Predicting Customer Lifetime Value in Marketing Analytics

Understanding how much a customer is worth over time is the cornerstone of profitable marketing, yet many businesses struggle to accurately predict this value. This text-only course guides you through the core concepts of Customer Lifetime Value (CLV) and how to model it effectively. By studying these comprehensive written modules, you will transition from basic historical calculations to predictive modeling. You will understand how to leverage transaction data to forecast future customer behavior, optimize acquisition costs, and segment high-value cohorts using modern analytics approaches. What you'll learn: Understand the fundamental terminology, metrics, and business significance of Customer Lifetime Value; Calculate historical CLV using standard formulas and cohort analysis; Explore predictive modeling techniques, including probabilistic models and machine learning approaches; Apply data preparation workflows to clean and structure transactional data for modeling; Evaluate model performance using key predictive analytics validation metrics; Translate CLV insights into actionable marketing strategies, such as budget allocation and customer retention. The course begins with essential terminology and foundational definitions before moving into step-by-step written explanations of predictive modeling workflows. You will reinforce your learning through conceptual reviews and written practice exercises designed to test your understanding. This course is designed for aspiring marketing analysts, data enthusiasts, and business professionals who want to understand predictive customer analytics from the ground up, with no advanced mathematical prerequisites required. Start reading today to unlock the power of predictive customer analytics.