Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
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A Sequential Pattern Analysis for Dynamic Discovery of Customers' Preference

고객의 동적 선호 탐색을 위한 순차패턴 분석: (주)더페이스샵 사례

  • 송기룡 ((주)더페이스샵) ;
  • 노성호 (한국산업기술대학교 e-비즈니스학과) ;
  • 이재광 (한국산업기술대학교 e-비즈니스학과) ;
  • 최일영 (경희대학교 경영대학 e-비즈니스) ;
  • 김재경 (경희대학교 경영대학)
  • Published : 2008.08.31
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Abstract

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

고객의 니즈가 시시각각 변화하는 경영환경에서 획일화된 매장관리 방법으로 매장의 수익성을 증대시키기에는 한계가 있다. 따라서 고객의 선호 변화를 예측하여 각 매장에 적절한 상품을 추천할 필요가 있다. 본 연구에서는 판매 데이터 분석을 통해 시간 순서를 고려한 상품 추천 및 매장관리 방법을 제안한다. 즉 자기조직화지도(Self Organizing Map) 알고리즘을 이용하여 매장의 판매 프로파일을 군집화하고, 매장 궤적의 예측을 통해 목표 매장을 관리하는 방법을 제시한다. 본 연구의 방법론을 검증하기 위해 (주)더페이스샵 판매데이터를 적용하여 평가하였으며, 평가결과 제시한 방법론은 화장품처럼 유행에 민감하고 라이프사이클이 짧은 특징을 지닌 상품을 판매하는 매장의 수익성 증대에 기여할 수 있을 것으로 기대된다.

Keywords

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