Problem Statement
Customer churn, also known as customer attrition, refers to the phenomenon whereby a customer leaves a company. For banks, acquiring new customers can cost five times more than satisfying and retaining existing customers.
Why?
Marketing costs to acquire new customers are high. Therefore, it is important to retain customers so that the initial investment is not wasted;
In this article, we’ll build a machine learning model using Voyance data science platform to predict how likely a customer is going to churn.
Dataset
Here’s a sample of our historical bank data
Using Voyance OMNI platform to build a model
Now that we know what the problem is and we have the required data, we can go ahead and build a model to predict customer churn.
Here’s a video demonstrating how we used this data to build a model in less than 10mins:
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