Implementing advanced analytical capabilities requires systematic planning and execution across multiple organizational dimensions. Many initiatives fail not from technical limitations but from overlooking critical preparatory steps or rushing past foundational requirements. This comprehensive checklist provides a structured framework for organizations pursuing sophisticated customer value prediction, ensuring that each essential element receives appropriate attention before, during, and after deployment. Organizations embarking on AI Lifetime Value Modeling initiatives benefit from methodical preparation that addresses data infrastructure, technical capabilities, organizational readiness, and governance frameworks. This checklist distills lessons from dozens of implementations across industries, highlighting both obvious requirements and subtle considerations that frequently determine success or failure. Each item includes rationale explaining why it matters and what risks emerge whe...