IMPLEMENTING ARTIFICIAL VISUAL SEARCH ON E-COMMERCE APP
Abstract
Visual search powered by AI is one of the innovations of the rapidly evolving e-commerce industry that helps to enhance the user’s experience and optimize processes. Paying special attention to the role and impact of AI for visual search mechanisms in supporting e-commerce this research explores the directions for engaging and changing the approaches to customers’ experience. The product search queries have shifted from word queries to photo based queries with help of visual search technology which comprises deep learning algorithms, computer vision and also the natural language processing. It means that this technology can decrease the difficulty of buying process and make it dependent not on exact keywords by using brilliant analysis of the visual content and providing very precise and relevant results. By using AI visual search, intuitive and clear interfaces of the search are provided, the level of personalization is improved, and the conversion rate is higher with less cart abandonment. The research also describes the technological challenges such as the need for considerable amounts of annotated data and computational resources among other things and outlines possible solutions to these challenges. The outcomes demonstrated the transformational impact of AI visual search technology on e-commerce business and contribute to the application of the technology to meet modern shoppers’ expectations.
Full-Text Access Notice
In accordance with the NERD Policy on promoting peer-reviewed publication, public access to the full text of a project, thesis or dissertation is restricted for three years, allowing the author and supervisors sufficient time to pursue peer-reviewed publication.
During this period, researchers with legitimate academic or research purposes may request authorisation directly from the author to enable NERD to release the indexed full texts of the work using the form below.