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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

Transforming E-commerce and Retail: The impact of machine learning on personalization, intelligent merchandising, and discovery experiences

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Nilesh Singh *

George Mason University, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 26(01), 3469-3479

Article DOI: 10.30574/wjarr.2025.26.1.1455

DOI url: https://doi.org/10.30574/wjarr.2025.26.1.1455

Received on 07 March 2025; revised on 23 April 2025; accepted on 25 April 2025

The retail and e-commerce sectors are being reshaped by machine learning technologies that enhance customer experiences and optimize business operations. This article delves into how ML applications, particularly in search discovery systems and cloud technologies, are revolutionizing three key areas: personalization, intelligent merchandising, and innovative discovery experiences. Through advanced data processing capabilities, retailers can now deliver tailored shopping experiences, optimize inventory management, and create seamless omnichannel environments. These technological innovations enable more precise demand forecasting, dynamic pricing strategies, and sophisticated product discovery through visual and voice interfaces. Despite implementation challenges such as data quality issues and privacy considerations, emerging trends like federated learning, generative AI, autonomous retail systems, and multimodal understanding promise continued transformation of the industry landscape, offering retailers opportunities to enhance customer satisfaction while improving operational efficiency.

Personalization Engines; Intelligent Merchandising; Visual Search; Voice Commerce; Cloud-Native Architecture

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1455.pdf

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Nilesh Singh. Transforming E-commerce and Retail: The impact of machine learning on personalization, intelligent merchandising, and discovery experiences. World Journal of Advanced Research and Reviews, 2025, 26(01), 3469-3479. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1455.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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