AI in Retail: Delivering Personalized Experiences to Scale
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Informative Article | Engineering Science | India | Volume 9 Issue 1, January 2020 | Popularity: 6.1 / 10


     

AI in Retail: Delivering Personalized Experiences to Scale

Bala Vignesh Charllo


Abstract: The rapid advancement of artificial intelligence (AI) is revolutionizing the retail industry by enabling businesses to deliver highly personalized experiences at scale. This paper explores the transformative role of AI in retail, focusing on its ability to tailor customer interactions, optimize operations, and enhance overall shopping experiences. By leveraging AI technologies such as machine learning, natural language processing, and recommendation systems, retailers are able to meet the growing demand for personalization across diverse customer segments. The discussion highlights the scalability of these AI - driven solutions, which allow for individualized customer engagement on a mass scale, thereby enhancing customer satisfaction and driving business growth. The paper also considers future trends and innovations in AI, as well as the ethical challenges associated with data privacy and algorithmic fairness. Ultimately, the paper underscores the significance of AI in reshaping the retail landscape, providing a competitive edge to businesses and setting the stage for continued innovation in the industry.


Keywords: artificial intelligence, retail industry, personalized experiences, customer satisfaction, data privacy


Edition: Volume 9 Issue 1, January 2020


Pages: 1968 - 1973


DOI: https://www.doi.org/10.21275/SR24829154824


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Bala Vignesh Charllo, "AI in Retail: Delivering Personalized Experiences to Scale", International Journal of Science and Research (IJSR), Volume 9 Issue 1, January 2020, pp. 1968-1973, https://www.ijsr.net/getabstract.php?paperid=SR24829154824, DOI: https://www.doi.org/10.21275/SR24829154824

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