• 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.

• Asia Marketing Journal
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• v.14 no.4
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• pp.143-165
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• 2013

Sales force automation (SFA) technologies are increasingly used to support customer relationship management (CRM) strategies. However, the popular press reports mixed results among companies incorporating SFA technologies and the previous studies have less interested in relationship quality between sales person and customer as an outcome of SFA. Actually the improved quality of the salesperson-customer relationship may be the most important outcome of SFA usage. This outcome is especially meaningful in today's marketplace given the increasing focus placed on customer retention and other customer related performance such as customer lifetime value. Therefore, this study seeks to further examine the impact of SFA usage within two different firms using SFA technologies to examine the impact of SFA usage on both customer relationship quality and sales performance. Additionally, the moderating roles of perceived managerial support and salesperson experience on the outcomes of SFA usage are examined. The results shows that direct effect of SFA usage on performance was not significant but highlight the mediating role of customer relationship quality in the SFA usage - sales performance relationship. Also, this research examines a number of moderating effects of both management supports for SFA and salesperson's sales work experience. The results indicate that management support has a significant direct influence on relationship quality and salesperson performance, but not a significant moderating effect on the relationship between SFA usage and the outcomes (relationship quality and performance). Thus moderating effects were not supported but find significant main effects. First of all, finding of this study suggest that a formula for successful SFA implementation must be one that highlights a SFA usage → relationship quality → sales performance sequence. This means when sales person use SFA they must build relationship with customer first then will return some long term performance. Second, the implications of not considering the introduction of big technology initiatives in terms of fit within the company's culture, strategy, structure, and environment may in many cases be quite noteworthy. Therefore, the launching of a new technology in the firm, such as SFA, may have a nonlinear impact upon overall firm performance, depending on the presence of other complimentary resources and capabilities. Finally the authors offer a number of implications for research and practice, and suggest directions for future SFA research that may further improve our understanding of this increasingly relevant topic.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.268-274
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• 2005

고객관리란 고객데이터와 정보를 분석, 통합하여 개별 고객의 특성에 기초한 마케팅 활동을 계획, 지원, 평가하는 과정이다. 고객 관리는 기업에 있어서 가장 중요한 전략 중의 하나이며, 1990년대 이후로 그 중요성은 강조되어 왔다. 이러한 고객관리의 출발은 고객의 가치를 정확히 측정하는 것이며, 고객평생가치를 판단하기 위한 많은 연구가 이루어졌다. 우리는 고객평생가치 모델을 한국의 이동통신산업에 적용하기 위한 이론적 배경과 그 방법론을 분석하였다. 또한 이 논문은 이러한 과정에서 나타나는 문제점의 원인과 그 해결방안을 제시하고 있다. 이러한 연구와 방법론들은 실제 마케팅 전략에 직접적으로 활용될 수 있을 것이다.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.53-84
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• 2013

With rapid development of ICT (Information and Communications Technology), new services by the convergence of mobile network and application technology began to appear. Today, smart phone with new ICT convergence network capabilities is exceedingly popular and very useful as a new tool for the development of business opportunities. Previous studies based on Technology Acceptance Model (TAM) suggested critical factors, which should be considered for acquiring new customers and maintaining existing users in smart phone market. However, they had a limitation to focus on technology acceptance, not value based approach. Prior studies on customer's adoption of electronic utilities like smart phone product showed that the antecedents such as the perceived benefit and the perceived sacrifice could explain the causality between what is perceived and what is acquired over diverse contexts. So, this research conceptualizes perceived value as a trade-off between perceived benefit and perceived sacrifice, and we need to research the perceived value to grasp user's continuous intention to use of smart phone. The purpose of this study is to investigate the structured relationship between benefit (quality, usefulness, playfulness) and sacrifice (technicality, cost, security risk) of smart phone users, perceived value, and continuous intention to use. In addition, this study intends to analyze the differences between two subgroups of smart phone users by the degree of personal innovativeness. Personal innovativeness could help us to understand the moderating effect between how perceptions are formed and continuous intention to use smart phone. This study conducted survey through e-mail, direct mail, and interview with smart phone users. Empirical analysis based on 330 respondents was conducted in order to test the hypotheses. First, the result of hypotheses testing showed that perceived usefulness among three factors of perceived benefit has the highest positive impact on perceived value, and then followed by perceived playfulness and perceived quality. Second, the result of hypotheses testing showed that perceived cost among three factors of perceived sacrifice has significantly negative impact on perceived value, however, technicality and security risk have no significant impact on perceived value. Also, the result of hypotheses testing showed that perceived value has significant direct impact on continuous intention to use of smart phone. In this regard, marketing managers of smart phone company should pay more attention to improve task efficiency and performance of smart phone, including rate systems of smart phone. Additionally, to test the moderating effect of personal innovativeness, this research conducted multi-group analysis by the degree of personal innovativeness of smart phone users. In a group with high level of innovativeness, perceived usefulness has the highest positive influence on perceived value than other factors. Instead, the analysis for a group with low level of innovativeness showed that perceived playfulness was the highest positive factor to influence perceived value than others. This result of the group with high level of innovativeness explains that innovators and early adopters are able to cope with higher level of cost and risk, and they expect to develop more positive intentions toward higher performance through the use of an innovation. Also, hedonic behavior in the case of the group with low level of innovativeness aims to provide self-fulfilling value to the users, in contrast to utilitarian perspective, which aims to provide instrumental value to the users. However, with regard to perceived sacrifice, both groups in general showed negative impact on perceived value. Also, the group with high level of innovativeness had less overall negative impact on perceived value compared to the group with low level of innovativeness across all factors. In both group with high level of innovativeness and with low level of innovativeness, perceived cost has the highest negative influence on perceived value than other factors. Instead, the analysis for a group with high level of innovativeness showed that perceived technicality was the positive factor to influence perceived value than others. However, the analysis for a group with low level of innovativeness showed that perceived security risk was the second high negative factor to influence perceived value than others. Unlike previous studies, this study focuses on influencing factors on continuous intention to use of smart phone, rather than considering initial purchase and adoption of smart phone. First, perceived value, which was used to identify user's adoption behavior, has a mediating effect among perceived benefit, perceived sacrifice, and continuous intention to use smart phone. Second, perceived usefulness has the highest positive influence on perceived value, while perceived cost has significant negative influence on perceived value. Third, perceived value, like prior studies, has high level of positive influence on continuous intention to use smart phone. Fourth, in multi-group analysis by the degree of personal innovativeness of smart phone users, perceived usefulness, in a group with high level of innovativeness, has the highest positive influence on perceived value than other factors. Instead, perceived playfulness, in a group with low level of innovativeness, has the highest positive factor to influence perceived value than others. This result shows that early adopters intend to adopt smart phone as a tool to make their job useful, instead market followers intend to adopt smart phone as a tool to make their time enjoyable. In terms of marketing strategy for smart phone company, marketing managers should pay more attention to identify their customers' lifetime value by the phase of smart phone adoption, as well as to understand their behavior intention to accept the risk and uncertainty positively. The academic contribution of this study primarily is to employ the VAM (Value-based Adoption Model) as a conceptual foundation, compared to TAM (Technology Acceptance Model) used widely by previous studies. VAM is useful for understanding continuous intention to use smart phone in comparison with TAM as a new IT utility by individual adoption. Perceived value dominantly influences continuous intention to use smart phone. The results of this study justify our research model adoption on each antecedent of perceived value as a benefit and a sacrifice component. While TAM could be widely used in user acceptance of new technology, it has a limitation to explain the new IT adoption like smart phone, because of customer behavior intention to choose the value of the object. In terms of theoretical approach, this study provides theoretical contribution to the development, design, and marketing of smart phone. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy formulation for acquiring and retaining long-term customers related to smart phone business. Since potential customers are interested in both benefit and sacrifice when evaluating the value of smart phone, marketing managers in smart phone company has to put more effort into creating customer's value of low sacrifice and high benefit so that customers will continuously have higher adoption on smart phone. Especially, this study shows that innovators and early adopters with high level of innovativeness have higher adoption than market followers with low level of innovativeness, in terms of perceived usefulness and perceived cost. To formulate marketing strategy for smart phone diffusion, marketing managers have to pay more attention to identify not only their customers' benefit and sacrifice components but also their customers' lifetime value to adopt smart phone.

• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.45-55
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• 2023

Purpose: As one of the continuous studies on the offline distribution industry, the purpose of this study is to find ways for offline stores to respond to the growth of online shopping by identifying research trends on department stores. Research design, data and methodology: To this end, this study conducted word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and dynamic topic modeling using Python 3.7 on a total of 551 English abstracts searched with the keyword 'department store' in scienceON as of October 10, 2022. Results: The results of word frequency analysis and co-occurrence frequency analysis revealed that research related to department stores frequently focuses on factors such as customers, consumers, products, satisfaction, services, and quality. BERTopic and LDA analyses identified five topics, including 'store image,' with 'shopping information' showing relatively high interest, while 'sales systems' were observed to have relatively lower interest. Conclusions: Based on the results of this study, it was concluded that research related to department stores has so far been conducted in a limited scope, and it is insufficient to provide clues for department stores to secure competitiveness against online platforms. Therefore, it is suggested that additional research be conducted on topics such as the true role of department stores in the retail industry, consumer reinterpretation, customer value and lifetime value, department stores as future retail spaces, ethical management, and transparent ESG management.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• The Journal of Industrial Distribution & Business
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• v.1 no.1
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• pp.33-41
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• 2010

In the age of globalization, effective and efficient corporate management is becoming more important as domestic and international business circumstances changes. In the middle of endless changes in business circumstances, fast reaction to customers and market, and offering customized goods and service became essential. In this respect, CRM designed to utilize customer information scientifically and systematically, has become an essential system and marketing strategy to enhance corporate competitiveness. CRM has placed the importance of customers in the front of marketing and has focused every process and business minds on customers. Recent change in the market and the trend of establishing and introducing CRM system has lead us to concentrate on the introduction of CRM in the financial institutions. This study searched for several views about CRM in academic and industrial papers. Through theoretical approach on CRM, the background of the introduction of CRM, the purpose of CRM, the characteristic and application of CRM, and the expected effect of CRM will be discussed. This study is focused on financial institutions where CRM is widely used. And through documents about examples of the introduction of CRM, the status of the establishment of domestic CRM and the necessity and trend of CRM will be discussed. Also the problem of CRM in the financial institutions and the improvement of CRM in domestic banks will be analyzed. When discussing CRM in the financial area, customers are the main source of corporate profit and through relationship management with the customers enhancing loyalty and maximizing profit can be obtained. Especially in CRM in financial institutions, maintaining existing customers makes higher profit ratio, so repurchasing and cross selling becomes important for obtaining lifetime value of existing customers who contribute to most of the profit of corporations. As a result, CRM should be completely customer oriented. CRM in financial institutions is not merely marketing work, but organizational competence which is made up of standardized work process through total process integration inside the corporation. Corporations which plan to introduce CRM should analyze the characteristics and conditions of corporations and establish purpose and strategy of CRM. And they need long term view to find out the factors which best fit for the introduction of CRM. To enable this, strategy composed of daily marketing activity and CRM concept is necessary. Also continued improvement through drill and training for operating organization should be followed to maintain CRM well. And corporate culture must settle customer as the center of corporate value. The race for introducing and improving CRM has already begun. CRM should not be regarded as a choice. It should be accepted as something essential. In this reality financial institutions should solve subdivision problem of customers and necessity of customers with the mind of 'customer's profit is my profit'. Customer focused management should not be emphasized only by words. Efforts like viewing from the customer's point must be nurtured to provide methods to help customers. That is, we should not just follow what is done in foreign countries. We should solve the problem of our customers according to the situation of our country, our industry, our corporation. Then we can gain the trust of customers, and the value derived from the customers will become the background of CRM which will lead the corporation to success.

• The Journal of Industrial Distribution & Business
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• v.2 no.1
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• pp.5-15
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• 2011

Prior to the introduction of the CRM, we need to analyze the characteristics and the situations of the company, and should establish a clear vision of the CRM. And each company should identify elements and technologies for introducing the most suitable CRM for them, and optimize them, with long-term perspective. In addition, it requires the implementation strategy which integrates the existing company's routine marketing activities with the concept of the CRM. According to the implementation strategy, the company should improve the business process which is the most effective in investment step by step, and the information system strategy, which develops system investment gradually, should harmonize with it. First, we recognized that raising the company value is important by maximizing customer lifetime value (LTV) by understanding customer needs, and achieving the company's goal through customer satisfaction. Second, we understood that adopting the CRM should be accompanied by changes in the structure, business process and customer contact channels, and it can be successfully integrated with business when it gets proper understandings and attentions of the management. Third, the reality is that there are few cases of successful implementation of domestic companies, and some companies that successfully implement the system mean nothing but implement the solution for developing the CRM. Therefore, it needs to be observed for the long haul, and it seems that we need to approach more systematically to implementation cases for each industry about implementation of the CRM. Fourth, the CRM is no longer the preserve of major companies, and it is the time that medium and small sized enterprises also need it. Taking lesson from Switzerland's small size store merchants who successfully adopt right size of the CRM for their business, for domestic medium and small sized enterprises, the necessity to develop business through developing the CRM models which fit their situations and maintaining relationships with customers has been grown. Fifth, for adopting the CRM business processes, changing or converting the CRM system to the model which fits the company's situation is important rather than applying the advanced company's CRM system model. In other words, the CRM solution which can maximize their own strength by developing the CRM program that makes the most of features and characteristics of the company should be adopted.