National Kaohsiung University of Science and Technology

Retail media networks usually compress clickstreams into click-through, conversion, recency and similar summaries, so two shoppers with identical event counts become indistinguishable. Across three campaign waves on an anonymized omni-channel retailer's platform covering 5.2 million active members, purchase-intention inference is framed as theory-coherent hidden semi-Markov dynamics: states are declared by the Theory of Planned Behavior, the Consumer Decision Journey and the Persuasion Knowledge Model, a retrieval-augmented language model supplies a reference posterior, and a KL regularizer in the expectation step stabilizes state assignment. On n=1,008 paired test consumers the model reaches one-step purchase AUC 0.717 against 0.635 for an action-only covariate baseline.

Retail media networks usually compress clickstreams into click-through, conversion, recency and similar summaries, so two shoppers with identical event counts become indistinguishable. Across three campaign waves on an anonymized omni-channel retailer's platform covering 5.2 million active members, purchase-intention inference is framed as theory-coherent hidden semi-Markov dynamics: states are declared by the Theory of Planned Behavior, the Consumer Decision Journey and the Persuasion Knowledge Model, a retrieval-augmented language model supplies a reference posterior, and a KL regularizer in the expectation step stabilizes state assignment. On n=1,008 paired test consumers the model reaches one-step purchase AUC 0.717 against 0.635 for an action-only covariate baseline.