[2604.04468] What Makes a Sale? Rethinking End-to-End Seller--Buyer Retail Dynamics with LLM Agents

Computer Science > Artificial Intelligence arXiv:2604.04468 (cs) [Submitted on 6 Apr 2026] Title:What Makes a Sale? Rethinking End-to-End Seller--Buyer Retail Dynamics with LLM Agents Authors:Jeonghwan Choi, Jibin Hwang, Gyeonghun Sun, Minjeong Ban, Taewon Yun, Hyeonjae Cheon, Hwanjun Song View a PDF of the paper titled What Makes a Sale? Rethinking End-to-End Seller--Buyer Retail Dynamics with LLM Agents, by Jeonghwan Choi and 6 other authors View PDF HTML (experimental) Abstract:Evaluating retail strategies before deployment is difficult, as outcomes are determined across multiple stages, from seller-side persuasion through buyer-seller interaction to purchase decisions. However, existing retail simulators capture only partial aspects of this process and do not model cross-stage dependencies, making it difficult to assess how early decisions affect downstream outcomes. We present RetailSim, an end-to-end retail simulation framework that models this pipeline in a unified environment, explicitly designed for simulation fidelity through diverse product spaces, persona-driven agents, and multi-turn interactions. We evaluate RetailSim with a dual protocol comprising human evaluation of behavioral fidelity and meta-evaluation against real-world economic regularities, showing that it successfully reproduces key patterns such as demographic purchasing behavior, the price-demand relationship, and heterogeneous price elasticity. We further demonstrate its practical utility via dec...