This article is devoted to the study of the role and significance of recommendation systems in e-commerce. The main types and methods of implementing recommendation systems are considered, as well as their impact on business efficiency, conversion growth, and user experience improvement. Special attention is paid to the adaptation and integration of such systems into modern IT products. The work also discusses existing technological challenges and the main directions of their development.
e-commerce, recommendation systems, IT products, collaborative filtering, personalization, behavioral analysis, digital transformation
1. Rikardo, B. A., Nil'sen, A. Sovremennye podhody k postroeniyu rekomendatel'nyh sistem // Zhurnal «Informacionnye tehnologii i analiz dannyh». – 2023. – № 4. – S. 45–58.
2. Gusev, I. V. Mashinnoe obuchenie v sistemah personalizacii internet-kommercii // Elektronnaya kommerciya i cifrovye platformy. – 2024. – T. 12, № 2. – S. 33–47.
3. Kuznecov, A. S., Smirnova, E. Yu. Analiz effektivnosti rekomendatel'nyh sistem v onlayn-torgovle // Vestnik prikladnoy informatiki. – 2023. – № 1. – S. 19–28.
4. Davydova, N. P. Primenenie metodov kollaborativnoy fil'tracii v cifrovom marketinge // Informacionnye tehnologii i programmirovanie. – 2024. – URL: https://cyberleninka.ru (data obrascheniya: 10.10.2025).
5. Voronov, M. E., Levina, T. S. Rekomendatel'nye sistemy kak instrument povysheniya konversii v elektronnoy kommercii // Sovremennye tehnologii v ekonomike i biznese. – 2023. – № 6. – S. 57–66.
6. Goh, H. A. Deep Learning Approaches for E-Commerce Recommendation Systems // International Journal of Computational Intelligence Systems. – Springer, 2023.
7. Nadukuda, N. AI-Driven Personalization in E-Commerce: Techniques and Trends // International Journal of Artificial Intelligence & Applications (IJAIAP). – 2023. – URL: https://iaeme.com (data obrascheniya: 10.10.2025).
