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.
Analyzing and predicting purchase intent in e-commerce: Anonymous vs
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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.