• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.43-48
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• 2010

Useful emails influence on consumers' purchase behavior and activate them to visit retail stores. Regular contact with consumers by e-mail has positive effects on brand loyalty. However, email marketing has a limitation. Spam now accounts for over half of all e-mail traffic. The increase of email users has resulted in the dramatic increase of spam emails during the past few years. In this paper, we proposed an ontology-based system offering personalized email services to overcome such limitation. Our method is not the ontology-driven spam filtering, but a personalized content service considering personal interests and relations among people by using FOAF and domain ontologies. Our system was successfully tested in email marketing domain.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.205-211
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• 2012

This paper presents research result of digital marketing model for improving enterprise marketing campaign performance. Recently, the enterprises which had completed projects such as ERP, CRM, and SCM for business value chain process transformation are working to improve enterprise marketing process. It is the trend for enterprises to use digital marketing tactics to overcome the limit of existing traditional marketing tactics. Especially, enterprises try to adopt digital marketing for marketing campaign performance. In this paper, digital marketing research model and hypothesis were established and statistically analyzed by marketing expert survey research. The research finding is that Web Analytics, Social Analytics, Personalized CRM, Campaign execution automation, Real-Time campaign management can be core influencers for marketing campaign performance improvement.

• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1175-1182
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• 2001

One to one Marketing (a.k.a. database marketing or relationship marketing) is one of the many fields that will benefit from the electronic revolution and shifts in consumer sales and advertising. As a component of intelligent customer services on Internet storefront, this paper describes technology of providing personalized advertisement using the market basket analysis, a well-Known data mining technique. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customer's data. However, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed Knowledge base. In this paper, using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.335-345
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• 2005

In personalized marketing, it is important to maximize customer satisfaction and marketing efficiency. As personalized campaigns are frequently performed, several campaigns are frequently run simultaneously. The multiple recommendation problem occurs when we perform several personalized campaigns simultaneously. This implies that some customers may be bombarded with a considerable number of campaigns. We raise this issue and formulate the multi-campaign assignment problem to solve the issue. We propose dynamic programming method and various heuristic algorithms for solving the problem. With field data, we also present experimental results to verify the importance of the problem formulation and the effectiveness of the proposed algorithms.

• Industry Promotion Research
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• v.8 no.4
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• pp.1-15
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• 2023

This study was conducted from May 10th to 30th, 2023 to confirm the relationship between advertisement irritation, privacy concerns, personalized marketing, and social influence of brand customized advertisements on advertisement avoidance and brand loyalty targeting the MZ generation. The following results were verified using the SPSS 28.0 and Smart PLS 4.0 programs for a valid survey of 400 people targeting the MZ generation nationwide on a daily basis. First, advertisement irritation had a positive (+) effect on advertisement avoidance but had no effect on brand loyalty, and personalized marketing had a positive (+) effect on advertisement avoidance but had no effect on brand loyalty. Second, concerns about personal information had a positive (+) effect on avoidance of advertisements and brand loyalty. Third, social influence had a positive (+) effect on advertisement avoidance and brand loyalty. Fourth, advertisement avoidance played a significant mediating role between advertisement irritation and brand avoidance, but did not play a significant mediating role between personalized marketing and social influence. Based on these results, this study is meaningful in that it can be used as basic data for research on advertising avoidance and brand loyalty and for establishing strategies necessary for brand marketing activities.

• The KIPS Transactions:PartA
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• v.19A no.1
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• pp.61-68
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• 2012

Since the increasing use of smart devices such as smartphone and tablet PC improves the quality of convergence of broadcasting and telecommunication, many new media have been created. This smart device can provide personal environments based on user's profile (age, gender, and job) and current location. In addition, it can be regarded as a media platform with two-way communication. This paper proposes personalized message syndication, called PMS, based on smart devices and then analyzes its business and technical issues. The PMS service as a smart media provides consumers customized information and can be used for producer's marketing tools which can lead consumers' heart and participation.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.311-317
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• 2016

In a smart commerce market, customers are seeking customized shopping services optimized for personal tastes and customized shopping experiences based on customers' tastes. Accordingly, individually customized services are needed more than anytime now. According to this demand, companies provide messaging services to the consumer, but do not include a personalized service for each individual. The purpose of this study is to combine the techniques of personalized services with messaging services and presents system construction plan and integrated model system for corporate messaging services and thereby possible are maximizing marketing effects and analyzing effects of cost savings. Applying the operation of the integrated model is proposed and message transmission scheme through effective personalization can be applied to personalized model using the personalized information according to customers' requirements. The integrated model of personalization on this study is expected to be highly effective when combined with the search service.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.93-97
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• 2002

In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)

• Management & Information Systems Review
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• v.9
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• pp.81-97
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• 2002

In the beginning of the Web history, the main function and importance of the Internet was focused on the content of the data. However, that focus has been switched to the search engines because of the abundant, humongous amount of data that are spread all over the globe. The Webmasters are now implying flasy, beautiful graphics and newly developed technologies to make their websites attract the Internet users. The significant change was mainly caused by the companies that thought cyber shopping malls were going to be very simple and profitable. They believed that the decreasing prices of hardware and easy-to-use software were going to attract the potential customers, resulting in a new, massive market. A website needs to be extremely captivating and attractive, in order to bring in new customers and induce them to return. The Webmaster has to devise methods to find out what kinds of contents would bring in a bigger audience, as well as checking the validity and correctness of the contents. In the thesis, the necessity and concept of a personalized Internet shopping mall will be discussed through the theoretical examination of the one-to-one marketing and the concept of the current shopping malls. The scheme of the personalized shopping mall will be presented, which will encourage the formation of loyal customers, in the ever-growing competitiveness of the marketing environment, by satisfying their wants faster and more precisely.