Google Search Console Now Reports Web Multimodal Search Performance: What Publishers Need to Know
Google has switched on a new performance report that shows exactly how your content is found through Lens, Circle to Search, image uploads, and Chrome's "Search this image" — and it changes how you should think about visual SEO.
Quick Answer
On September 24, 2026, Google announced new multimodal search reporting inside Search Console, giving site owners visibility into traffic from image-based searches — including Google Lens, Circle to Search on Android, image uploads to Google Search, and Chrome's right-click "Search this image" feature. The data appears in both the standard Performance on Search results report and the Generative AI features report, filterable via a new "multimodal" search type and exportable for deeper analysis. The rollout is global and automatic — no setup is required, and metrics will appear once your site starts receiving qualifying multimodal traffic.
What Is Multimodal Search, and Why Is Google Reporting on It Now?
"Multimodal search" describes any query where a user searches using more than text alone — most commonly, a photo, a screenshot, or a live camera view combined with a typed or spoken question. Instead of typing "red midcentury armchair with wooden legs," a shopper can simply point their phone camera at a chair they like and ask Google to find similar options.
This isn't a niche behavior anymore. Visual search has moved from an experimental feature to a default entry point for shopping, identification, and research queries — particularly on mobile. Google's own product leadership frames this shift plainly in the announcement: as Search evolves to include more visual and multimodal experiences, publishers need matching visibility into how that traffic behaves.
Until now, that visibility didn't exist. Search Console could tell you a query drove a click — but it couldn't tell you the click came from someone circling an object on their phone screen rather than typing a search term. That blind spot is what this update closes.
The core problem this solves
Without this data, a site could be receiving meaningful traffic from visual search and have no way to distinguish it from ordinary organic traffic, no way to see which pages or images are winning that traffic, and no way to optimize for it deliberately. Multimodal reporting turns an invisible traffic source into a measurable, exportable one.
Which Search Experiences Does This Data Cover?
The new "multimodal" search type filter in Search Console's Performance report consolidates four distinct ways users search visually:
| Search Method | What It Is | Typical Device |
|---|---|---|
| Google Lens | Camera-based search — point at an object, product, plant, landmark, or text and get results directly. | Smartphone (Android & iOS) |
| Circle to Search | Android gesture that lets users circle, tap, or scribble on anything on their screen — in any app — to search it instantly. | Android |
| Image upload to Google Search | Uploading an existing photo directly into the Search bar to find matches, sources, or related content. | Desktop & mobile |
| Chrome "Search this image" | Right-click context menu option in Chrome that searches an image found while browsing. | Desktop |
Because this spans both a dedicated smartphone-camera feature (Lens/Circle to Search) and desktop-browser behavior (Chrome right-click, uploads), the data reflects visual search intent across the full spectrum of devices — not just mobile.
How to Access Multimodal Performance Data in Search Console
No opt-in or code change is required. The rollout is automatic and global, and the report populates as soon as your site earns qualifying multimodal impressions or clicks.
- Open the Performance report. In Search Console, go to Performance > Search results (or the Generative AI features report for AI-surfaced visibility).
- Apply the new search type filter. Use the search type filter control and select "Multimodal" alongside the existing Web, Image, Video, and News options.
- Review clicks, impressions, CTR, and position exactly as you would for any other search type — now segmented to isolate visual-search performance specifically.
- Cross-reference by page and query to identify which URLs and images are actually being surfaced through Lens, Circle to Search, uploads, and Chrome image search.
- Export the data. Click "Export" to pull the dataset into Sheets, Excel, BigQuery, or your analytics stack for trend analysis, cohort comparison, and reporting.
Where else this shows up
The same multimodal signal also feeds Search Console's Generative AI features report, meaning you can now see whether your content is being pulled into AI-generated, visually-triggered results — not just traditional blue-link results.
Deeper Insights: What This Data Actually Tells You
Once the numbers start populating, the real value isn't the raw traffic count — it's what the pattern reveals about how your content is being consumed. A few things worth watching:
1. Which pages "win" visual search — and why
Pages that rank for multimodal queries tend to share traits: a clear, well-lit hero image; a single dominant subject (rather than a cluttered composite); and surrounding text that unambiguously names the object, product, or entity in the photo. Compare your top multimodal pages against your low performers to reverse-engineer what Google's image understanding models are rewarding on your site specifically.
2. The gap between impressions and clicks
Visual search often has a different CTR profile than text search, because the user has already seen a visual match before clicking — they're often confirming identity or seeking a purchase path rather than exploring. A high-impression, low-click multimodal page may indicate your image matches the search but your page (price, title, availability) doesn't convert the confirmation into a visit.
3. Query-less demand
Because Lens and Circle to Search often involve no typed query at all, this report surfaces demand that would never appear in your traditional keyword data. That's genuinely new market intelligence — it shows you what people are pointing their cameras at, not just what they're typing.
4. Product and identification-heavy content over-indexes
Early patterns across multimodal search — plants, landmarks, fashion, home decor, packaged products, textbooks — consistently over-index for visual queries. If your site touches any identification-style use case (species, models, parts, ingredients), expect this segment to matter disproportionately.
Optimizing for the New Reality: SEO, AEO, and GEO for Visual Search
Multimodal reporting isn't just a measurement tool — it's a signal about where to invest. Visual discoverability now sits at the intersection of three overlapping optimization disciplines. Here's how to approach each one.
Traditional Image & Technical SEO
- Use descriptive, keyword-relevant file names (
navy-suede-loafers.jpg, notIMG_4021.jpg). - Write specific, human-readable alt text that names the object, not just the category.
- Implement
Product,ImageObject, andArticlestructured data so Google can confidently bind an image to an entity. - Submit an image sitemap and keep image URLs stable — don't rotate CDNs or paths unnecessarily.
- Compress without degrading clarity — Lens and Circle to Search rely on crisp detail recognition.
Answer Engine Optimization
- Pair every important image with a concise, factual caption that could stand alone as an "answer" (material, origin, use, price range).
- Use clear heading structure so extracted answers map cleanly to a source section, not a whole page.
- Add FAQ blocks near visual content — visual queries frequently resolve into a follow-up question ("what is this," "how much does this cost").
- Keep one dominant subject per image; ambiguous or multi-subject photos are harder for answer systems to attribute confidently.
Generative Engine Optimization
- Establish strong entity clarity across your site (consistent naming, sameAs links, organization/product schema) so generative systems can verify what an image depicts.
- Build topical depth around visually-searched subjects — a single strong page beats five thin ones for AI synthesis.
- Monitor the Generative AI features report alongside multimodal data to see which visual entities are being cited in AI Overviews and AI Mode responses.
- Keep source content freshly maintained; generative systems favor pages that show recency and accuracy signals for visually-identified products or topics.
Action Checklist: First 30 Days
- Apply the new "Multimodal" filter in the Performance report and note your baseline clicks/impressions.
- Identify your top 10 URLs by multimodal impressions and audit their imagery and alt text.
- Export the dataset and segment by device (mobile vs. desktop) to separate Lens/Circle to Search behavior from Chrome/upload behavior.
- Cross-check top multimodal pages against your Generative AI features report for overlap.
- Fix the lowest-CTR, highest-impression multimodal pages first — that's the fastest win available.
- Add or upgrade
ImageObject/Productschema on pages with strong visual-search potential.
Frequently Asked Questions
Do I need to do anything to activate multimodal reporting in Search Console?
No. The rollout is automatic and global. Once your site receives qualifying traffic from Lens, Circle to Search, image uploads, or Chrome's "Search this image," the multimodal filter will populate with data — no verification, tagging, or setup is needed.
Where exactly do I find the multimodal filter?
In Search Console, go to Performance > Search results (or the Generative AI features report), then open the search type filter and select "Multimodal" alongside Web, Image, Video, and News.
Does this replace the existing Image search filter?
No. It's a distinct, additional segment. Image search reflects Google Images results; multimodal reflects camera- and photo-based query methods like Lens, Circle to Search, uploads, and Chrome's image search — which can drive traffic that never shows up under a traditional query at all.
Why might my multimodal numbers show zero at launch?
The report only populates once your site has measurable multimodal traffic. Sites with limited visual content, weak image SEO, or low visual-search demand for their niche may see minimal or no data initially — which is itself a useful diagnostic signal.
Can I export multimodal data for reporting or BI tools?
Yes. Use the "Export" option in the Performance report to download the filtered dataset for use in spreadsheets, BigQuery, or your existing analytics and client-reporting workflows.
Key Takeaways
- Google now reports on visual/camera-based search performance directly inside Search Console — no setup required.
- The data covers Lens, Circle to Search, image uploads, and Chrome's "Search this image," across both mobile and desktop.
- It appears in both the standard Performance report and the Generative AI features report, giving visibility into AI-surfaced visual results too.
- Winning this channel requires treating images as first-class SEO assets — clear subjects, descriptive alt text, structured data, and strong supporting copy.
- This is a genuine new demand signal: much of this traffic has no typed query behind it at all.
Want Your Content Ready for Visual, AI, and Traditional Search?
RankSenseAI helps SaaS and B2B brands optimize for SEO, AEO, and GEO together — so you're discoverable everywhere search is heading, not just where it's been.
Talk to RankSenseAISource: Google Search Central Blog, "Announcing web multimodal Search performance reporting in Search Console," posted by Harsh Kharbanda (Product Manager Lead, Google Lens) and Moshe Samet (Product Manager Lead, Search Console), September 24, 2026.
Author: Irfan Dar
Irfan Dar is an SEO professional with 4+ years of experience in SEO, performance marketing, and digital analytics. He specializes in technical SEO, content strategy, on-page optimization, keyword research, AEO (Answer Engine Optimization), and GEO (Generative Engine Optimization). At RankSenseAI, Irfan focuses on helping businesses improve their visibility across traditional search engines and emerging AI search platforms. His work covers technical SEO, content optimization, AI search visibility, structured data, entity optimization, and strategies designed to help brands get discovered across search experiences such as Google AI Overviews, ChatGPT, and other AI-powered platforms. He also works with tools and platforms including Google Search Console, GA4, Google Tag Manager, SEMrush, Screaming Frog, Google Ads, Meta Ads, and Looker Studio. Irfan believes effective SEO is not just about rankings. It is about creating useful, technically sound content and building the signals that help search engines and AI systems understand, trust, and surface a brand.