Any business wants to maximize the number of customers. To achieve this goal, it is important not only to try to attract new ones but also to retain existing ones. Retaining a client will cost the company less than attracting a new one. In addition, a new client may be weakly interested in business services, and it will be difficult to collaborate with him, while old clients already have the necessary data on the interaction with the service. Accordingly, we can react in time and try to keep the client who wants to leave. Based on the data about the services that the client uses, we can make him an exclusive offer, trying to change his decision to leave the operator. This will make the task of retention easier to implement than the task of attracting new users, about which we do not know anything yet. These data from a telecommunications company contains information about six thousand users, their demographic characteristics, the services they use, the duration of using the operator's services, the method of payment, and the amount of payment. The task is to analyze and take insights from data and identify what is causing the customers churn.
Access jupyter notebook: https://edugvs.github.io/Project02-Customer-Churn-Analysis/index.html
Original database on Kaggle: https://www.kaggle.com/radmirzosimov/telecom-users-dataset
