Customer Churn 

In a Meeting

Keeping existing customers is five times cheaper than the cost of attaining new ones.For this reason, marketing executives often find themselves trying to estimate the likelihood of customer churn and finding the necessary actions to minimize the churn rate.

Customer Churn Prediction uses Machine Learning to predict churn probability and helps find patterns in existing data associated with the predicted churn rate.

This information will empower your organization with actionable intelligence to improve customer retention and profit margins.

Why do we need Customer Churn Prediction?

The impact of losing a customer is substantial and long reaching.

Impacts include:

  • Lost Sales and Revenue

  • Opportunities for Competition

  • Lost Brand Ambassadors

  • Missing long term Customer Acquisition Goals


Increasing customer retention by 


increases profits by 



Improve Customer Retention

Proactively launch campaigns and strategies to abate customer attrition


Gain Actionable Intelligence

Know the effects of seasonality on customer churn and the success of campaigns and strategies


Reduce Costs

It is more profitable to keep existing customers than to acquire new ones