Implement clustering algorithms to segment customers based on their usage patterns, enabling the identification of distinct customer groups with similar behaviors for targeted marketing strategies.

Apply association rule mining to discover relationships between the service features used by customers and their demographic or behavioral attributes, facilitating personalized service recommendations.

Utilize predictive analytics to forecast customer churn, identifying at-risk customers for targeted retention campaigns, thereby reducing potential revenue loss.

Combine clustering algorithms, association rule mining, and predictive analytics to segment customers, uncover feature relationships, and predict churn, providing a holistic view of customer usage patterns and opportunities for revenue growth.