ChatGPT prompt for building a SQL query to analyze customer churn patterns

Act as a senior data analyst specializing in customer retention. I need SQL queries to analyze customer churn patterns in my database. Database context: - Database type: [PostgreSQL / MySQL / BigQuery / etc.] - Key tables: customers (id, signup_date, plan_type, status), orders (id, customer_id, order_date, amount), activity_logs (customer_id, event_type, event_date) - Churn definition: [e.g., no activity in 90 days / subscription cancelled / etc.] - Time period to analyze: [e.g., last 12 months] Write SQL queries for: 1. Monthly churn rate over the analysis period 2. Churn by customer segment (plan type, signup cohort, geography if available) 3. Average customer lifetime before churning 4. Revenue impact of churn (lost MRR per month) 5. Pre-churn behavior patterns — what do churned customers do differently in their last 30 days compared to retained customers? 6. Cohort retention analysis — for each signup month, what percentage remain active at month 1, 3, 6, 12? 7. At-risk customer identification — flag currently active customers whose recent behavior matches churn patterns For each query: - Include clear comments explaining the logic - Use CTEs for readability - Note any performance considerations for large datasets - Explain what the results mean and how to act on them End with recommendations for building a churn prediction dashboard.