AI-Driven Personalization and Its Impact on Consumer Decision-Making: Experimental Evidence
DOI:
https://doi.org/10.68337/cpsm.v1.i2.2026-030Keywords:
AI personalization, hybrid learning, consumer behavior, machine learning, deep learning, reinforcement learning, decision-makingAbstract
Artificial intelligence (AI) has changed how people engage with digital content and services by personalizing recommendations, content, and pricing strategies. The success of such personalization depends on how different learning paradigms are combined. This paper proposes a hybrid learning model that combines machine learning (ML), deep learning (DL), and reinforcement learning (RL) to improve personalized consumer experiences. An experiment with 300 participants was carried out to test the effect of AI-driven personalization on consumer decision-making. The findings indicate that hybrid learning is much more effective than conventional personalization methods in improving engagement, trust, and purchase intention. The paper adds empirical evidence to the growing literature on AI personalization and offers practical suggestions to marketers and platform designers.
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The data supporting the findings of this study are available from the corresponding author upon reasonable request.Conference Proceedings Volume
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