Our mobile-savvy generation frequently uses image recognition technology, with services like Google Photos and Apple’s iCloud efficiently tagging objects, people, and landmarks in photos, even without geo-tags. This capability allows for quick organization and retrieval of images from vast photo libraries.
Despite its impressive application in personal photo management, the adoption of image recognition technology in retail has been slower. However, this is changing. Retailers are beginning to leverage image recognition to improve customer experiences. For instance, customers can now take a photo of an item they like and find similar products in a store’s catalog, streamlining the discovery process that previously relied on luck, especially in large catalogs.
While visual search has been experimented with over the past five years, results have varied, and consumer skepticism remains. Yet, practical applications are emerging. For example, the Argos app in the UK and the Conforma app in France use visual search to help users find products by taking photos of items like furniture. This technology not only enhances product discovery but also allows for more accurate tagging of items, improving text search results and reducing reliance on manual processes.
Looking ahead, advancements in visual AI, such as those offered by companies like Syte, promise to further revolutionize how we discover products and interact with social media.
