This article was published as a part of the Data Science Blogathon. Customer churn or attrition is one of the most crucial problems for any business that directly sells or serves customers Be it Telecom service providers, eCommerce or SaaS businesses it is important to track and analyse how many customers are leaving the platform and how many are sticking and the reasons behind them. Knowing customer behaviour can greatly enhance decision-making processes and can further help reduce churn to improve profitability. In this article, we are going to analyse an eCommerce dataset and find the best model to predict customer churn. But before delving into analysis let's have a brief look at what is churn Customer churn can be defined as the rate at which customers leave a platform or service.