Churn prediction methods are widely used in Customer Relationship Management and have proven to be valuable for retaining customers. To obtain a high predictive performance, recent studies rely on increasingly complex machine learning methods, such as ensemble or hybrid models. However, the more complex a model is, the more difficult it becomes to understand how decisions are actually made. Pre...

Customer churn prediction is very important for e-commerce enterprises to formulate effective customer retention measures and implement successful marketing strategies. According the characteristics of longitudinal timelines multidimensional data variables B2C customers’ shopping behaviors, this paper proposes a loss model based on combination k-means segmentation support vector machine (SVM) p...

Telecommunications’ industry evolves into a high competitive market which demands companies to put in place an effective customer relation approach. Social network analysis can be used to increase the knowledge related to the customers’ influence, arising relevant information to turns the customer experience better. SNA can be used to evaluate the customers’ links and therefore clarify distingu...

For brands, gaining new customer is more expensive than keeping an existing one. Therefore, the ability to keep customers in a brand is becoming more challenging these days. Churn happens when a customer leaves a brand to another competitor. Most of the previous work considers the problem of churn prediction using CDRs. In this paper, we use micro-posts to classify customers into churny or nonc...

Numerous valuable clients can be lost to competitors in the telecommunication industry, leading profit loss. Thus, understanding reasons for client churn is vital companies. This study aimed develop a prediction model predict telecom through customer segmentation. Data were collected from three major Chinese companies, and Fisher discriminant equations logistic regression analysis used build mo...

This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design & test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of thi...

In the telco industry, attracting new customers is no longer a good strategy since cost of retaining existing much lower. Churn management becomes instrumental in industry. As there limited study combining churn prediction and customer segmentation, this paper aims to propose an integrated analytics framework for management. There are six components framework, including data pre-processing, exp...

Multimedia on demand (MOD) is an interactive system that provides a number of value-added services in addition to traditional TV services, such as video on demand and interactive online learning. This opens a new marketing and managerial problem for the telecommunication industry to retain valuable MOD customers. Data mining techniques have been widely applied to develop customer churn predicti...