Exploring Consumer Perception and Adoption of AI-Enabled Smart Mirrors in Retail Shopping Experiences, A Study based in Navi Mumbai Area
In recent years, artificial intelligence (AI) has significantly transformed the retail industry, introducing innovative solutions that enhance customer experiences and improve business efficiency. One such advancement is the development of AI-enabled smart mirrors, which are becoming increasingly popular in retail stores, particularly in the fashion and beauty sectors. These smart mirrors use advanced AI technologies, including computer vision, augmented reality (AR), and machine learning, to offer customers a more interactive and personalized shopping experience (Xu et al., 2022). By allowing shoppers to virtually try on clothing, accessories, and makeup without physically wearing them, smart mirrors help customers make more informed purchasing decisions while saving time and effort (Lee & Kim, 2021). Smart mirrors are equipped with high-definition cameras and AI-driven software that analyze a shopper’s body shape, facial features, and preferences to recommend products that suit them best (Chaudhary et al., 2023). For example, in fashion retail, a customer can stand in front of a smart mirror, which will digitally overlay different outfits onto their reflection, enabling them to see how they look in various styles and colors without having to change clothes. Similarly, in the beauty industry, smart mirrors can apply virtual makeup, allowing customers to test different shades of lipstick, eyeshadow, and foundation before making a purchase. This not only enhances convenience but also minimizes hygiene concerns associated with traditional product testing (Smith & Johnson, 2020).
Institutions
- American Marketing Association (US)
- Bharat Serums and Vaccines (India) (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-30
- DOI
- https://doi.org/10.5281/zenodo.15710643
- Primary Topic
- Consumer Retail Behavior Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00