Every business is keen to know the reasons behind the customers who left and mainly it becomes a important task to atleast retain the existing customers.

Than implemeting plans to new customer, it is the existing customer who can generate additional customer referrals.

Customer retention can be achieved with good customer service and products. But the most effective way for a company to prevent attrition of customers is to truly know them.

The vast volumes of data collected about customers can be used to build churn prediction models.

Knowing who is most likely to defect means that a company can prioritise focused marketing efforts on that subset of their customer base.

Preventing customer churn is critically important to the telecommunications sector, as the barriers to entry for switching services are so low.

we will examine here:

customer data with the aim of building and comparing several customer churn prediction models.