A modular, LLM-executed rule engine for e-commerce session analysis achieves 56.4% accuracy on a 39-session pilot while prioritizing auditability over predictive performance.
Exploring the impact of time spent reading product informa- tion on e-commerce websites: A machine learning approach to analyze consumer behavior
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From Explicit Elements to Implicit Intent: A Predefined Library for Auditable Behavioral Inference
A modular, LLM-executed rule engine for e-commerce session analysis achieves 56.4% accuracy on a 39-session pilot while prioritizing auditability over predictive performance.