• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.259-263
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• 2002

CLV(Customer Lifetime Value; 고객생애가치)는 한 고객이 기업의 고객으로 존재하는 전체 기간동안 그 기업에게 제공할 것으로 추정되는 잠재적인 수익의 합계로 정의할 수 있으며, CRM(Customer Relationship Management)이 기업의 경쟁력 강화를 위한 핵심 수단으로 등장하면서 고객가치에 대한 측정 및 분석의 필요성이 증가하고 있다. 본 연구에서는 CLV를 측정하기 위해서 제안된 여러 모형들을 소개, 비교하고 몇 가지 측면에서 기존 모형들의 단점을 보안할 수 있는 모형들을 제안하고자 한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.187-190
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• 2003

Since the early 1980s, the concept of relationship management in marketing area has gained its importance. Acquiring and retaining the most profitable customers are serious concerns of a company to perform more targeted marketing campaigns. For effective CRM (Customer Relationship Management), it is important to gather information on customer value. Many researches have been performed to calculate customer value based on CLV (Customer Lifetime Value). It, however, has some limitations. It is difficult to consider the churn of customers, because the previous prediction models have focused mainly on expected future cash flow derived from customers'past profit contribution. In this paper we suggest a CLV model considering past profit contribution, potential benefit, and churn probability of a customer. We also cover a framework for analyzing customer value and segmenting customers based on their value. Customer value is classified into three categories: current value, potential value and customer loyalty. Customers are segmented according to the three categories of customer value. A case study on calculating customer value of a wireless communication company will be illustrated.

• International Journal of Costume and Fashion
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• v.10 no.2
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• pp.73-88
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• 2010

Study aims to identify customer equity drivers and their relative importance, to represent customer lifetime value (CLV) distribution, and to investigate the effect of customer equity drivers and demographics on CLV when shopping apparels at the four big department stores in Seoul. Recently, Korean department stores marked significant decrease in sales volume and it calls for more focus on customer orientation. Customer equity is a managerial concept which considers customers as a valuable asset for business success. Sustainable competitive advantage is attainable when customer equity drivers and CLV are measured, managed and enhanced. results identified four dimensions of customer equity drivers such as 'retail brand equity: 'relationship equity', 'retail service equity', and 'price value equity'. Among them, 'relationship equity' was proved to be the most influencing factor on the customer's store patronage intention. The CLV distribution represented unique characteristics of each department store. The level of CLV depended on such demographics as age and income. Marital status influenced the relationship between perceived customer equity drivers and CLV. It also analyzed competitive structure of the four big department stores in Seoul and offered managerial suggestions. This study provided conceptual framework for the future study of customer equity related to apparel shopping at the department stores as well as managerial implications.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.63-82
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• 2014

The main objective of this research is to investigate whether the RFM (recency-frequency-monetary value) information of a customer's redemption behavior of loyalty points can improve the prediction of future value of the customer. The conventional measurement of customer value has been primarily based on purchase transactions behavior although a customer's future behavior can be also influenced by other interactions between the customer and the firm such as redemption of rewards in a loyalty program. We theorize why a customer's redemption behavior can influence her future purchases and thereby the customer's total value based on operant learning theory, goal gradient hypothesis, and lock-in effect. Using a dataset from a major book store in Korea spanning three years between 2008 and 2010, we analyze both purchase transactions and redemption records of over 10,000 customers. The results show that the redemption-based RFM information does improve the prediction accuracy of the customer's future purchases. Based on this result, we also propose an improved estimate of customer lifetime value (CLV) by combining purchase transactions and loyalty points redemption data. Managerial implications will be also discussed for firms managing loyalty programs to maximize the total value customers.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.687-696
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• 2011

Customer Lifetime or Customer Lifetime Value is a essential metric of differentiated CRM marketing and differentiated marketing strategy as a company core competency. However, customer lifetime used in companies is easily obtained from a confined simple customer attrition rate at some specific time point regardless of customer characteristics. In this study, in order to overcome the constraints of previous simple methods and to make practical use of it in industries, we suggest a method that estimates a customer lifetime using a customer segment based survival analysis with the censored data of customers; in addition, we apply this method to A mobile telecom company data. A method using customer segment based survival analysis is suggested in this study 1) includes all customers having different subscription dates, 2) reduces individual error, 3) can reflect trends after the observed time point and is more realistic.

• Asia Marketing Journal
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• v.10 no.4
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• pp.99-121
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• 2009

Social networks can be a powerful force in marketing because they provide new ways to market to young generation. Though many studies on evaluation of customer lifetime value have been conducted, it is not clear how to assess the value of members within social networks. The purpose of this study is to evaluate members based on customer intangible value as well as customer lifetime value. Customer network value in terms of the power and influence within a network is analyzed through network structure analysis. Using Cyworld log file data, this study have shown that high percentage of members are very influential in terms of spreading or withholding information even though their CLV is low. It is expected that the findings of this research contribute to understand the interactive behaviors of members within networks and to provide valuable implications on new product launching and customer management strategies to marketers.

• Journal of Distribution Science
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• v.20 no.6
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• pp.1-10
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• 2022

Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.

• Fashion & Textile Research Journal
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• v.18 no.4
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• pp.438-449
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• 2016

Domestic and foreign tourism authorities show that the most favorite tourist activity is shopping. Tourism income in Korea set a record in 2014 due to a large influx of Chinese tourists. Dongdaemun fashion market was selected as the most preferred destination for Chinese tourists shopping in Korea. This study examines the effect of store attributes on customer equity at Dongdaemun shopping malls. This study adopted a survey; subsequently, 637 questionnaires were used in the final analysis. Collected data were analyzed using SPSS 21.0 and AMOS 18.0 statistics program. The main findings of this study are as follows. Among the three store attributes of Dongdaemun shopping malls, service and environment attributes appeared to influence the three drivers of consumer equity. In addition, value equity was identified to provide a positive impact on Customer Lifetime Value (CLV), brand equity, and relationship equity were identified as having a positive impact on revisit intention. Second, the relationships between the variables were significantly different in two types of the Dongdaemun fashion shopping mall (Doota vs Lotte Fitin). In addition, this study offers a valuable implication for brand marketers to maintain and develop customer equity in Dongdaemun fashion markets.