Optimización de estrategias comerciales mediante minería de datos: un estudio de caso en la identificación de patrones de compra en retail.

Abstract

This degree work focused on the optimization of commercial strategies in the retail sector through data mining, with emphasis on the identification of purchasing patterns. The importance of data quality and the integration of various sources of information to obtain accurate results in the analysis of consumer behavior was analyzed. The methodology adopted was practical, descriptive and correlational, aimed at solving specific retail problems. The study included the analysis of historical sales and transaction data, which made it possible to identify consumer preferences and purchasing habits, facilitating strategic decision-making. Data sources such as point-of-sale systems and loyalty cards were used, and advanced analysis techniques such as regression, clustering, association rules, and neural networks were applied. These methodologies made it possible to extract relevant patterns and generate predictive models to anticipate consumption trends, optimize inventory management, and improve marketing campaigns.