Makine Öğrenmesi Yöntemleriyle Müşteri Kaybı Analizi

OpenAlex · İngilizce

Purpose The purpose of this paper is to provide a detailed analysis of the usage pattern of non‐revenue earning customers (NREC) who cause revenue churn in the company and are susceptible to churn in the near future. These NREC customers were analyzed to discern a pattern in their usage and to serve as proactive measure to prevent customer churn. Design/methodology/approach Data from a leading telecom service provider were analyzed. The company has around seven lakh consumer mobile users. Within the seven lakhs consumer mobile users around two lakh customers are active users, i.e. revenue earning customers. This group of active customers also consists of around 37,388 customers who move to dormant state (from revenue earning to non‐revenue earning) every month. These customers were analyzed to understand their susceptibility to churn. Findings Analysis of revenue dump data indicates consumers with overall usage revenue per minute greater than 75 paise (USD 0.01) and those with greater usage of value added services are susceptible to churn. Also based on the nature of calls, churn occurs with the subscribers making more calls to other networks rather than to the same network. Research limitations/implications In a fiercely competitive market, service providers constantly focus on customer retention. The study has high importance as it helps to find out the customers who are likely to churn. This would help telecom companies create proactive rather than reactive strategies toward customer churn. Originality/value Earlier studies identified the reasons for customer churn and attributed the same to it. The authors propose that prior to customer churn there is a distinct shift in his/her usage pattern with the current service provider and this behavior is termed revenue churn. This revenue churn ultimately leads to customer churn from the network. This revenue churn is not explored much in detail in the literature.