In a very competitive mobile telecommunication industry business environment, marketing managers need a business intelligence model that allows them to maintain an optimal (at least a near optimal) level of churners very effectively and efficiently while minimizing the costs throughout their marketing programs. As a first step toward optimal churn management program for marketing managers, this...

Churn prediction aims to detect customers intended to leave a service provider. Retaining one customer costs an organization from 5 to 10 times than gaining a new one. Predictive models can provide correct identification of possible churners in the near future in order to provide a retention solution. This paper presents a new prediction model based on Data Mining (DM) techniques. The proposed ...

Customer churn is a main concern of most firms in all industries. The aim of customer churn prediction is detecting customers with high tendency to leave a company. Although, many modeling techniques have been used in the field of churn prediction, performance of ensemble methods has not been thoroughly investigated yet. Therefore, in this paper, we perform a comparative assessment of the perfo...

Customer temporal behavioral data was represented as images in order to perform churn prediction by leveraging deep learning architectures prominent in image classification. Supervised learning was performed on labeled data of over 6 million customers using deep convolutional neural networks, which achieved an AUC of 0.743 on the test dataset using no more than 12 temporal features for each cus...

Customer defection or "churn" rate is critically important since it leads to serious business loss. Therefore, many telecommunication companies and operators have increased their concern about churn management and investigated statistical and data mining based approaches which can help in identifying customer churn. In this paper, a churn prediction framework is proposed aiming at enhancing the...

Machine learning, or as it is also called automated a special subfield of scientific information technologies. The name "machine learning" refers to the detection meaningful patterns in large data sets. learning gaining importance many different areas economy. One those prediction and prevention consumer churn. There are two basic types churn, complete churn partial used determine most signific...

A huge number of customer data was collected by using of information technology in healthcare context. It is very important for healthcare providers to analyze this type of big data following the logic of customer relationship management. So here we propose an integration framework which can realize the customer segmentation and customer churn prediction together. To efficiently segment the cus...