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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44513
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The AI in personalized services is an online e-commerce platform that uses AI to improve the shopping experience. This system maximizes customer engagement and product discovery by combining AI-driven recommendations, automated inventory management, and an intuitive user interface. With the help of HTML, CSS, and JavaScript, the platform’s user-friendly front end ensures a smooth surfing experience. In order to offer tailored product recommendations, AI algorithms examine user behavior and preferences. Customers can effectively locate the products they want thanks to the store’s intelligent search and filtering features. Automated stock monitoring minimizes manual intervention by assisting in the dynamic management of inventory levels. Additionally, the system improves user support by integrating a chatbot driven by AI for real-time customer assistance. Reliability and trust are increased through secure payment integration, which guarantees safe transactions. Mobile phones and desktop computers are among the devices that are accessible thanks to the responsive design. Because of the platform’s scalability, future improvements like voice-based search and predictive analytics are possible. This store wants to use AI to improve sales, streamline operations, and offer a highly personalized shopping experience. Operations run smoothly thanks to the backend architecture’s support for effective data processing and management. Real-time analytics help businesses make datadriven decisions by providing insights into customer preferences. By fusing technology and user-centric design, the AI-enabled store is a major breakthrough in contemporary e-commerce.
KEYWORDS
Publication Date
4/14/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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