Case studies and real-world examples
In this section, we will explore two prominent use cases of ML: customer churn prediction and fraud detection. These examples demonstrate the practical applications of ML techniques in addressing real-world challenges and achieving significant business value.
Customer churn prediction
Customer churn refers to the phenomenon where customers discontinue their relationship with a company, typically by canceling a subscription or switching to a competitor. Predicting customer churn is crucial for businesses as it allows them to proactively identify customers who are at risk of leaving and take appropriate actions to retain them. ML models can analyze various customer attributes and behavior patterns to predict churn likelihood. Let’s dive into a customer churn prediction case study.
Case study – telecommunications company
A telecommunications company wants to reduce customer churn by predicting which customers are most likely...
