Customer Churn Prediction & Prevention Using Machine Learning

The Problem

According to reports, cost of acquiring new customers is considerably higher than retaining existing customers. Churn also equates to lost revenue. Even a 1% churn rate monthly can quickly compound and translate to 12% churn rate annually. Customer churn therefore is a critical business problem for organizations. So how can organizations prevent customer churn from happening.

Solution

In order to prevent customer churn, it is important that an organization be able to predict the customers who are likely to churn so that they can do something about it. Machine Learning models deployed on Kranium can be used to analyse customer data to discover patterns of potential churners and use this understanding to segment at-risk customers. Organizations can then take appropriate actions to gain back the trust of such customers.

Preventing customer churn in a timely manner can help organizations retain customers, increase profits, improve customer experience, and optimize their products and services.