Google Search Console’s New Multimodal Search Data: What It Means for SEO and AI Search

Search has spent years being treated as a text-first activity. A person has a question, they type a few words into Google, results appear, and a website earns an impression or a click. That model is still important. But it no longer describes every way people search.

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A user can now point a phone camera at something, use Google Lens, circle something on their screen, upload an image, or right-click an image and search from it. Google has now started exposing part of that behavior inside Search Console through a new Web → Multimodal search type.

The change is easy to misunderstand.

And that distinction matters.

Because for SEO teams, the interesting question is no longer only “Which keywords brought people to our website?”

It is increasingly:

What Did Google Actually Add to Search Console?

On September 24, 2026, Google introduced web multimodal search reporting in Search Console. The reporting is available in the Performance report for Search results and is also incorporated into the report for Generative AI features.

The new reporting is designed to show how your content performs when users search using images.

The New Web → Multimodal Filter

If you open the Search Console Performance report and select Search type, Web now has two categories:

Google specifically includes visual search experiences such as:

This is important because these interactions are not necessarily happening inside Google’s traditional Image Search.

A user can start with an image and still end up discovering a web page.

Multimodal Data in the Generative AI Report

There is another important detail.

Google has also added multimodal reporting to its Generative AI performance report.

That creates a connection between visual search and Google’s generative search experiences but it still does not mean that every multimodal search is an AI search.

What Is Multimodal Search and How Is It Different From Image and AI Search?

The easiest way to understand the change is to separate how the user searches from where Google presents the result.

The distinction can be reduced to one sentence:

That’s why Web → Multimodal should not be interpreted as “AI Search traffic.”

A person can use an image to search and receive traditional web results.

Likewise, a person can perform a text-based search and encounter a generative AI experience.

These are different dimensions of the search journey.

How Does a Multimodal Search Journey Work?

The most useful way to understand multimodal search isn’t as another Google feature.

It’s a change in the starting point of the search journey.

The user can use an experience such as Google Lens, Circle to Search, an image upload, or Chrome’s “Search this image” functionality.

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Google then uses the visual input as part of understanding what the user is looking for.

The exact underlying systems are not something Search Console exposes to website owners, so SEOs should avoid turning this into a list of supposed “multimodal ranking factors.” What we can observe is the resulting search behavior.

The search does not necessarily stop at an image. The user can be shown web results, and that is where a website can receive visibility through Web → Multimodal reporting.

This is the important distinction from simply appearing in Google Images.

What Can SEO Teams Actually Learn From Multimodal Data?

The new report doesn’t magically reveal everything about visual search.

But it gives SEO teams something they previously couldn’t isolate in Search Console: visibility associated with web searches where an image was part of the search.

What You Can Measure

It can also be analyzed through dimensions such as pages, countries and devices, depending on the report and available data.

Google explains that query data isn’t available for multimodal searches because these searches primarily use images rather than text.

This makes the Pages dimension particularly interesting.

Suppose a SaaS website sees multimodal impressions concentrated around:

That doesn’t prove exactly why those pages appeared.

But it gives you a useful signal that visual-led discovery is reaching those parts of the website.

That’s where analysis becomes more valuable than simply watching the total number of impressions.

What Does Multimodal Search Change About SEO?

The biggest mistake would be to treat this as a new checklist of image optimization tricks.

The more meaningful change is conceptual.

Visual Assets Become Discovery Inputs

Images have traditionally been treated as supporting elements. They make a page attractive, explain a product, show a location, demonstrate a process, or break up long blocks of text.

Multimodal search adds another possibility:

That doesn’t mean every image needs to be created for search. It means important visual assets deserve to be treated as part of the information architecture of a page.

Context Around the Image Matters

An image rarely exists in isolation.

Consider a product screenshot.

The image may show what the product looks like, but the surrounding page can explain:

The visual provides context. The page provides depth. For SEO, those two things should support each other.

Entity Understanding Becomes More Important

Visual search can start with something tangible: a product, a brand, a location, a business, a piece of equipment, a logo, or a physical environment.

That makes clear entity information increasingly valuable.

Your website should make it easy for search systems to understand what the thing is, who it belongs to, what it does, and where it fits.

This is not a new replacement for SEO. It is an extension of something SEO has always needed: clear, consistent information.

Search Intent Can Begin Before a Keyword Exists

This may be the most interesting shift.

With traditional search, marketers often start with the query:

With multimodal search, the user may begin with:

Or simply:

The search system has to connect the visual input with possible information needs.

That means the search journey can begin before a conventional keyword is formulated.

How Should Businesses Prepare for Multimodal Search?

There is no need to create a completely separate “multimodal SEO strategy.”

Google’s announcement is about reporting and visibility; it does not publish a special set of multimodal ranking factors.

A better approach is to make your existing content clearer, more connected and more useful.

Make Visual Content Understandable

Use meaningful images where they genuinely help explain the subject.

The goal isn’t to produce more images. It’s to make important information available visually as well as textually.

Connect Visuals With Relevant Page Content

A screenshot of a feature is more useful when the page clearly explains that feature.

A photograph of a business is more useful when the page clearly identifies the business, service and location.

A product image is more useful when the page provides accurate product information.

rather than

Strengthen Entity and Business Information

Make your important information consistent across the site.

Keep Structured Data and On-Page Information Consistent

Structured data should support what the page actually says.

It shouldn’t be treated as a way to tell Google something that users cannot find on the page.

Measure Instead of Guessing

This is perhaps the most important part.

Don’t assume that a particular image strategy is working because it sounds good.

Use the new Search Console data to find out whether your website is actually receiving multimodal visibility.

How to Analyze Multimodal Search in Google Search Console

The new report becomes much more useful when you compare it with your existing search data rather than looking at it in isolation.

Frequently Asked Questions About Multimodal Search