Customer churn is a serious problem, which critical issue encountered by large businesses and organizations. Due to the direct impact on company's revenues, particularly in sectors such as telecommunications well banking, companies are working promote ways identify of prospective consumers. Hence it vital investigate issues that influence customer yield appropriate measures diminish churn. The ...

Companies in a wide variety of industries use the customer churn prediction (CCP) process to keep their current clientele happy. Insurance companies need be able forecast enhance potency and functionality deep learning methods. Deep techniques have significant impact on improving forecasting retention. Numerous studies employ standard machine Learning strategies retention, despite fact that the...

A holistic approach, in the form of a process, is proposed in order to discover marketing intelligence from Internet data. The Internet-enabled knowledge discovery process contains the steps human resource identification, problem specification, data prospecting, domain knowledge elicitation, methodology identification, data pre-processing, pattern discovery, and knowledge post-processing. It al...

The telecommunication industry has evolved into a highly competitive market, which requires companies to put an effective customer relation approach in place. In order to increase customer relationship management, social network analysis (SNA) can be used to increase the knowledge related to the customers’ influence. SNA can improve relevant information that helps to increase the customer exper...

Churn prediction is a Big Data domain, one of the most demanding use cases recent time. It also critical indicators healthy and growing business, irrespective size or channel sales. This paper aims to develop deep learning model for customers’ churn in e-commerce, which main contribution article. The experiment was performed over real e-commerce data where 75% buyers are one-off customers. base...