• 제목/요약/키워드: customer classification

검색결과 285건 처리시간 0.021초

Using GAs to Support Feature Weighting and Instance Selection in CBR for CRM

  • 안현철;김경재;한인구
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2005년도 공동추계학술대회
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    • pp.516-525
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    • 2005
  • Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

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고객의 이탈 가능성과 LTV를 이용한 고객등급화 모형개발에 관한 연구 (A Model for Effective Customer Classification Using LTV and Churn Probability : Application of Holistic Profit Method)

  • 이훈영;양주환;류치훈
    • 지능정보연구
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    • 제12권4호
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    • pp.109-126
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    • 2006
  • 성공적인 고객관계관리(CRM : customer relationship management)를 수행하기 위해서는 효과적인 고객 등급화가 필요하다. 일반적으로 고객등급화는 고객별로 LTV를 산정한 다음 일정한 비율로 고객을 분류하여 등급을 정하는 방법이 사용되어 왔다. 그러나 이러한 방법은 등급간의 이질성을 명확하게 반영하지 못하기 때문에 적지 않은 문제점을 내포하고 있다. 본 논문에서는 Holistic Profit을 이용해서 고객을 등급화 하는 방법을 제시하고, A 생명보험회사의 고객자료을 이용해서 이를 검증하였다. Holistic Profit은 신용대출 승인정책에서 승인임계점수(Cutoff Point) 책정에 활용되고 있는 방법들 중의 하나이다. 요약하면, 본 논문의 목적은 Holistic Profit을 활용하여 보다 효과적이고 과학적인 방법으로 고객 등급화 하는 방법의 개발과 검증에 있다. 본 논문에서 제시된 방법을 사용해서 고객을 등급화 함으로써 기업은 보다 효과적인 고객관계관리(CRM)와 마케팅 활동을 수행할 수 있을 것으로 기대된다.

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고객 클러스터링 기법을 활용한 할당규칙의 시뮬레이션 연구 (A Simulation Study on Dispatching Rule Using Customer Clustering Method)

  • 양광모;박재현;강경식
    • 산업경영시스템학회지
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    • 제29권1호
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    • pp.26-33
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    • 2006
  • The potential needs as well as visible needs of customer should be considered in order to research and analyze of the customer data. The methods to analyze customer data is classified into customer segmentation, clustering analysis model, forecasting customer response probability model, analysis of the customer break rate model and new customer analysis model by the purpose. In this study, we developed the CW-CLV (Correlation Weight Customer Lifetime Value)method that used AHP(Analytic Hierarchy Process)rule for enhance the reliability of customer data and quantitative analysis of the customer segmentation, based on CLV(Customer Lifetime Value). We suggest to new variables and methodology from determined CW-CLV coefficients, because all of companies respect to the diversified customers classification and complexity of consumers needs. Finally, we unfolded any company's scheduling added new methodology using simulation and leaded conclusion about the new methodology.

카노모델에서 품질요소 분류를 위한 퍼지기법 연구 (On Fuzzy Methods to Classify Quality Attributes in Kano Model)

  • 김성준
    • 한국지능시스템학회논문지
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    • 제26권6호
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    • pp.439-444
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    • 2016
  • 품질에 대한 정의는 계속 진화하고 있다. 최근 들어서는 고객관점의 품질을 중시하며 고객의 잠재적 요구를 얼마나 잘 충족시키고 있는가에 대한 관심이 커지고 있다. 카노가 제안한 2차원적 품질의 개념은 고객만족에 중요한 품질속성을 발견하는 데 유용한 프레임워크를 제공하며 제품 및 서비스 개발을 위해 널리 적용되고 있다. 카노모델은 제품 및 서비스 품질요소를 매력적, 일원적, 필수적, 무관심, 그리고 역 품질요소로 구분한다. 그 중 매력적 요소를 발견하는 것은 고객만족의 효과적인 달성에 중요하다. 하지만 카노가 제시한 분류방법은 고객의 애매하고 복잡한 생각을 다루는 데 한계가 있다. 고객응답에는 그 자체로 불확실성과 불완전성이 포함되기 때문이다. 이를 극복하기 위해 본 논문은 퍼지기법을 이용한 품질요소 분류절차를 제시한다. 수치실험 결과, 제안된 방법은 고객의 다양한 반응을 수용하는 데 효과적이며 잠재적 요구를 식별하는 데에도 유용한 것으로 나타났다.

전자메일 기반의 고객관계관리(CRM) 시스템 개발에 관한 연구 (A Study on the Development of Electronic Mail-based Customer Relationship Management System)

  • 김승욱;양광민
    • Journal of Information Technology Applications and Management
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    • 제10권4호
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    • pp.51-63
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    • 2003
  • This study designs and implements a new approach to the classification of e-mail requests from customer based on machine learning techniques. The work on building an electronic mall classifier can be cast into the framework of text classification, since an e-mail is a viewed as a document, and judgement of interest is viewed as a class level given to the e-mail document. It is also implemented an e-mall based automated response system that integrate with Call Center in a practical use.

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영 캐주얼 패션브랜드 웹사이트를 활용한 마케팅 커뮤니케이션 전략 (A Study on the Internet Marketing Communication Strategy of Young Casual Fashion Brand through the Website Analysis)

  • 이민경;나수임
    • 패션비즈니스
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    • 제12권4호
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    • pp.46-55
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    • 2008
  • The purpose of this study is to provide the effective internet marketing communication strategy as marketing tools by analyzing the web sites of young casual fashion brands. We've selected 19 young casual fashion brands in 3 department stores and made the classification standard - advertising, promotion, public relation(PR), customer management - and analysed the young casual fashion brands according to 4 classification standard on the web sites. As a result of study, it is found that 19 young casual brands' web sites put an emphasis on activity of customer management and promotion in general. However, they did not conduct the PR and advertising actively compared with other parts. Especially, the promotion strategy occupies more parts than any other parts through the variety of membership card's services. Also they are sending e-mails or providing 1:1(FAQ/Q&A) board to the members as a customer management to be able to help to communicate with customer through the web site.

Dynamic Text Categorizing Method using Text Mining and Association Rule

  • Kim, Young-Wook;Kim, Ki-Hyun;Lee, Hong-Chul
    • 한국컴퓨터정보학회논문지
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    • 제23권10호
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    • pp.103-109
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    • 2018
  • In this paper, we propose a dynamic document classification method which breaks away from existing document classification method with artificial categorization rules focusing on suppliers and has changing categorization rules according to users' needs or social trends. The core of this dynamic document classification method lies in the fact that it creates classification criteria real-time by using topic modeling techniques without standardized category rules, which does not force users to use unnecessary frames. In addition, it can also search the details through the relevance analysis by calculating the relationship between the words that is difficult to grasp by word frequency alone. Rather than for logical and systematic documents, this method proposed can be used more effectively for situation analysis and retrieving information of unstructured data which do not fit the category of existing classification such as VOC (Voice Of Customer), SNS and customer reviews of Internet shopping malls and it can react to users' needs flexibly. In addition, it has no process of selecting the classification rules by the suppliers and in case there is a misclassification, it requires no manual work, which reduces unnecessary workload.

외식프랜차이즈 시스템하의 동인별 고객만족도에 관한 연구 (A Study on the franchisee satisfaction in the foodservice franchise industry)

  • 홍기운;김형준
    • 한국조리학회지
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    • 제6권3호
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    • pp.119-147
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    • 2000
  • This Study is performed to research a customer satisfaction to a Franchisee on the food franchise industry. In future, the food industry will be complicated and various. So customer needs also will be complicated. Consequently. a study of customer satisfaction will be researched continuously for corresponding an industrial transfiguration and a customer variety. The result of this study, a Franchisee satisfaction on the food franchise industry is evaluated below the average. This result can be happened by the scale of food franchise industry. However actually it has caused by the lack of Franchisee management mind, the capability of head office, and the lack of competitive power. The mind of service for customer, hygiene and cleanness mind, and the lack of marketing strategies and strategic management can not be satisfied of customer. Also customer value creation can not be made. So the education training and marketing strategies for Franchisee on the food franchise industry have to be requested. And a continuous study for customer satisfaction that correspond with the characteristics of industrial classification be raised.

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사전 세분화를 통한 고객 분류모형의 효과성 제고에 관한 연구 (Improving the Effectiveness of Customer Classification Models: A Pre-segmentation Approach)

  • 장남식
    • 경영정보학연구
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    • 제7권2호
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    • pp.23-40
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    • 2005
  • 시장에서의 경쟁이 점차 심화되고 서비스나 상품에 대한 고객들의 요구와 기대치가 증가함에 따라 기업들에 있어 과학적인 데이터 분석에 근거한 경영전략 수립 및 실행의 필요성이 어느 때보다 크게 강조되고 있다. 그러나 인적자원과 및 자금 등을 포함한 가용자원은 한정적이기 때문에 이들 자원을 얼마나 효율적으로 사용하여 효과적인 결과를 획득하는가가 기업 성패를 좌우하는 주요 지표가 되고있다. 본 연구에서는 선택과 집중적 자원 배분이라는 이슈에 초점을 맞춰 사전 세분화를 통해 선정된 고객 군만을 대상으로 고객의 특성을 파악하고 관리하는 방안이 전체 고객을 대상으로 하는 것보다 보다 의미가 있다는 것을 실제 현업데이터를 통해 검증하고자 하였다. 이를 위해 카드사, 이동통신사, 보험사의 고객 인적데이터 및 거래데이터를 수집하였고, 통계분석과 현업전문가의 의견을 수렴해 고객 세분화를 수행하였으며, 각 세분 군별로 데이터마이닝의 의사결정나무 기법을 이용해 해지모형을 구축하여 전체 고객을 대상으로 한 모형과 정분류율과 규칙의 간결성 측면에서 비교 평가하였다. 결과적으로 세분 군별 해지모형이 전체 고객대상 모형에 비해 정분류율은 높거나 비슷한 수준을 유지하면서 보다 간결하고 의미있는 규칙을 제공하였다.

A methodology for Internet Customer segmentation using Decision Trees

  • Cho, Y.B.;Kim, S.H.
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2003년도 춘계학술대회
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    • pp.206-213
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    • 2003
  • Application of existing decision tree algorithms for Internet retail customer classification is apt to construct a bushy tree due to imprecise source data. Even excessive analysis may not guarantee the effectiveness of the business although the results are derived from fully detailed segments. Thus, it is necessary to determine the appropriate number of segments with a certain level of abstraction. In this study, we developed a stopping rule that considers the total amount of information gained while generating a rule tree. In addition to forwarding from root to intermediate nodes with a certain level of abstraction, the decision tree is investigated by the backtracking pruning method with misclassification loss information.

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