Real time Project in Data Science | Customer Churn-ML Model I A step by step guide | KSR Datavizon

Retaining existing customers is vital for organizations looking to grow their business without relying too heavily on the significantly higher cost of acquiring new customers. Marketing, sales, and customer retention departments need to work to make sure customers are satisfied, provide them with incentives, and present offers at the right time to reduce churn. Machine Learning can help marketing, sales, and customer retention teams determine the best incentive and the right time to make an offer to minimize customer turnover.

In this tutorial you will learn how to train a machine learning model and make predictions in simple steps: Here we build a model to predict how likely a customer will churn by analyzing its characteristics:
(1) demographic information,
(2) account information, and
(3) services information.

The objective is to obtain a data-driven solution that will allow us to reduce churn rates and, as a consequence, to increase customer satisfaction and corporation revenue.

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