적인 마케팅 전략을 세울 필요가 있다. 본 논문에서는 오픈 쇼핑몰에서 판매업자가 동일 제품을 판매하는 경쟁사의 제품 가격, 평점, 판매수량을 시간대별로 분석하여 소비자의 구매 패턴을 파악했다. 또한 수집된 정보들을 차트로 가시화하여 자사와 경쟁사의 판매동향을 쉽게 비교할 수 있도록 하였다. 위 시스템을 사용하면 분석된 구매패턴을 통해 판매수량을 예측할 수 있고 판매동향을 파악하여 상품의 합리적인 가격 선정이 가능하다.

Keywords

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