Act as a senior financial data scientist with 10+ years of experience in predictive analytics. Your task is to develop a robust model to predict customer lifetime value (CLV) for a [BANK/INVESTMENT FIRM/INSURANCE COMPANY]. The model should incorporate [TRANSACTION HISTORY/DEMOGRAPHIC DATA/BEHAVIORAL PATTERNS] and account for variables such as [MARKET TRENDS/ECONOMIC INDICATORS/CUSTOMER CHURN RATES]. Provide a detailed analysis of the key drivers of CLV, actionable insights to improve retention, and a visualization of projected revenue over [1/3/5] years. Ensure the model is scalable, interpretable, and validated using [REGRESSION ANALYSIS/MACHINE LEARNING TECHNIQUES].