Churn prediction is essential as It is more expensive to attract new customers than it is to keep existing ones, which makes reducing churn a priority. Customer retention is key so it is important to get an understanding of why customers churn. The information that comes from calculating churn rates can give vital insights, but this process can be time and resource consuming when done manually across a company.
The probability of churn can be estimated by various Machine Learning models. Using past purchase and client behaviour data, a model can help to detect the factors of client attrition, identify those who are at high risk of leaving and show which actions should be used to increase retention.