• Korean Management Science Review
• /
• v.26 no.1
• /
• pp.183-196
• /
• 2009

Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

• Information Systems Review
• /
• v.8 no.3
• /
• pp.125-134
• /
• 2006

This article adopts a decision tree algorithm(C5.0) to predict customer churning in online auto insurance environment. Using a sample of on-line auto insurance customers contracts sold between 2003 and 2004, we test how decision tree-based model(C5.0) works on the prediction of customer churning. We compare the result of C5.0 with those of logistic regression model(LRM), multivariate discriminant analysis(MDA) model. The result shows C5.0 outperforms other models in the predictability. Based on the result, this study suggests a way of setting marketing strategy and of developing online auto insurance business.

• Journal of Service Research and Studies
• /
• v.6 no.3
• /
• pp.57-78
• /
• 2016

The purpose of this research is to study how service recovery activities influence customers' commodity churning in the media telecommunication industry(CATV industry). Put it differently, we tried to identify this change of commodity churning rates by the stages of service failures, by which we intend to emphasize the importance of service recoveries. Korean media telecommunication market has already been saturated; customers tend to move to bigger major companies with better customer care increasingly. As once customers gone never returns, CRM functions are being reinforced over the time. We were able to have the following results. First, turning rates, for those experienced service failure, who were dissatisfied with service recovery activities are 2~5 times (monthly average turning rates are 1.3%) higher than those satisfied. Secondly, active service recovery activities at the customer's service request after experiencing service failure lowered churning rates significantly. The most effective timing is service recovery activities pre-recovery stage. Thirdly, reward activities after service recovery activities at the immediate recovery stage is more effective than service recovery at the arranged recovery schedule and reward activities after customer's expressing churning intension. The implications of this study are that firms should engage in service recovery activities at the time of identifying service failures, prior to customer's expressing churning intention, which means relatively lower ROI for the service recovery activities than the times of customers' expressing churning intention.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.34 no.4
• /
• pp.57-72
• /
• 2009

As development of information technologies, customer retention has been an important issue in the competing environment. A lot of researches focus on prediction of the churning customers and seeking their characteristics. However, relationships among customers or products have not been considered in existing researches. In this study, product networks are proposed and analyzed to investigate the differences of network characteristics of products purchased by potential churning customers and those of loyal customers. The product networks are constructed from real product purchase data collected from a Korean department store. We investigated the characteristic differences, such as the degree centrality, degree centralization, and density, of two product networks constructed by potential churning customers and the loyal customers. The results indicate that degree centrality, density and degree centralization of the product network of the loyal customers are higher than those of the potential churning customers. And the promotional products of the department store are resulted to be effective in attracting the loyal customers.

• Asia Marketing Journal
• /
• v.7 no.1
• /
• pp.21-42
• /
• 2005

Customer Relationship Management (CRM) is a corporate marketing strategy maintaining and managing customers. And with CRM companies maximize the customer's value through a series of processes of new customer retention, VIP customer retention, customer value increase, potential customer activation, and customers for lifetime by collecting the customer information and taking advantage of it effectively. In particular, as the competitive environment is changing rapidly and getting more intense, maintaining the customer retention through customer churn management becomes more important in order to increase the customer value for maximizing the company's profit and to build up the relationship with customers. For example, the financial industry has managed the customer churn with the concept of customer segmentation. Recently the customer retention and churn management is becoming increasingly important in all business fields as well as financial industry since the companies expect the effect of preventing the customer churn by identifying characteristics of customers. However, despite the increasing interest and importance of the management of the customer churn, not many of studies are systematically executed by analyzing the data of customer churn. In this study we analyze the actual data of CRM activities for the customer retention, specifically the data of TV home-shopping. By doing so, we hope to identify the differences of demographic attributes and transaction specific characteristics in consumer behaviors between the churning customer and the retained customers. In addition, we try to find out the variables which can impact the churning of the customers and to predict the churn rate of individual customer through our proposed model of customer churn. In the end, based on our findings we suggest the possible marketing strategies for TV home-shopping companies.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.10a
• /
• pp.310-313
• /
• 2000

This paper develops a model of customer satisfaction in the mobile telecommunication services. We examine the relationships among customers'overall satisfaction and underlying dimensions； perceived service quality, service value, and brand image. Variables related to customer satisfaction and dissatisfaction are derived from customer critical incidence survey. The model is estimated with multi-variate data analysis. Results indicate that the (1) technical service quality is the main driver of customer overall satisfaction, (2) some peripheral services are rapidly evolving into the core services of mobile telecommunications, and (3) the current policy of service providers does not focus on customer satisfaction but on establishing churning barrier by increasing switching costs.

• Journal of Intelligence and Information Systems
• /
• v.7 no.1
• /
• pp.17-25
• /
• 2001

Tree model is the most popular classification algorithm in data mining due to easy interpretation of the result. In CART(Breiman et al., 1984) and C4.5(Quinlan, 1993) which are representative of tree algorithms, the split fur classification proceeds to attain the homogeneous terminal nodes with respect to the composition of levels in target variable. But, fur instance, in the chum prediction modeling fur CRM(Customer Relationship management), the rate of churn is generally very low although we are interested in mining the churners. Thus it is difficult to get accurate prediction modes using tree model based on the traditional split rule, such as mini or deviance. Buja and Lee(1999) introduced a new split rule, one-sided purity for classifying minor interesting group. In this paper, we compared one-sided purity with traditional split rule, deviance analyzing churning vs. non-churning data of ISP company. Also reviewing the result of tree model based on one-sided purity with some simulated data, we discussed problems and researchable topics.

• Industrial Engineering and Management Systems
• /
• v.13 no.4
• /
• pp.454-462
• /
• 2014

Retention of possible churning customer is one of the most important issues in customer relationship management, so companies try to predict churn customers using their large-scale high-dimensional data. This study focuses on dealing with large data sets by reducing the dimensionality. By using six different dimension reduction methods-Principal Component Analysis (PCA), factor analysis (FA), locally linear embedding (LLE), local tangent space alignment (LTSA), locally preserving projections (LPP), and deep auto-encoder-our experiments apply each dimension reduction method to the training data, build a classification model using the mapped data and then measure the performance using hit rate to compare the dimension reduction methods. In the result, PCA shows good performance despite its simplicity, and the deep auto-encoder gives the best overall performance. These results can be explained by the characteristics of the churn prediction data that is highly correlated and overlapped over the classes. We also proposed a simple out-of-sample extension method for the nonlinear dimension reduction methods, LLE and LTSA, utilizing the characteristic of the data.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2013.07a
• /
• pp.109-110
• /
• 2013

국내 이동통신 서비스 시장 사업자들은 신규고객 유치에 집중하기 보다는 기존고객 유지에 더 관심을 가지고 있다. 이러한 배경에는 새로운 신규고객의 창출에 소요되는 비용이 기존고객을 유지하는 비용이 적게 들기 때문이다. 따라서 고객이탈을 발생시키는 요인이 무엇인지를 본 연구에서 알아보고자 한다.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2002.10a
• /
• pp.21-24
• /
• 2002

There is a trend with driveline lubricants toward improved thermal stability, vehicle component durability and fuel efficiency. These improvements can significantly reduce vehicle operating costs and improve customer satisfaction. Of these improvements, the fuel efficiency is getting a substantial attention due to recent focus on $CO_2$ emission control in Europe, Japan and $CAF{\'{E}}$ requirement in U.S.A. Lower viscosity axle oils and transmission fluids are currently being evaluated as potential solutions since these lubricants tend to reduce the churning losses and can improve the fuel efficiency. However, these lubricants should provide adequate gear and bearing protection, while increasing the overall efficiency of the driveline components. In this paper, the development of new fuel efficient axle was discussed with the focus on the effect of base oils, additives, and viscosity modifiers on the fuel efficiency of driveline components.