Best Practices In ML Observability for Customer Lifetime Value (LTV) Models

Customer lifetime value (LTV) is a crucial metric to evaluate a company's overall sales motion, especially in non-contractual sectors like consumer packaged goods or retail. LTV models predict future purchasing behavior and help increase profitability by identifying valuable customers. These models use machine learning algorithms to analyze patterns of engagement based on predictions. Monitoring and observability are essential for LTV models as they must iterate and quickly estimate long-term value with delayed or no ground truth data. ML observability platforms should set up baseline monitors, evaluate feature, model, and actual/ground truth drift, and measure model performance to improve overall business outcomes.