Google Search Console Multimodal Search Report: What It Tracks and How to Use It

Google Search Console now separates searches that start with an image from searches that start with typed text. The new multimodal search type filter shows how often your pages appear and get clicked when people search with Google Lens, Circle to Search, image uploads or Chrome’s “Search this image” option. It is available in the Performance reports for Search results and Generative AI features.

For sites with product photos, project galleries or any meaningful visual content, this is the first direct view of a search behaviour that was previously hard to measure. Below is what the report includes, what it leaves out, and how to turn the data into useful SEO work.

What Google Actually Announced

Google Search Central announced web multimodal search reporting as a global rollout. According to the announcement, the data covers four entry points:

• Google Lens
• Circle to Search on Android
• Image uploads to Google Search
• Chrome’s “Search this image” feature

Inside the Performance report, when you open the Search type filter, the “Web” option now splits into “Text-based” and “Multimodal.” Google’s own definition is simple: multimodal covers results triggered by a query that uses an image, photo or screenshot, while text-only queries fall under Web text-based. Search Engine RoundtableSearch Engine Roundtable

Google also said the filter works in the Generative AI features performance report, and that the same insights are available for platform properties such as YouTube, Instagram and TikTok accounts.

Because this is a gradual rollout, some properties may not show the filter yet. That is normal for new Search Console features and not a sign that something is wrong with your site.

Multimodal Is Not the Same as Google Images

This is the distinction most people will get wrong in the first few weeks.

The “Image” search type in Search Console reports performance inside Google Images, where someone typed a text query and browsed image results. Multimodal reporting sits under the Web search type. It measures web results shown after someone used an image as the query itself.

Two different behaviours:

So if you already monitor the Image report, you are not already covered. Multimodal traffic was previously mixed into your overall Web numbers with no way to isolate it.

How to Find the Multimodal Filter in Search Console

1. Open Search Console and choose your property.
2. Go to Performance, then Search results.
3. Click the Search type filter at the top of the report.
4. Under Web, select Multimodal.
5. Use the Compare option to view Multimodal against Text-based for the same date range.

Repeat the same steps in the Generative AI features report if your property has access to it.

The comparison view is where the report becomes useful. A raw multimodal number means little on its own. The share of a page’s visibility that comes from image-led searches tells you much more.

What the Report Shows, and What It Does Not

The biggest limitation is query data. Google’s help documentation explains that since these searches mostly use images rather than text, specific query data isn’t available, so the queries dimension disappears when this search type is selected. Search Engine Roundtable

That changes how you analyse the report. You cannot ask “which keywords triggered this?” Instead, you work backwards from pages.

Here is what that means in practice:

• Pages become the main dimension. The question shifts from “what did people search?” to “which pages earn visibility when someone searches with a photo?”
• The images on those pages are your best clue. If a pool repair page gets multimodal impressions, look at which images on that page could match what someone photographed.
• Country and device data still help. Image-led searches are heavily tied to smartphone cameras and Android devices, so the device split is worth checking. Treat this as an expectation to verify in your own data, not a rule.

A second limitation applies to the AI side. The Generative AI features reports show impressions from AI Overviews, AI Mode and generative AI features in Discover, but do not include click data. So when you apply the multimodal filter there, expect a visibility signal, not a traffic signal. Search Engine Journal

Why This Matters for SEO, Especially Local SEO

Image-led searches often carry a different intent from typed searches. People reach for the camera when they do not know the name of what they are looking at, or when describing it in words would be slow.

Consider a few realistic service business scenarios:

• A homeowner photographs a wasp nest under the roof edge and wants to know what it is and whether it is dangerous. A pest control company with a clear, well illustrated wasp nest identification page is a natural result.
• A pool owner photographs a cracked skimmer lid or an unfamiliar pump part. A pool service company with original photos of common repairs has a better chance of matching than one using stock images.
• Someone photographs a leaking valve under the sink and wants to know what part it is. A plumber’s guide to common valve problems could answer that search.

In each case, the searcher may not know the correct term to type. The image does the work that a keyword used to do.

This is also where original imagery starts to matter more. A stock photo appears on hundreds of sites, so it gives Google little reason to connect it to your business specifically. Real photos of your jobs, your products and your work carry a stronger link between the image and your page. That is my practitioner interpretation rather than a documented ranking factor, but it lines up with how visual matching works.

One boundary to keep in mind: Search Console reports on your website. It does not show how your Google Business Profile photos perform in image-led searches. For local businesses, GBP and website visibility still need to be read together, using the right tool for each.

How to Use the Data: A Practical Workflow

1. Record a Baseline Now

Take a snapshot of multimodal clicks and impressions for your top pages, and note the date the filter became visible for your property. New reports often look thin at first, and a baseline lets you judge changes fairly later.

2. Find Pages Where Multimodal Share Is High

Compare Multimodal with Text-based at page level. Look for pages where image-led searches make up an unusually large portion of visibility. These pages are telling you that their images are doing real discovery work.

Then ask a diagnostic question: what on this page could someone have photographed?

3. Find Pages That Should Appear but Do Not

Some pages naturally invite photo searches. Product pages, parts guides, identification guides, before and after project galleries, menus and equipment pages all fit this pattern.

If a page like this shows no multimodal visibility, check whether its images are accessible and understandable to Google at all.

4. Fix Image Basics Before Anything Clever

Google’s image SEO documentation has recommended the same foundations for years, and they matter here:

• Use standard HTML image elements so Google can find the images.
• Do not block image files or image folders in robots.txt or through CDN settings.
• Write descriptive alt text that explains what the image shows, not a list of keywords.
• Use meaningful file names instead of camera defaults such as IMG_4821.jpg.
• Place images near relevant text, captions or headings so the page explains the image.
• Include important images in your sitemap or an image sitemap.
• Keep images compressed and pages fast, especially on mobile.

The surrounding content matters as much as the image file. Google needs the page to confirm what the image represents and why the page is a useful answer.

5. Use the Data to Win Internal Arguments

Google’s announcement made a fair point here. Many teams treat image optimisation as a low priority task that keeps getting pushed back. Multimodal data gives you evidence tied to real pages. If a product category earns meaningful image-led visibility, that is a business case for better photography, cleaner markup and faster image delivery.

Common Mistakes to Avoid

Confusing multimodal with Google Images. They measure different behaviours. Reporting them as one number will mislead clients and stakeholders.

Waiting for query data. It is not available for this search type. Build your analysis around pages, devices and countries instead.

Judging the numbers too early. A small multimodal share in week one tells you very little. Give it a few months before drawing conclusions.

Treating low volume as irrelevant. Image-led searches can be small in number but high in intent, particularly when someone photographs a problem they need solved.

Expecting Google Analytics to separate this traffic. Do not assume your analytics platform will label these visits differently from other organic Google traffic. Search Console is the place to segment it.

Replacing real images with more stock images. If visual search rewards anything, it is images that are clearly connected to your business and content.

How to Measure Progress

Keep measurement simple and tied to outcomes:

• Track monthly multimodal clicks and impressions for your priority pages.
• Watch the ratio between Multimodal and Text-based for those pages over time.
• Annotate the dates of image improvements, such as new photography, alt text updates or sitemap changes.
• Connect landing page performance to calls, enquiries, bookings or sales wherever tracking allows.

The last point is the one that matters most. Higher multimodal impressions are only useful if the pages behind them lead to qualified visits and real enquiries.

The Practical Takeaway

Multimodal reporting does not change what good image SEO looks like. It changes how well you can see the results of it.

Start by recording your baseline, find the pages already earning image-led visibility, and fix the basics on pages that should be appearing but are not. For local service businesses, original photos of real work are likely to be the strongest place to start, because they give Google something specific to match and give searchers a reason to trust the result.