# LCM-Promo: An LLM-Based Uplift Model for Promotion Allocation

**Authors:** Nesta Midavaine, Floris Fok, Paulo Mendes, Joao Silva, Önder Akaçık, Dimas Lima, Zülküf Genç  
**Lab:** Prosus AI · **Published:** 27 Oct 2026 · **Upvotes:** 5  
**Links:** [arXiv](https://arxiv.org/abs/2610.37570) · [PDF](https://arxiv.org/pdf/2610.37570) · [This page](https://omen-bit.github.io/ai-paper-daily/paper/2610.37570.html)

## Key numbers

- **1%**: LCM-Promo increased conversion by 1% and reduced promotion cost by 6% relative to the Segment-EMA production…
- **6%**: …increased conversion by 1% and reduced promotion cost by 6% relative to the Segment-EMA production baseline.

## Abstract

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.

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