Visual Search (Google Lens)

Visual search lets people search using a picture: pointing a camera at a plant, circling a jacket in a video or uploading a screenshot. The system recognises what is in the image and returns matching or related results. Google Lens is the best-known example, alongside Circle to Search on Android and image input in AI Mode, Gemini and ChatGPT. It is part of the wider shift to Multimodal Search.

How it works

Modern image understanding relies on a few ideas that MLforSEO’s image SEO guide explains:

• Patches: Vision Transformers cut an image into small squares and treat them like words in a sentence.
• Contrastive learning: models such as CLIP train an image encoder and a text encoder together, so a photo and its description end up close in the same embedding space.
• Image embeddings: each image becomes a vector, so visually or semantically similar images can be found with Vector Search.

The same models recognise objects, read text inside images and describe scenes. Visual search then combines that understanding with the text signals around an image on the web: file name, alt text, captions, surrounding copy and structured data.

How it’s used in SEO and marketing

• Using original images. A stock photo on thousands of pages is, to a visual matcher, one image with many owners.
• Making images crawlable as <img> elements, with descriptive file names, alt text and captions consistent with what the image shows.
• Adding product structured data and Merchant Center feeds, since a large share of Lens searches are about shopping.
• Monitoring the “Multimodal” search type Google added to the Search Console Performance report in 2026, which covers Lens, Circle to Search and image uploads.
• Clustering and de-duplicating your own image library with embeddings.

Example

Someone photographs a friend’s armchair with Lens. Lens recognises the style, finds visually similar products and shows shopping results with prices. A retailer with an original, well-lit product photo, matching alt text and complete Product markup is far more likely to appear than one reusing the manufacturer’s image.

Limitations and things to watch

• Usage figures come from Google: nearly 20 billion visual searches a month in October 2024. Treat newer numbers as company-reported.
• Search Console’s Multimodal report does not show queries, only pages and clicks.
• Vision models misread images; never publish AI-drafted alt text without checking it.

Learn it on MLforSEO

• Image SEO in 2026: The Complete Guide to Image Optimisation, Advanced Tactics and Multimodal Search
• Image Clustering by Color with Three Machine Learning Approaches for Visual Content Organization
• Semantic ML-enabled Keyword Research