EXPLORATORY ANALYSIS ON PRODUCT SUBSTITUTION

Small businesses in Argentina, such as kiosks and microenterprises, often face challenges in managing inventory and responding to shifting customer preferences especially when certain products are unavailable. This study explores product substitution behaviors in such contexts by applying Natural Language Processing (NLP) and Large Language Models (LLMs), with the goal of informing improved inventory management practices. By combining exploratory data analysis (EDA) with demographic and consumption data, this research provides actionable insights into substitution dynamics. Customer interviews and AI-based analysis reveal nuanced behavioral patterns not captured through traditional approaches.