XGBoost-Based Prediction and Evaluation Model for Enchanting Subscribers in Industrial Sector

In this paper, we propose an innovative method XGBoost to enhance the company’s engagement level with the customers based support with machine learning concepts. The trade-off between the customer needs and providing services towards them plays a major role in the service management sector. So, it is necessary to understand the customer needs, and offering better services plays a major task in today’s Internet world. Most companies cannot find the exact root cause of the minimal number of users on buying/reviewing the particular product. Also, the subscribers’ usage patterns may vary dynamically on a time-to-time basis. Most companies will earn millions and millions of revenues depending on the subscriber base and the level of engagement of their subscribers. So, it becomes necessary to evaluate the parameter for companies’ fall and make forward the progression towards the next level of enhancement for earning a good amount of revenue. Thus, the XGBoost classifier gives the idea behind the focus on the improvement of the shortfall of subscribers in the industrial management system.