Title: Optimizing E-Commerce Through AI-Powered Intelligent Sorting and Personalization
Authors: Jihad Mahfouz, Samy S. Abu-Naser
Volume: 10
Issue: 7
Pages: 45-51
Publication Date: 2026/07/28
Abstract:
The rapid growth of e-commerce platforms has created significant challenges in organizing and presenting products to customers effectively. Traditional sorting methods, such as sorting by price or popularity, often fail to consider individual customer preferences. Artificial Intelligence (AI) has emerged as a powerful solution for enhancing product sorting through personalized recommendations and intelligent ranking systems. This paper explores the role of AI-powered sorting in e-commerce, focusing on personalization and performance optimization. The study reviews existing literature, discusses common AI techniques used in product ranking, proposes a conceptual methodology, and analyses the expected impact of AI-driven sorting systems on customer satisfaction and business performance. The findings indicate that AI-based sorting can significantly improve user experience, increase conversion rates, and optimize operational efficiency in online marketplaces.