• Proceedings of the Korea Database Society Conference
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• 2001.06a
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• pp.172-182
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• 2001

재구매 가능성이 많은 고객을 세분화 하여 재구매 가능성이 많은 고객과, 그 고객의 정보를 제공함으로써 영업의 효율성을 도모하고자 함. 차종별 가망고객을 분석하여 New Car가 개발 되었을 때 차별적인 마케팅 활동을 수행하고자 함. 기존과 차별화 된 마케팅 전략을 적용하기 위해 대상자 선정하는 작업을 데이터 마이닝 기법을 적용함. (중략)

• Information Systems Review
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• v.9 no.3
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• pp.99-132
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• 2007

As customer management rises by important issue in electronic commerce, virtue study about CRM have proceeded much. However, because existent researches were positive researches of most statistical base, There are some limitation that does not show dynamic change with CRM flow by flowing of time, and can not forecast propriety and future result about CRM strategy. Therefore, in order to overcome existent limitation on these CRM study, this study designed dynamic model which draws factors that compose CRM strategy of on-line shopping mall, and do based on technique in system dynamics so that can analyze dynamic change between these factors. Concretely, atomized customer focuses in the on-line shopping mall and does based on Permission marketing theory, and applied CRM of different level to atomized customers and know change of customer satisfaction measurement and discomfort degree accordingly. According to the result of Simulation practice, situation that achieve CRM strategy of different level by atomize customer more increase the customer satisfaction than situation that is not so. Dynamic pattern that presented in this study is expected that can verify validity about CRM achievement strategy of different level at each CRM point of contact & how Internet enterprise including on-line shopping mall is establishing CRM strategy reasonably.

• Korean Business Review
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• v.17
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• pp.137-151
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• 2004

Wrap accounts are customized financial services for which investment companies and stock brokers manage investors assets based on their preferences. The success of wrap accounts depend upon the accurate understanding of investment risk propensity and the proper designing of financial portfolio. To this end investment companies should accurately measure investors investment risk propensity with calibrated measures. There, unfortunately, exist few highly calibrated measures of investment risk propensity. Therefore the practices of marketing strategies and customer management often turn out to be less effective and fragile to competition. The purposes of this present study aim to understand the investment risk propensity of wrap accounts customers, to help classify the customers based on the degree of the investment risk propensity, and to implement relevant marketing strategies for different groups of customers. Based on previous studies, two hypotheses were delineated and verified. The findings of the study should help differentiate prospective customers into unique and accessible segments for further targeting and positioning wrap account markets.

• Korea Information Processing Society Review
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• v.8 no.6
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• pp.38-43
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• 2001

본 고에서는 인터넷 쇼핑몰 기업들 중 신생기업들을 대상으로 이들의 기업환경에 맞는 데이터베이스 마케팅 방법론을 제시하고자 한다. 그러므로 데이터마이닝(Data Mining)을 이용하여 기존고객을 세분화한 다음 고객 개개인의 특성에 맞는 마케팅을 프로모션(Promotion)하고 신규고객을 획득할 때는 신규고객의 특성을 미리 예측하여 고객의 평생가치(LTV:Life Value)를 촉진하여 기업과 고객과의 관계성을 높이고, 기업은 안정된 고객층으로부터 수익을 창출하고, 기업으로부터 더 많은 혜택을 받게 하는 것에 대하여 연구하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.530-538
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• 2003

Recently the needs for keeping existing customers is increasing in the field of marketing. So, the customers needs to be classified by groups and the differentiated responses to the specified customer groups are demanded. In this paper, we implemented a system that classifies the customer groups using the neural network, and classified the purchasing patterns among customer groups. Empirically examining the association rules between two groups, we could find out that similar rules exist between them. So, it is important that customers should be classified into the excellent customer group and the general group for the decision making of marketing. This paper shows that the efficiency of the differentiated marketing can be maximized by raising the correctness of the expectation in the classification of customer groups.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.11a
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• pp.21-21
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• 2001

• Proceedings of the Korea Database Society Conference
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• 2002.10a
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• pp.511-528
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• 2002

현 CRM(Customer Relationship Management)의 솔루션은 기업 중심의 고객관리, 분석, 협업의 기능으로 그룹화되어 시상을 형성하고 있다. 하지만 다양한 고객의 요구 사항을 충족하기 위해서는 어느 하나의 솔루션으로는 현재의 세분화 되고 다양화 되어지는 고객 관리 프로세스를 충족 시키기가 어렵다. (중략)

• Journal of Digital Convergence
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• v.11 no.1
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• pp.139-144
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• 2013

This paper is an exploratory study to improve customer satisfaction survey for resolving practical problems. It is natural phenomenon that, as the level of customer satisfaction index increases, the ratio of satisfied customers increases too. However, the effectiveness of practical application of customer satisfaction survey for improvement of customer satisfaction decreases due to its structural limitation on its data analysis system. In order to cope with these problems, we compares the three satisfied customer reclassification methods such as attribute complex scores, satisfaction/dissatisfaction dimension and latent class analysis models. The case study results show that satisfied customer reclassification methods have merits and demerits and are expected to play the role as the groundwork for the revitalization of customer satisfaction survey as well as improving customer satisfaction management.

• Journal of Korean Ophthalmic Optics Society
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• v.20 no.4
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• pp.405-414
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• 2015

Purpose: We analyse characteristics of optical shop customer's segmented market by using clustering analysis, and we expect it would be a useful indicator of marketing strategy for optical shops. Methods: Survey was conducted from March 10 to March 31, 2015. The survey asked customers who have visited optical shops in Seoul and Northern Gyeonggi-do regions, and analyzed by utilizing SPSS v.10.0 statistical package program. The analysing methods are frequency analysis, factor analysis about variable of values, clustering analysis for market segmentation, and crosstabs. Results: The market is segmented based on values. In the process of establishing marketing strategy, it is useful to establish strategy by classifying customers into 3 types of cluster; "middle level value oriented cluster", "high level value oriented cluster", "high level value oriented and non-religious cluster". In marketing strategy of progressive lenses, it turned out that the most important strategy is to target self-employed person in "middle level value oriented cluster". Conclusions: As a result of market segmentation by using clustering analysis, it was classified into 3 types of cluster, and we found that most important customer for progressive lenses is self-employed person in "middle level value oriented cluster" who is more than 41 years old.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.272-284
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• 2009

In this paper, we proposed the methodology for analyzing online customer reviews by using text mining technologies. We introduced marketing segmentation into the methodology because it would be efficient and effective to analyze the online customers by grouping them into similar online customers that might include similar opinions and experiences of the customers. That is, the methodology uses categorization and information extraction functions among text mining technologies, matched up with the concept of market segmentation. In particular, the methodology also uses cross-tabulations analysis function which is a kind of traditional statistics analysis functions to derive rigorous results of the analysis. In order to confirm the validity of the methodology, we actually analyzed online customer reviews related with tourism by using the methodology.