• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.45-60
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• 2005

The purpose of this study is to classify customer by e-mailing responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems were adapted for Customer segmentations. ROI analysis were consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customer segmentations were loyal customer, odds customer, dormant customer, secession customer and observation customer by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mailing systems were appropriate methods to grouping the customer with demographic variables. Therefore, effective e-mailing marketing strategy of e-Biz have suitable active DB and Behavior targeting is best approach to enforcing the target e-mailing marketing.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.531-538
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• 2005

In k-means clustering, we standardize variables before clustering and iterate two steps: units allocation by Euclidean sense and centroids updating. In applications to DB marketing where clusters are to be used as customer segments with similar consumption behaviors, we frequently acquire additional variables on the customers or the units through marketing campaigns a posteriori. Hence we need to modify the clusters originally formed after each campaign. The aim of this study is to propose a revision method of k-means clusters, incorporating added information by weighting clustering variables. We illustrate the proposed method in an empirical case.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.52-69
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• 1998

Using GIS, this study constructs and evaluates a bank marketing system. The study collects a marketing GIS database case from the Daegu Bank, which is one of the leading local banks in Korea. The database includes spatial data such as digital road map, internal and external attribute data which are combined for the construction of bank marketing database. Based on these data, the study developed an interface which enables searching and analysing functions of bank GIS marketing system. For the development of the interface, this study examined the basic concepts of area marketing and its development and utilized Map/Info as a basic GIS software package and Delphi as computer language. Finally, the study makes a comprehensive evaluation of various problems of spatial and attribute data which occurred in the process of constructing the bank marketing database.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.123-127
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• 1999

애경백화점은 백화점 업계 최초로 데이터웨어하우스를 구축하여 이를 기반으로 ACOMS라는 고객 지향적인 마케팅 정보시스템을 도입하였다. 현재로서는 기존고객 유지 및 신규고객 유치를 위해 이용되고 있으나, 이 시스템을 이용한 DB마케팅 전략개발은 앞으로 무한한 가능성을 보이고 있다. ACOMS는 마케팅기획팀에 의해 주도적으로 사용되고 있는데, 이제까지 예측치 못했던 다각적인 판매정보를 입수할 수 있게 됨으로써 더욱 참신한 마케팅 아이디어를 도출해 낼 수 있게 되었다. 이제 이들이 제출하는 마케팅 기획안은 경영진에 의해 신중하게 받아 들여지고 있으며, 따라서 예산이 많이 드는 기획안일지라도 채택되는 빈도가 높아지고 있다. 경영진은 마케팅 기획팀이 제안하는 기획안들이 다각적인 데이터 분석에 의해 수립된 사실을 알기 때문에 그 어느 때보다도 자신감있게 의사결정을 내리고 있다

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.139-154
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• 2011

Recently Internet keyword search service providers tends to use CPC advertizement method rather than CPM method. However researches how much the CPC method is beneficial to advertisers than CPM method in certain perspectives are insufficient and not performed systematically. So this paper tries to do comparative analysis about the two methods by analyzing the real transactional DB data from an advertizement agency. Due to the difficulties of direct comparison between the two methods because of their different expose positions on the Web and different types of attributes in DB, we did some preprocessing step for the transactional data. From the result of analysis, the click rate of CPC is higher than CPM by 1.3% and the unit cost for the CPC per one click is lower than CPM method by 51 Won. It shows the CPC method is more effective than CPM method for advertizement from the point of advertizement effectiveness (CTR) and advertizement cost (CPC). We hope this research would give useful information to advertisers and marketing managers in making advertizement strategy, marketing decision and budgeting.

• Information Systems Review
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• v.21 no.4
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• pp.31-45
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• 2019

Despite the expansion of the market of performing arts and culture, small and medium size theaters are still experiencing difficulties due to poor accessibility of information by consumers. This study proposes a machine learning based genre recommendation system as an alternative to enhance the marketing capability of small and medium sized theaters. We developed five recommendation systems that recommend three genres per customer using customer master DB and transaction history DB of domestic venues. We propose an optimal recommendation system by comparing performances of recommendation system. As a result, the recommendation system based on the ensemble model showed better performance than the single predictive model. This study applied the personalized recommendation technique which was scarce in the field of performing arts and culture, and suggests that it is worthy enough to use it in the field of performing arts and culture.

• Korea Journal of Hospital Management
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• v.17 no.2
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• pp.21-33
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• 2012

Purpose : This study aims to suggest application of patients DB to hospital marketing by performing market segmentation and selecting target market. Consequently help to establish suited strategy of marketing. Method : 14,072 patients hospitalized in a University Medical Center were recruited into this study. In order to classify the customer groups, cluster analysis was used with RFM(Recency, Frequency, Monetary) model, and 1-way ANOVA verified the differences among groups. And then, sociodemographical status, healthcare utilization and diagnosis(ICD-10) of each group were compared to draw a marketing strategy. Results : Four groups were classified through clustering analysis, and'high use and high profit' and'low use and high profit' groups were selected as a target market. The features of target market were as follows, the female proportion was high; used a private room; hospitalized through the emergency room; had operation; length of stay was long; had many comorbidity and cooperative treatment. There was difference in each feature of target market: as for the'high use and high profit' group, many patients were diagnosed with 'certain infectious and parasitic diseases'; and as for the'low use and high profit'group, the proportion of patients who purchased'industrial accident compensation insurance'and'auto insurance'was relatively high; many patients were diagnosed with'Injury, poisoning and certain other consequences of external causes'. Conclusion : It is needed to establish'positioning' strategy by monitoring and communicating with'high use and high profit' group. And for the case of'low use and high profit' group, it is necessary to make a follow-up management and lead them to have a medical check-up.

• Archives of design research
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• v.15 no.2
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• pp.169-176
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• 2002

The purpose of this paper is to describe and predict the color trends of the handy electronic plastics product materials using design management based on a field survey in Korea and Japan. It is attempted to suggest more rational, systematic design process management of Korean firms, and to provide sharing of design knowledge management system among small businesses, home appliances, and the related organizations. Results of color trends survey shown plastics materials are cybertic, purity, and colorful trends. In addition, as emotional marketing strategy the trends of color and face processing are high quality, variety, and difference. Finally, this paper also suggests the way of DB building of color trends.

• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.381-389
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• 2014

This research focuses on the current trend of 'Sharing Transportation' to clarify the regional factors having a decisive effect on the use of Car Sharing. To accomplish this, the current research is built a Database of the regional characteristics of Car Sharing spots based on railway stations in Seoul and performed an analysis of the primary regional factors affecting Car Sharing usage. As a result, we found conclusive factors affecting the use of Car Sharing. This research can be utilized for establishing strategies and effective measures to support the use of Car Sharing and sustainable development with respect to issues of motorization.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.473-474
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• 2023

본 연구는 코로나-19 이후로 증가할 것으로 보이는 방한 외국인 관광객의 지역별 소비 경향을 카드 소비 데이터를 데이터베이스화하여 다각적인 방면에서 분석하고 정보를 만들었다. 코로나 이전 'K-pop'과 'K-drama'의 영향으로 계속해서 증가하던 방한 외국인의 수는 코로나의 영향으로 50%가량 감소했다. 하지만 '위드 코로나'로 접어든 지금, 다시금 외국인 관광객을 유치하기 위해선 각 관광객의 니즈에 맞는 서비스를 제공해야 한다. 또한, 각 지자체에서는 외국인 관광객이 선호하는 서비스를 파악하고 각 국적별 관광객에게 맞는 서비스를 제공하는 노력을 통해 지역경제를 활성화시킬 수 있을 것이다. 현재 많은 기업에서 지역별, 업종별로 맞춤 서비스를 제공하는 것처럼, 지자체가 구체적인 데이터를 사용하여 맞춤 서비스를 제공한다면 코로나로 어려운 시기를 슬기롭게 극복할 수 있다고 생각한다.