Akademik Veri Yönetim Sistemi
5th International Artificial Intelligence and Data Science Congress, Zonguldak, Türkiye, 24 - 25 Nisan 2025, ss.1, (Tam Metin Bildiri)
Predicting customer purchasing behavior has become an essential part of modern e-commerce operations. By utilizing artificial intelligence (AI) models, businesses can gain insights into customer patterns, enhance marketing strategies, and streamline inventory control. This article outlines and analyzes three major AI approaches commonly used to predict purchasing behavior: decision trees, support vector machines (SVMs), and neural networks. This article focuses on reviewing relevant literature, discussing methodological steps, and examining potential trade-offs between model simplicity, interpretability, and resource requirements. Rather than focusing on specific empirical results, this article provides conceptual guidance and practical recommendations for e-commerce practitioners on which model to choose. It also outlines future directions in AI-driven customer behavior research, highlighting the importance of model interpretability, data integration, and ethical implications.