• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.105-124
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• 2007

CRM (Customer Relationship Management) becomes a crucial paradigm as the environment of the market changes. About the CRM actively maintaining and managing customers that have been already acquired, the research has been done as a plan to lure loyal customers who bring lucrative profits in the long term for the company in order to increase the value to the customers. However, in practice, the focus is on putting spurs to attracting new customers in a short term rather than retaining existing customers who give profitable revenues. If the company puts high emphasis on drawing the new customers, in a CRM's point of view in relation to the value of the customers, it can incur a loss in the long run. The reason is that if the firm conducts discriminative sales promotion, the existing clients with high loyalty will feel relatively treated inappropriately and they will have negative feelings such as being betrayed from the company they prefer. This occurrence of negative emotion can in-crease the possibility of highly profitable clients' secession. In consequence, this paper focusing on the process of the client segmentation at the mobile telecommunication services shows that the sales promotion strategy for the new customer attraction can lead to negative effect on the loyalty of the existing customers.

• Fashion & Textile Research Journal
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• v.10 no.1
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• pp.50-58
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• 2008

This study aims to identify whether shopping malls affect customer satisfaction significantly according to the store image assessment of consumers after their purchases. This comparative study on the store image and satisfaction level according to shopping mall type is supposed to offer useful basic data for developing a niche market while establishing market segmentation strategies for internet fashion shopping malls. As a result of an empirical analysis, it was found that important standards for assessing the store image of internet fashion shopping malls include product and information service, customer service after purchase, atmosphere, convenience and reliability, and all five factors were shown to affect the satisfaction level for all general malls significantly. However, product and information service and convenience were shown not to be significantly influential to the satisfaction level for fashion specialty mall. In addition, customer satisfaction was found to affect the customers' intention to repurchase and word of mouth. Therefore, if marketing managers of internet fashion shopping malls elevate customer satisfaction by managing the store image before the customers' purchase, they can attract customers to repurchase intention and ultimately prompt a word of mouth effect.

• Journal of Information Management
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• v.35 no.1
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• pp.51-69
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• 2004

Libraries have been made effect to satisfy customer by reflecting information need of customer on libraries. They have considered introducing the data mining techniques to analyze complicated and massive data of libraries and the Customer Relationship Management(CRM) to produce suitable services to each customer segmentation. The purpose of this study is to apply the CRM and data mining techniques to a library, ultimately intends to suggest rules for the collection management and the customer management.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.119-128
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• 2010

The purpose of this thesis is to analyze and test hypotheses that the internet shopping customer's satisfaction would be differences between customer's lifestyle and a type of buying product characteristics. In addition, this study tested differences between lifestyle groups and product type in terms of customer's transaction continuity. In result, we find that there are significant differences of customer's satisfaction and customer's continuity in terms of the lifestyle, but not in the product types. This study provide useful informations on market segmentation strategy to the firms which had been doing on-line shopping and will help them minimize the possible risks when firms enter into internet shopping market.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.27-37
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• 2022

Purpose: The purpose of this study is to derive various ways to realize customer satisfaction for the development of the service industry by exploring research trends related to customer satisfaction, which is presented as an important goal in the service industry. Research design, data and methodology: To this end, 1,456 papers with English abstracts using scienceON were used for analysis. Using Python 3.7, word frequency and co-occurrence analysis were confirmed, and topics related to research trends were classified through BERTopic and LDA. Results: As a result of word frequency and co-occurrence frequency analysis, words such as quality, intention, and loyalty appeared frequently. As a result of BERTopic and LDA, 11 topics such as 'catering service' and 'brand justice' were derived. As a result of trend analysis, it was confirmed that 'brand justice' and 'internet shopping' are emerging as relatively important research topics, but CRM is less interested. Conclusions: The results of this study showed that the 7P marketing strategy is working to some extent. Therefore, it is proposed to conduct research related to acquisition of good customers through service price, customer lifetime value application, and customer segmentation that are expected to be needed for the development of the service industry.

• Journal of Fashion Business
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• v.6 no.5
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• pp.136-150
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• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• Journal of Global Scholars of Marketing Science
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• v.14
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• pp.125-144
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• 2004

The purpose of this study is to classify customer bye-mailing responsiveness on time-series analysis and RFM module and testify the effectiveness of grouping by ROI analysis. RFM (Recency, Frequency, Monetary Value) analysis are used for customer classification that is fundamental process of e-CRM application. ROI analysis were consisted of open, click-through, duration time, conversion rate, personalization and e-mail loyalty index. Major findings are as follows; Customer segmentation were loyal customer, odds customer, dormant customer, secession customer and observation customer by Activity email module. And Loyal, dormant and secession customer are segregated by RFM module. Loyal customer group have higher point of all ROI index than other groups. These results indicated that customer responsiveness of e-mailing and RFM analysis were appropriate methods to grouping the customer. Mid-small Internet Biz adapted marketing strategy by optimization of consumer information.

• 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.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.309-321
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• 2014

Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.