arXiv:2610.37570 · v1
LCM-Promo: An LLM-Based Uplift Model for Promotion Allocation
摘要
We present LCM-Promo, an LLM-based uplift model for promotion allocation. LCM-Promo is a task-specific Large Commerce Model (LCM): a finetuned LLM trained on transactional commerce data to predict user intent and promotion response. It learns monotonic promotion-response curves from production logs by interpreting single-token outputs as conversion-threshold probabilities, while conditioning on session context such as day and delivery shift. In a production A/B test on churn reactivation, LCM-Promo increased conversion by 1% and reduced promotion cost by 6% relative to the Segment-EMA production baseline.
作者备注：4 pages, 2 tables. Accepted at ECML PKDD 2026 (Industrial Track)
期刊信息：In: Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, Demo Track and Industrial Track. ECML PKDD 2026. Lecture Notes in Computer Science (LNAI), vol 16950, pp. 450-453. Springer, Cham (2026)