Telecom-churn

The company is facing increased customer churn, especially among high-value customers who contribute 80% of its revenue. To address this, the goal is to predict which customers are likely to churn in the ninth month based on the past three months’ data. Key factors like demographics, usage patterns, service quality, and complaints will be analyzed to understand the causes of churn. The focus will be on high-value customers, using machine learning models to predict churn and identify the most important factors influencing customer decisions. This will help the company take action to retain valuable customers and improve overall satisfaction.