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Research Paper | Computer Technology | India | Volume 11 Issue 1, January 2022 | Popularity: 4.8 / 10

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Automated Item Recommendation Systems for Retail Stores

Yogananda Domlur Seetharama

Abstract: This research paper considers the approaches for recommending items to customers in retail stores and the utilization of machine learning interfaces and control circuits to improve the shopping experience. The paper explains how to hear the music of customer preferences by holding portable electronic devices and using proximity selling. The critical processes of the system involve data gathering, position identification, nearness assessment, and recommendation creation, with customers? data processing performed with machine learning techniques to offer customers relevant recommendations in real time. An essential aspect of the system?s functioning is considering the proximity of items placed in the store and offering the client to buy more. Audio and video advertisement, artificial intelligence tools, personalized marketing, and augmented reality are analyzed to reveal ways to increase customer satisfaction and loyalty. The ethical use of customer data and the future of AI and machine learning in retail are also highlighted. The paper concludes that automated recommendation systems, one of the emerging technologies in retail management, can increase buy - side satisfaction, tailor recommendations for customers, and stimulate sales. These systems will benefit the future development of retail environments as customers? expectations remain high and the competitive advantage remains paramount. The study specifically highlights the need for unfaltering change in this area of retailing and the proficient use of new technologies.

Keywords: Automated Recommendation, Retail Stores, Machine Learning, Control Circuits, Proximity - Based, Recommendations, Personalized Shopping Experience, AI, Augmented Reality (AR)

Edition: Volume 11 Issue 1, January 2022

Pages: 1653 - 1663

DOI: https://www.doi.org/10.21275/SR24809044235

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