• 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.

• Asia Marketing Journal
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• v.12 no.4
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• pp.27-54
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• 2011

This research attempted to present the efficiency of culture marketing to the organizations producing culture-art products and to the companies utilizing art and suggest the practical viewpoints to the culture and art policy agencies. The methodology used was to take an in-depth look at the consumer value cognition and benefits of culture-art products in contemporary consumption culture from a social context by conducting a total of 12 Focus Group Interviews, consisting of 58 males and females in their 10s~50s who can represent culture-art product consumers. The culture-art products refer to the artist's spiritual, actual act of creating or to the end products with economic exchange value. They are also sense goods and merit goods that affect the mental state of consumers. By looking at culture-art products as consumer merit goods, this research examined consumer value cognition of culture-art products based on the characteristics culture-art products. As a result, this research determined that consumers view culture-art products largely as 'aesthetic and sensuous merit goods', 'actual and individual merit goods', and 'social public property'. As 'aesthetic and sensuous merit goods', culture-art products are considered as the products of an artist's creative activities; as 'social public property', culture-art products have a public value in terms of ownership; and as 'actual and individual merit goods', culture-art products act on the spirit and reality of a consumer in terms of consumption. As a result of analyzing the benefits of culture-art products based on the above-mentioned consumer value cognition, it was observed that the benefits of culture-art-product consumption are chiefly divided into 'aesthetic character-oriented', 'social relationships-oriented', and 'individual benefits-oriented' depending on how consumers see culture-art products. A 3-conceptional structures model was constructed according to the relationship between consumer value cognition of culture-art products and the benefits. This research revealed that consumers who pursue the aesthetic value or sense of beauty as the central reason experience culture-art products themselves, enjoy intellectual quests, and pursue their satisfaction by expressing affection for and interests in culture-art products. On the other hand, consumers who pursue social value as the central reason as a means of communication by perceiving culture-art products as a public property of society, pursue sympathy with people close to them through the symbolic power of culture-art product consumption or the joy of self-display. Consumers who perceive art products as spiritual and actual merit goods and pursue consumer value as a central reason want to express their own personality, develop themselves, and differentiate themselves or identify themselves with others in the context of social relations for the ultimate goal of living a happy and satisfied life while pursuing to satisfy imminent and actual necessities as emotional stability and rest. The fact that culture-art product benefits could vary according to how a consumer perceives them implies that consumer value cognition of culture-art products and their benefits significant affect consumers' decision in choosing and consuming various culture-art products. It turned out that such benefits from the consumption of culture-art products reflect the complex contemporary consumption culture of rational consumption, symbolic consumption, experiential consumption, and social reflective consumption. This research identified conceptional structures of consumer value cognition on culture-art products and benefits that can be used for studying and understanding culture-art products consumers who pursue a variety of consumption values. They can also be used by private companies in utilizing art, as well as by national agencies in enhancing the population's quality of life. However, since this research could only conceptually grasp consumer perception of culture-art products and reveal the dimension of classification due to its own limitations arising from characteristic investigation, quantitative data on the benefits of culture-art product consumers should be measured in future studies through a quantitative investigation, while using the value cognition of culture-art products and the individual characteristics of consumers as variables based on this research.