Big data in the retail world: customer segmentation and recommender system in a European supermarket chain

• Autor: Cam Gensollen, César Rogelio
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad de Lima
• Repositorio: Revistas - Universidad de Lima
• Lenguaje: español
• OAI Identifier: oai:revistas.ulima.edu.pe:article/5808
• Enlace del recurso: https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/5808
• Nivel de acceso: acceso abierto
• Materia: retail; segmentation; recommender system; big data; machine learning; segmentación; sistema de recomendación; aprendizaje automático

In this research, we want to present the concepts and techniques used in a big data project for a European supermarket company, through a customer segmentation proposal, using the k-means algorithm, and a recommender system, via Light FM library. The main conclusions include the importance of adequately defining the problem to be solved, the correct use of the big data infrastructure, the relevance of the exploratory analysis of the dataset and its pre-processing, as well as the use of the TDSP methodology (Team Data Science Process), oriented to big data projects.