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Predecir la lealtad del cliente en el comercio minorista omnicanal utilizando el comportamiento de compra, los
Shima Roosta1, Seyed Jafar Sadjadi1, Ahmad Makui1
1Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
PloS one
|August 21, 2025
Resumen
Este estudio introduce un marco inteligente para predecir la lealtad del cliente en el comercio minorista omnicanal utilizando datos integrales y inteligencia artificial avanzada. Mejora la gestión de las relaciones con los clientes para una mejor retención y competitividad en el mercado.
Área de la Ciencia:
- * Análisis de negocios
- * Inteligencia artificial
- * Gestión minorista
Sus antecedentes:
- * La lealtad del cliente es crucial en el comercio minorista omnicanal competitivo, sin embargo, la investigación existente a menudo examina los factores que influyen de forma aislada.
- * Los estudios tradicionales carecen de una visión holística de los factores de lealtad dentro de entornos omnicanal flexibles.
- * Existen lagunas en la comprensión de la compleja interacción de factores que afectan a la lealtad de los clientes en las diversas plataformas minoristas.
Objetivo del estudio:
- * Desarrollar un marco analítico inteligente para predecir la lealtad del cliente en entornos minoristas omnicanal.
- * Integrar un conjunto completo de datos, incluidos datos de ventas, socioeconómicos, de comportamiento y de sentimiento.
- * Mejorar los subsistemas de gestión de relaciones con los clientes (CRM) dentro de los sistemas de información empresarial (EIS) para mejorar la toma de decisiones.
Principales métodos:
- * Utiliza un enfoque híbrido de IA que combina BERT para el análisis del sentimiento y el aprendizaje por refuerzo para el análisis del comportamiento.
- * Utiliza redes convolucionales de gráficos (GCN) y aprendizaje adaptativo para el análisis de tendencias y la predicción de lealtad.
- * Incorpora técnicas de ajuste fino para una mayor precisión predictiva a nivel individual y de vecindario.
Principales resultados:
- * El estudio proporciona un nuevo marco para predecir la lealtad del cliente utilizando datos omnicanal integrados.
- * El modelo híbrido de IA demuestra efectividad en el análisis de comportamientos y sentimientos complejos de los clientes.
- * El marco permite predicciones tanto a nivel individual como de vecindario, ofreciendo información granular.
Conclusiones:
- * El marco inteligente propuesto mejora significativamente la predicción de la lealtad del cliente en el comercio minorista omnicanal.
- * Las estrategias de CRM optimizadas a través de este marco pueden mejorar los precios, la gestión de inventario y la publicidad personalizada.
- Esta investigación contribuye en última instancia a una mayor retención de clientes y a una mayor competitividad en el mercado.
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