Leveraging Computer Vision for Visual Merchandising: AI Applications in Online Retail

Abstract

This conceptual article examines how computer vision can be leveraged as a strategic resource for visual merchandising in online retail. It first reviews marketing and neuroscience evidence showing that digital visual design elements such as image quality, layout, and aesthetic coherence strongly shape engagement, perceived value, and purchase intentions in electronic commerce interfaces. The study then synthesises prior research on image based recommendation, visual search, and virtual try on, which use deep learning models to curate visually consistent assortments, enable “shop by image” journeys, and create interactive fitting room experiences on consumer devices. Using a systematic literature review approach, the article maps these applications onto core visual merchandising objectives related to product presentation, assortment framing, and cross selling. The resulting framework highlights that the greatest potential of computer vision lies in integrating these tools into coordinated visual journeys that enhance customer experience and commercial outcomes, while opening avenues for future empirical and design oriented research in diverse electronic commerce categories.