Customer Loyalty Through Machine Learning: A Bibliometric Analysis: Research Trends, Collaboration Patterns, and Keyword Dynamics

Enriquez-Maguiña M.W.; Rodriguez C. · 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025 (2025) · DOI: 10.1109/cicn67655.2025.11367995

Resumen

Machine learning (ML) has demonstrated outstanding potential for enhancing customer-facing business processes. This study aimed to examine how ML can be used in the development of customer loyalty strategies. To this end, a bibliometric analysis was performed on the Scopus database, setting the time limit as publications made between 2020 and 2025. The bibliometric analysis concluded that publications on ML and customer loyalty experienced an increase of 363.64% since 2020. Also, the main institutions with the most published documents were Indian, while the publications were mainly in Q4 and Q1 journals. The country analysis revealed that the most productive country on the subject was Australia (with a per capita index of 0.770). Also, the main topics were: (i) customer relationship in e-commerce; (ii) optimization through machine learning; (iii) customer churn; (iv) applications in the financial sector, and (v) Deep Learning and customer prediction. It is concluded that ML applied to customer loyalty is an emerging topic that has gained the interest of the scientific and business communities.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional Federico Villarreal