Prediction of Dynamic Churn using Azure and Machine Learning

Customers are becoming more drawn to the quality of service (QoS) offered by businesses in the present. Yet, the greater rivalry is shown in present days in offering clients technologically cutting-edge QoS. Yet, effective customer relationship management systems can help the organization attract preserve client connections, new clients, and increase customer loyalty by increasing revenue for business operations. The current proposed methodology mainly consisting of two components: Machine Learning and Cloud computing. The customer churn is predicted using the machine leaning techniques and further the SMS is sent to the customers who may have chances to unsubscribe from the network using Azure cloud. Furthermore, the client retention methods can benefit greatly from the use of machine learning models like SVM and RF algorithms.