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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17275611
Primary Topic
Oil Palm Production and Sustainability
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Oil Palm Production and Sustainability
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
George Mason University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Oil Palm Production and Sustainability
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Transforming E-commerce and Retail: The impact of machine learning on personalization, intelligent merchandising, and discovery experiences · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS