The way we search is going through an advanced era that is not only limited to typing keywords and text-based queries. Today, visual search is completely changing the search dynamics by offering a more personalized and easier way to conduct searches using images instead of keywords.
Let’s say you saw a pair of sneakers walking down the road. You don’t know the brand name or model, but you want those shoes. So instead of typing white sneakers with yellow strips, just snap the picture from your smartphone and get instant, fast, and relevant results.
According to a report, 22% of the people between the ages of 16 to 34 are most likely to purchase through visual search as compared to 17% of the people between the ages of 35 to 54.
Visual search is not just a trend; it’s the future of search, driven by Artificial Intelligence, that is reshaping how consumers discover information, products, and services online.
Visual search uses Artificial Intelligence and computer vision to enable users to search for products using images instead of text or typing keywords. It allows users to upload an image or take a real-time snapshot and upload it in the search query to learn more about what’s in the image or find a product included in the image.
Visual Search works when a search engine receives an image, recognizes it, and hunts down other images online that are either exactly or nearly similar. The results may carry images of the object itself or an object partly consisting of that object. If one searches for a product, information on product names, pricing, and product page links could also be made available.

Few engines can also use Artificial Intelligence to provide search based on image understanding and image comparison.
A visual search engine incorporates machine learning by learning the content of an image and then trying to find contextual examples; computer vision might be yet another approach to facilitating image visualization for such engines.
Image Capture or Upload:
Image Preprocessing:
Feature Extraction by CNNs:
Embedding and Vectorization:
Similarity Matching:
Rendering of Results:
Visual search tools can identify not only product types (categories) but also additional information, such as the physical properties (e.g., shape, texture, background, etc.) of the items to be searched for. This facilitates retailers to get search results much more closely aligned with what shoppers are looking for, even if fine detailed analysis is needed on the items.
Some of the main reasons why visual or image-based search is gaining importance include:
Today, people want instant results, especially Gen Z and millennials, who prefer visual over text content. According to a report, more than 50% of consumers find visual information more important than text while shopping online. Moreover, with most people shopping from their smartphones, visual searches have become an important element that influences consumer buying decisions.
Visual search lets customers search online hassle-free by granting an immediate image upload. Marketers should make efforts to link users directly with what they want, whether information, a product, or anything else.
Optimizing for various visual search tools could increase engagement and conversion in some ways. For example, downloading an application will enable you to get visibility to the concerned audience utilizing a search experience based on visual means, increasing engagement from such audiences.
Visual search caters to micro-moments—instances where users want immediate results. Mobile users, in particular, prefer the convenience of snapping a picture and getting results instantly, creating a smoother path to conversion.
Visual search is becoming a new SEO frontier, helping marketers and consumers connect more intuitively through images rather than text-based queries. Here are some of the tips to use visual search for better SEO:
Traditional SEO exclusively focused on alt text and file names, but visual search brings a new level of image optimization that offers a more personalized and to-the-point approach to search queries.
Behind all successful visual search results is a strong metadata set. Trend-worthy marketers are now ushering in:
Encourage UGC on social media to automate the generation of your content. A UGC example is running a contest wherein users are rewarded for submitting creative ideas on how to use products.
Use as many relevant tags as possible to link images with their respective product page. Shoppable images thus can go a step further and provide a more effortless ecommerce environment for the customers by allowing them to click on a photo to proceed directly to the checkout page.
Visual search tools require contextual relevance so that they can understand and render the images they index for visual search.
Alongside XML or HTML sitemaps, the creation of an image sitemap is one worth considering. This will foster the ability of visual search engines to find your images and index them, thereby broadening your chances of being searched for online.
With Visual Search on the rise, some of the key players have already established a strong position offering a combination of AI and complex algorithms to understand, recognize, and compare images when bringing back results to users.
No surprises, Google is leading the way in visual search discovery with Google Lens. It uses the advanced combination of Artificial Intelligence, Augmented Reality and Computer Vision to enables users to search directly for what they see. Users just need to upload the image, the Google AI will look for objects text, landmarks, products, and other items using any image.

StyleSnap is accessible through the Amazon app to help users find fashion products based on visual search.
For example, an image of a dress worn by somebody will cause StyleSnap to bring up recommendations for that precise dress or kinds of dresses with similar features.
Pinterest AI lens takes visual discovery to the next level by targeting consumers interested in lifestyle, home decor, and fashion, enabling them to upload images to get ideas or inspiration.

Bing Visual Search is more like a Google Lens powered by Bing. It has advanced image recognition capabilities that help your uploaded images match similar ones in Bing’s database.
The shift towards visual search brings a major transformation in how audiences discover and consume products. Therefore, it becomes very important for the brands to design their digital strategies to remain visible in a world where consumers increasingly prefer to search with their cameras rather than their keyboards. Visual search is the future of e-commerce, offering a more intuitive approach for brands ready to be discovered in this new visual-first ecosystem.
To rank better in Visual Search for utmost visibility, it’s always better to partner with an expert digital marketing agency like ResultFirst. With years of experience in providing advanced digital marketing and SEO services, we help your brand stay ahead by optimizing for visual discovery, driving more engagement, discoverability, and conversions.
Visual search uses Artificial Intelligence and computer vision to enable users to search for products using images instead of text or typing keywords. It allows users to upload an image or take a real-time snapshot and upload it in the search query to learn more about what’s in the image or find a product included in the image.
Visual search offers convenience, speed, and accuracy. It helps users find products easily, especially when they don’t know the name or details, by simply using a photo or screenshot.
Visual search is widely used in e-commerce, fashion, home décor, and travel apps. It helps users discover similar items, compare styles, or find the best deals using just images.
Most modern smartphones and devices with cameras support visual search, especially when using apps like Google Lens or shopping platforms that have integrated AI-based visual recognition tools.