Gonzalez, Maria and Morales, Sofia and Torres, Javier (2025) CREATION OF AI-BASED CUSTOMER BEHAVIOR ANALYTICS MODELS TO HELP BUSINESSES IMPROVE MARKET FORECASTING AND PERSONALIZED SERVICES. International Journal of Artificial Intelligence for Digital Marketing, 2 (12). pp. 1-7. ISSN 3047-2903

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Abstract

Objective: Understanding customer behavior is fundamental to effective market forecasting and personalized service delivery. This paper presents AI-based customer behavior analytics models that leverage deep learning and clustering techniques to segment customers, predict purchasing patterns, and enable personalized marketing strategies. Method: Our multi-layered approach integrates collaborative filtering, sentiment analysis, and sequential pattern mining to create comprehensive customer profiles. Results: Validation using e-commerce datasets shows prediction accuracy improvements of 31% over traditional methods, with personalized recommendations achieving a 24% increase in conversion rates. Novelty: The research contributes to customer relationship management theory and provides actionable insights for businesses seeking to enhance customer engagement through data-driven personalization.

Item Type:	Article
Subjects:	A General Works > AI Indexes (General)
Depositing User:	admin eprints
Date Deposited:	07 May 2026 09:31
Last Modified:	07 May 2026 09:31
URI:	http://eprints.umsida.ac.id/id/eprint/16461

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