Título: An Adaptive Clustering -Based Customer Loyalty Score for Modeling of Customers’ Behavior
Autores: Marcello Eduardo Mônaco, Alex Torquato Souza Carneiro, Alan Felipe R. Reggi de Oliveira, Gabriely Fagundes O. Martins & Nicoll y Nascimento A. Trajano
Resumo: A customer loyalty score indicates the strength of the relationship between a customer and a seller, e.g., branches, makers, and stores. Conventional loyalty scores are calculated through linear mathematical models, for example, a linear equation that returns the score as a weighted sum of the Recency, Frequency, and Money values obtained from the RFM approach. Linear models present several restrictions for customer segmentation because they associate very close scores with customers in distinct patterns of Recency, Frequency, and Money. In this work, we introduce a novel customer loyalty model based on clustering that calculates the loyalty of a customer according to his/her adherence to each cluster. The obtained results suggest our proposal yields a discriminative score that “summarizes” the strength of the relationship between customers and sellers.
Palavras-chave: customer behavior; customer profiles; clustering; mathematical analysis.
Páginas: 7
Código DOI: 10.21528/CBIC2025-1175661
Artigo em PDF: CBIC_2025_paper1175661.pdf
Arquivo BibTeX:
CBIC_2025_1175661.bib