Earticle

초록

영어

As the range of the customer choice becomes more diverse, the average life span of companies’ products and services is becoming shorter. Most companies are striving to maximize the revenue by understanding the customer’s needs and providing customized products and services. However, companies had to bear a significant burden, in terms of the time and cost involved in the process of determining each individual customer’s needs. Therefore, an alternative method is employed that involves grouping the customers into different categories based on certain criteria and establishing a marketing strategy tailored for each group. In this way, customer segmentation and customer clustering are performed using demographic information and behavioral information. Demographic information included sex, age, income level, and etc., while behavioral information was usually identified indirectly through customers’ purchase history and search history. However, there is a limitation regarding companies’ customer behavioral information, because the information is usually obtained through the limited data provided by a customer on a company’s website. This is because the pattern indicated when a customer accesses a particular site might not be representative of the general tendency of that customer. Therefore, in this study, rather than the pattern indicated through a particular site, a customer’s interest is identified using that customer’s access record pertaining to external news. Hence, by utilizing this method, we proposed a methodology to perform customer segmentation. In addition, by extracting the main issues through a topic analysis covering approximately 3,000 Internet news articles, the actual experiment applying customer segmentation is performed and the applicability of the proposed methodology is analyzed.

목차

Abstract
 1. 서론
 2. 관련 연구
  2.1 텍스트 마이닝 및 토픽 분석
  2.2 고객 세분화
 3. 관심 기반 고객 세분화 방법론
  3.1 연구 범위
  3.2 Module 1 : 인구통계학 정보 기반의 고객 클러스터링
  3.3 Module 2 : 뉴스 접속 기록 기반의 고객 클러스터링
  3.4 Module 3 : 포털사이트 검색 키워드 기반의 고객 클러스터링
 4. 실험 및 결과
  4.1 실험 데이터 소개
  4.2 Module 1 : 인구통계학 정보 기반의 고객 클러스터링
  4.3 Module 2 : 뉴스 접속 기록 기반의 고객클러스터링
  4.4 Module 3 : 포털사이트 검색 키워드 기반의 고객 클러스터링
  4.5 클러스터링 결과 비교
 5. 결론
 참고문헌

키워드

저자

• 현윤진 [ Yoonjin Hyun | 국민대학교 비즈니스IT전문대학원 박사과정 ]
• 김남규 [ Namgyu Kim | 국민대학교 경영정보학부 부교수 ] 교신저자
• 조윤호 [ Yoonho Cho | 국민대학교 경영학부 교수 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005