Retail Innovation Visual AI Blog No Longer a Novelty: The Evolution of Visual Search In the years since its emergence, and as technology and consumer demands evolve, visual search is no longer a “nice-to-have.” It’s quickly become a crucial part of the customer experience for all shoppers, not just digital natives. Ofer Holtzman March 1, 2021 6 Min Read Not so long ago, visual search was considered a novelty for eCommerce sites — a shiny new toy that could attract a budding class of Gen Z shoppers, and not much more. But in the years since its emergence, and as technology and consumer demands evolve, visual search is no longer a “nice-to-have.” It’s quickly become a crucial part of the customer experience for all shoppers, not just digital natives. Among their top demands, today’s consumers desire ease-of-use, especially when it comes to locating the products they’re already motivated to buy. To fulfill your shoppers’ expectations and shorten the path to purchase, on-site search needs to be instant, intuitive, and accurate. Advanced visual search tools enable you to achieve all of that so you can provide the kind of experience your shoppers want — and more. How it Started And How It’s Going Nascent visual search offered basic image search capabilities. For example, a search engine’s visual search tool could tell you which famous artist created the painting in the image you uploaded, or what breed of dog is pictured in a photo. On eCommerce sites, uploading an image of a dress would yield you categorically similar items within an online store’s inventory, but precision was lacking. The accuracy of visual search tools back when the technology was brand new was good enough, but not perfect. It served as a “fun thing to try” for shoppers who were interested in a more innovative shopping experience. Today, visual search plays a much different and more important role. Here are four main ways visual search capabilities have evolved. 1. Increased Accuracy of Search Results Today, best-in-class visual search solutions can produce almost perfectly accurate results. For example, at Syte, we’ve been able to continuously train our algorithm and improve our visual search capabilities to reach 95% accuracy. Beyond simply identifying and interpreting the products in an image, advanced visual search tools can automatically recognize product categories and types, the age and gender of models, and even more granular data, such as the physical attributes of items (material, texture, shape, style, occasion, etc.). This helps brands and retailers provide highly relevant search results that match exactly what a shopper is looking for, down to the touch and feel of an item’s fabric. Today’s visual search tools can also identify multiple objects within a single image, giving shoppers more avenues and inspiration for discovering new products. Other features, such as smart object cropping, helps shoppers focus on the products within an image that they are interested in. 2. Additional Tools and Capabilities Visual search is no longer just a stand-alone feature — the brands and retailers that implement it aren’t simply adding an alternative way to search for products. Rather, the visual AI technology that powers visual search enables several other key functions that enhance product discovery and streamline core backend processes, such as merchandising, tagging, and inventory management. For example, the same image recognition technology that enables visual search can also be used to assign tags to each minute visual attribute on items within a given image. Automating this process enriches product metadata, creating a more robust infrastructure for both search and merchandising. Combined with other technologies like natural language processing (NLP), visual AI can even improve the accuracy of text-based search querying, leading to more relevant results (again aided by the visual-AI-enhanced tags) And finally, the granularity of insight into aesthetic taste and styles that visual AI data uniquely provides creates a foundation for personalization that is so detailed and attuned to individual tastes, it makes product recommendations feel human. If standard personalization might pick up on your penchant for midi dresses, visual AI enables recommendation engines to understand that your true affinity lies with sweetheart necklines, delicate floral prints, and spaghetti straps. If visual search was once a point solution, today, it is the backbone of the entire product discovery experience — that is, for the brands intent on delivering unique and delightful customer experiences. 3. Fulfills Rising Demand Among Consumers As the state of the world changes, technology develops, new brands and retailers emerge, and business models evolve, consumer behavior has also undergone profound shifts. With more shoppers than ever shopping online (projected 2.14 billion online shoppers worldwide in 2021), using social media, and engaging with other online content, their expectations for the customer experience are continuously rising. Today’s customer wants an online shopping experience that is as simple, instant, and intuitive as scrolling through their social media feed. As soon as they see an image with a product they love — be it a skirt, pair of sunglasses, sofa, rug, or earrings — they want a route to find it in their own price range, and buy it. It’s up to brands and retailers to make this journey as seamless as possible. And, when it comes to deciding how to do that, the answer is loud and clear. More than three-quarters of shoppers (78%) say product search is one of the most important factors for online shopping, while 62% want access to visual search capabilities more than any other technology. The easiest route to delighting your customers is to give them the tools they are asking for. 4. Creates a Significant Business Impact With the current level of sophistication, advanced visual search can have a profound uplifting effect on core business metrics, such as conversion rate, average order value, average revenue per user, and shopper engagement. Working with some of the world’s biggest brands and retailers, we’ve seen these game-changing results first-hand. For example: Fashion brand PrettyLittleThing achieved a 269% ROI in direct revenue generated after adopting visual search, as well as a 130% boost in CVR, and 2.3% uplift in revenue per session. Home decor marketplace Yestersen realized a 186% CVR uplift after implementing visual search and other visual discovery solutions Italian fashion retailer Rinascimento saw a 168% uplift in CVR, increased AOV by 17%, and achieved an outstanding 415% uplift in ARPU with the solutions in place Better business performance is the natural outcome of adopting visual search. With a more direct pathway to the items shoppers love, and by seizing their motivation to buy, brands and retailers that offer visual search are poised to improve a wide range of performance metrics. No Longer Just a “Nice-to-Have” As consumers’ standards for customer experience continue to rise, keeping pace and meeting their demands will be crucial for maintaining brand relevance, providing a differentiated experience, and competing in a saturated market. Visual search is no longer a shiny new toy. It’s core machinery in modern eCommerce infrastructure, enabling a better CX, boosting business performance, and enabling significantly better back-end efficiency. The longer laggards wait to implement it, the farther behind they will fall.