Google Lens: What Is It and How Does It Work in Visual Search?

Type less and show more: that’s the logic behind visual search, the search format that no longer relies solely on words to find information.

When someone takes a photo of a plant, a shoe, or a sign in another language and gets an instant answer, visual search is at work behind the scenes.

Tools like Google Lens have made this type of search commonplace, and so-called multimodal search—which combines images and text in the same query—has further expanded this way of searching.

For content publishers, this changes the game, as images are no longer just illustrations but have become a gateway for traffic—provided they are properly optimized with alt text, file names, and correct structured data.

This article covers everything you need to know to optimize your images in this context.

What is visual search, and how does it work?

Visual search is a way to search that uses an image, a photo, or a screenshot as a starting point, rather than a typed phrase.

The search engine analyzes the visual content, recognizes objects, text, places, or patterns, and returns related results—whether they’re similar products, information about a landmark, or the translation of a photographed text.

This technology relies on computer vision and image recognition models trained to identify visual patterns and associate them with information already indexed on the web.

In practice, visual search solves a long-standing problem. We don’t always have the right vocabulary to describe what we’re looking for. No one knows the scientific name of that plant, the exact model of those sneakers, or the species of that insect in the garden.

With an image, that barrier disappears. That’s why Google has invested so heavily in this area, and the results are evident in the numbers: Google itself states that Lens is used more than 10 billion times a month for camera- or image-based searches.

This connects visual search to a broader trend—the same one that brought about Google AI Mode and AI-generated overviews to the center of the search experience.

Caption: Google Lens identifies objects in real time and displays results and related products in visual search.

How does Google Lens work in practice?

Google Lens works by scanning an image captured by the camera, uploaded from the gallery, or selected directly from the results page.

It identifies objects, text, and scenes through visual recognition and cross-references this information with Google’s search index to deliver relevant results.

The tool was originally designed for simple tasks, such as scanning a business card or translating a sign. Today, it does much more than that.

With the feature called “multisearch,” you can combine an image with a text prompt in the same search, such as taking a photo of a dress and asking to find it in a different color, or taking a photo of a dish and asking for the recipe.

Lens now also works within other apps, allowing you to search for any image or video that appears on your phone’s screen without having to leave the app you’re currently using.

For website owners, this behavior matters because Lens uses the same pages indexed by traditional search as a source for its results, and a well-optimized image has a real chance of appearing in those results.

What is multimodal search?

Multimodal search is a type of search that combines more than one type of input—such as images, text, and, in some cases, voice—in a single query.

Instead of choosing between taking a photo or typing, the user does both at the same time to get a more accurate answer.

This behavior is a natural extension of visual search. A photo alone identifies the object; the added text refines the intent, whether it’s a filter for color, size, brand, or use.

Multimodal search also appears in generative AI tools, which can already accept images, text, and even documents in a single query and process everything together before responding.

This is the same principle behind the query fan-out: the original query—whether visual, textual, or mixed—is broken down into subqueries so that the system can search for and combine answers from different sources.

For content creators, the lesson is the same as always. Clear textual context surrounding each image helps both traditional and multimodal search understand what is being shown.

What image best practices help visual search?

Best practices for images in visual search include using lightweight files in modern formats, descriptive filenames, and high-quality images placed near relevant text, as well as ensuring they are loaded with the HTML tag `<img>` so that Google can crawl them.

The Google Search Central details these practices in its official image SEO guide, emphasizing points that are often overlooked:

• Use standard HTML image elements; images loaded solely via CSS are not indexed.
• Opt for short, descriptive filenames, such as blue-running-shoes.jpg instead of IMG00023.jpg.
• Use supported formats, such as WebP, AVIF, PNG, JPEG, or SVG, prioritizing a balance between quality and file size.
• Use the same URL for an image across multiple pages, which facilitates caching and prevents repeated crawling.

Here’s how these factors work together in practice:

Table: Technical factors that influence image indexing.

Clear images also influence the decision to click. Blurry thumbnails in search results tend to be ignored, even when the content behind them is good.

How do you write alt text for image SEO?

Good alt text describes the image’s content objectively, in a few words, without artificially repeating terms and without starting with phrases like “image of” or “photo of.”

It needs to work for both screen readers and the algorithms that try to understand what the image shows.

Google itself advises focusing on useful, information-rich content, while avoiding exaggeration. Alt text like “dog” provides little description; “a golden retriever puppy playing fetch with a ball” describes it well, without turning into a list of keywords.

SemRush takes the same approach in its guide on alt text, recommending concise descriptions—ideally under 125 characters—that benefit both accessibility and image SEO.

Check out the difference between missing, generic, and well-written alt text:

Table: Examples of alt text for the same image.

This attention to detail also applies outside the blog. Professional profiles that already use descriptive alt text in Instagram posts and Reels reap the same benefits, with a better chance of appearing in image searches, both on and off the platform.

What structured data optimizes images for image search?

Structured data helps Google understand which image is the main image on a page and display additional information about it, such as licensing and authorship, but it does not replace alt text, file names, or contextual text; rather, it complements these signals.

A practical example is the ` primaryImageOfPage` property from Schema.org, which indicates which image should represent the page in search results. The same effect can be achieved with the `og:image` tag .

Another resource is the image license metadata, which informs Google how an image may be used and enables the “licensable” badge in image search—a key differentiator for stock photo sites, photographers, and publishers.

For an institutional blog, the essentials remain simple: a relevant, high-resolution image—without extreme aspect ratios or embedded text—linked to the correct page. Tagging without this basic care accomplishes nothing.

How do you develop an image SEO strategy?

A image SEO strategy organizes your efforts across four areas: technical file preparation, alt text and descriptive filenames, on-page textual context, and structured data with an image sitemap—all while continuously monitoring performance in Google Search Console.

The Search Engine Land summarizes this approach as a combination of accessibility, performance, and thematic relevance—not just a list of tags to check off.

The step-by-step guide follows this order:

1. Compress and convert images to lightweight formats before uploading them to the site.
2. Write descriptive file names and alt text, without stuffing them with keywords.
3. Place each image near the text that explains what it shows.
4. Add an image sitemap for pages with a lot of visual content.
5. Track clicks and impressions from the Images tab in Search Console.

A SemRush recommends reviewing this checklist periodically, since the volume of images on a website grows quickly and small details—such as a forgotten alt text—can pile up.

Blogs and social media also work together on this front. Anyone who already manages SEO for social media knows that captions, on-screen text, and well-described images on both platforms reinforce the same digital entity for search engines.

Anyone who wants to take this work further with a comprehensive view of technical, content, and image SEO can count on the mkt4edu’s SEO team to build this plan from the ground up.

Frequently Asked Questions About Visual Search/Google Lens

Is it worth investing in visual search right now?

Yes, it is—especially because optimizing images isn’t a standalone project; it’s the natural extension of well-executed SEO, which should already be in place on your website. The difference is that now these images are also competing for space in visual and multimodal search, with real traffic potential.

Anyone who already follows best practices for content, structure, and alt text is just a few tweaks away from taking advantage of this channel.

But for those who still treat images as mere aesthetic details, the path forward is clear: file names, alt text, lightweight formats, textual context, and—when appropriate—structured data.

This attention to detail ties into a broader landscape—the same one that has changed the way Google delivers AI-generated overviews and has come to interpret images, text, and intent as part of the same search.

If your institution wants to turn every image on its website into a gateway for qualified traffic, talk to the mkt4edu team and find out how a comprehensive SEO strategy—including images—can boost your visibility in search results.