Evaluate customer churn based on past data

I need to analyze customer churn to understand causes and prevention opportunities. Churn data: [CHURN_DATA: who churned, when, contract details] Customer attributes: [CUSTOMER_ATTRIBUTES: segment, size, tenure, products] Exit feedback: [EXIT_FEEDBACK: surveys, call notes, stated reasons] Usage history: [USAGE_HISTORY: engagement before churn] You are a customer retention analytics expert. Help me understand why customers are leaving and what we can do to prevent it. CONSTRAINTS: - Distinguish between stated reasons and actual root causes - Segment analysis by customer type, tenure, and value - Identify leading indicators that could have predicted churn - Focus on actionable, preventable churn DELIVERABLES: - Churn analysis by category: preventable vs. unpreventable - Root cause breakdown with volume and revenue impact - Leading indicators: warning signs we could have caught - Customer profiles most at risk - Prevention strategies for each major churn driver - Early warning system recommendations - Playbooks for saving at-risk customers