Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A study on proposing a method for grouping R, F, and M in RFM model

RFM에서 등급부여 방법에 관한 연구

  • 류귀열 (서경대학교 컴퓨터과학과) ;
  • 문영수 (한국과학기술정보연구원)
  • Received : 2013.01.21
  • Accepted : 2013.02.13
  • Published : 2013.03.31
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Abstract

The object of study is to propose a method for grouping R, F, and M in RFM model. Our model uses 6 levels using standard normal distribution. First level is upper 2.5% and second level next 13.5%, third level next 34%, fourth level next 34%, fifth level next 13.5%, sixth level next 2.5%. Values are symmetric and limits are clear. We compare proposed model with traditional 5 level model and 10 level model using NDSL data of KISTI. Proposed model divides most clearly the distribution of the RFM function for all cases of weights, because it uses the distribution of customers. Comparison studies of our model with grouping using cluster analysis and studies on weights of RFM model are needed.

본 논문은 RFM (recency frequency monetary) 모델에서 등급을 매기는 방법을 정규분포를 이용하여 6등급모델을 제안하고 NDSL (national discovery for science leaders) 자료를 이용하여 현재 많이 사용되고 있는 5등급모델과 10등급모델을 비교하였다. 제안 모델이 5등급모델과 10등급모델에 비해 고객그룹들을 쉽게 세분화할 수 있다는 사실을 알 수 있었다. 제안된 모델은 대칭적으로 등급을 부여하고, 고객분포를 이용하기 때문에 고객특성을 잘 반영함으로써 경계값들이 명확하게 구분되는 특징을 가지고 있다. 또한 등급 값을 보면 쉽게 어느 위치에 속하고 있는 지 알 수 있으며, 고객세분화 후 고객의 RFM값들의 확인으로 고객의 특성을 쉽게 알 수 있는 장점이 있다. 향후 군집분석 등의 통계적 등급부여 방법들과 비교연구와 가중치 부여 방법에 관한 연구가 필요하다.

Keywords

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