Using user data intelligence in marketing to personalize offers and increase conversion

Authors

DOI:

https://doi.org/10.35381/r.k.v10i1.4873

Keywords:

Artificial intelligence, Marketing, Data analysis, Consumer, Online learning, (UNESCO Thesaurus).

Abstract

ABSTRACT

This article was written with the aim of analyzing how data intelligence improves the personalization of offers and optimizes marketing strategies, specifically in supermarkets. The methodology used combines a mixed qualitative and quantitative approach, through surveys of seventy-five supermarket customers in Santo Domingo. The results show that segmentation based on consumer preferences influences their purchasing decisions, with a divided perception of its real impact. Artificial intelligence and machine learning are key tools for improving personalization and conversion rates, and their implementation must be more precise to achieve a significant impact. This highlights the need to improve training and technological infrastructure in companies to take advantage of the potential of these methods. In conclusion, personalized marketing strategies still need to be refined to achieve optimal results in conversion rates.

 

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References

Acosta, M., Erazo, J., & Bermeo, K. (2024). Desarrollo Sostenible y Marketing: Cómo las empresas pueden alinear sus prácticas con RSC. . Universidad y Sociedad, 232–241. https://n9.cl/evkf6

Almidón, C., Ñañez, M., Chiok, P., & Rojas, J. (2025). Evolución histórica del marketing digital y su impacto en la expansión de las PYMEs en América Latina. Revista de Historia, Ciencias Humanas y Pensamiento Crítico, 5(10), 1236-1267. doi:10.5281/zenodo.15345905

Banco Central del Ecuador. (2022). Estadísticas económicas. BCE. https://www.bce.fin.ec/estadisticas-economicas/

García, A., & Herrero, Á. (2025). Impacto del marketing predictivo basado en inteligencia artificial: Transformando estrategias de comunicación y ventas en Pymes y Startups. Revista Internacional de Cultura Visual, 17(1), 165-178. https://n9.cl/j60qh

Gigli, M., & Stella, F. (2025). Multi-armed bandits for performance marketing. International Journal of Data Science and Analytics, 20, 151-165. https://n9.cl/t2p5i

Gómez, J., Álvarez, J., Tinto, J., & Bermeo, K. (2024). E-commerce: oportunidades y desafíos para las marcas en los entornos virtuales. Universidad y Sociedad, 16(S2), 162-171. https://n9.cl/ngbzwt

Instituto nacional de estadística y censos. (2023). Ecuador en Cifras. INEC. https://www.ecuadorencifras.gob.ec/

Jauregui, R., Alca, J., Vilca, M., & Llanos, O. (2024). La inteligencia artificial en la segmentación del cliente potencial: enfoque machine . Data and Metadata, 3, 305. https://n9.cl/g4mip

Li, M., Guo, S., & Liu, R. (2025). BERT-based Consumer Sentiment Analysis for Personalized Marketing Strategies. Informatica, 49(28), 211-226. https://n9.cl/falxk

Lin, J. (2025). Application of machine learning in predicting consumer behavior and precision marketing. PLOS One, 20(5). https://n9.cl/k2rxt

Loukili, M., Messaoudi, F., El Aalouche, O., El Youbi, R., & Loukili, R. (2025). Adaptive Pricing Strategies in Digital Marketing: A Machine Learning Approach with Deep Q-Networks. Statistics, Optimization and Information Computing, 14, 1244-1251. https://n9.cl/3ntni

Medina Herrera, M. A., Erazo Álvarez, J. C., & Cordero Guzmán, D. M. (2024). El impacto de la inteligencia artificial en la personalización de la experiencia del cliente en el e-commerce. Universidad Y Sociedad, 16(4), 394–403. https://n9.cl/0oueu

Ministerio de Producción. (2025). Boletines de Comercio Exterior. Tercera Edición. https://n9.cl/g3xyn

Nguyen, H., Huynh, T., Tran, Q., Ngo, H., Pham, V., & Nguyen, H. (2025). Personal brand value extraction method to identify micro-influencer for effective digital marketing. Complex & Intelligent Systems, 11, 438. https://n9.cl/9q8wt

Ortega, D., Palencia, I., Ojeda, A., & Cortes, O. (2025). Integración de algoritmos de aprendizaje automático como herramienta innovadora para la enseñanza del mercadeo en programas de administración de empresas. Formación Universitaria, 8(4), 73-84. https://n9.cl/guhh8o

Ruiz, F., Erazo, J., & Tinto, J. (2024). La influencia de la psicología del consumidor en las estrategias de marketing. Universidad y Sociedad, 450–459. https://n9.cl/6odemb

Shi, Z., Cao, K., & Yao, X. (2025). The Impact of Digital Marketing Campaign Strategies on Consumer Buying Intention. Technical Gazette , 32(3), 819-829. https://n9.cl/nefrez

Shlash, A., Shelash, S., Al Oraini, B., Hindieh, A., Vasudevan, A., & Alshurideh, M. (2025). Decoding Consumer Behaviour: Leveraging Big Data and Machine Learning for Personalized Digital Marketing. Data and Metadata, 4(700), 1-17. https://n9.cl/rfxats

Vij, M., Vij, A., Kumar, P., Masoud, E., Al Kurdi, B., & Alzoubi, H. (2025). Artificial Intelligence in Digital Marketing Strategies in the UAE: The Mediating Role of Predictive Analytics in Enhancing Customer Conversion. International Review of Management and Marketing, 15(4), 380-387. https://n9.cl/wokwd

Published

2025-12-01

How to Cite

Cumbajín-Torres, J. S., & Cordero-Guzmán, D. M. (2025). Using user data intelligence in marketing to personalize offers and increase conversion. Revista Arbitrada Interdisciplinaria Koinonía, 10(1), 879–898. https://doi.org/10.35381/r.k.v10i1.4873

Issue

Section

De Investigación