Automating customer feedback in online marketplaces with retrieval augmented generation

Abstract

This paper proposes a solution for automating customer review responses in online marketplaces. The goal is to save time and resources for sellers. The proposed system combines traditional methods with Large Language Models, allowing the sellers to provide a personalized service and improve customer satisfaction. The system has been implemented and integrated with two main online marketplaces in Russia: Wildberries and Ozon. The study demonstrates promising results in terms of response quality and efficiency. In particular, the system was used to answer more than 3800 reviews for three sellers, which was estimated to be an equivalent of 120 working hours.

Keywords: Automation, LLM, RAG, E-commerce, Customer Support, Customer Service

DOI: 10.54941/ahfe1005849