Google Search Console Now Reports Web Multimodal Search Performance
Google has officially launched multimodal search performance reporting in Search Console, giving site owners visibility into how their content surfaces when users search using images, camera input, and visual tools. This new search type filter covers traffic from Google Lens, Circle to Search, image uploads, and the Chrome right-click image search feature. For marketers and SEO professionals, this represents a significant step toward understanding a growing and previously unmeasured traffic source.
Key points
- Google has introduced a dedicated multimodal search type filter in the Search Console Performance report, available globally starting September 24, 2026.
- The data covers four distinct visual entry points: Google Lens, Circle to Search on Android devices, direct image uploads to Google Search, and the Chrome browser right-click 'Search this image' feature.
- Multimodal search performance data is also integrated into the Generative AI features report within Search Console, reflecting the growing overlap between visual search and AI-driven search experiences.
- Sites that are receiving traffic from multimodal queries will automatically begin seeing the relevant metrics appear in their Performance report without any additional configuration required.
- The data can be exported directly from Search Console, allowing teams to pull multimodal performance metrics into their own reporting tools and dashboards for deeper analysis.
- The announcement was made by Harsh Kharbanda, Product Manager Lead for Google Lens, and Moshe Samet, Product Manager Lead for Search Console, signaling close collaboration between the Lens and Search infrastructure teams.
Analysis
Until now, traffic originating from visual and camera-based searches was essentially invisible to site owners working within Search Console. Users searching with Google Lens, uploading images to find similar content, or using Circle to Search on Android could land on a website without that visit being attributable to a specific search type in any standard report. This update closes a significant measurement gap that has existed as visual search usage has grown substantially over recent years.
The inclusion of multimodal data within both the standard Performance report and the Generative AI features report is strategically meaningful. It signals that Google views visual search not as a peripheral feature but as a core part of the modern search ecosystem, one that intersects directly with AI-powered experiences. For SEO professionals, this means that multimodal visibility is now a legitimate and measurable performance dimension alongside traditional text-based search.
The scope of what is counted under multimodal search is broader than many practitioners may have assumed. It encompasses not just Lens queries initiated from a smartphone camera, but also Circle to Search interactions on Android, image file uploads directly into the Google Search interface, and the Chrome right-click search functionality. This breadth suggests that a meaningful portion of users across multiple platforms and devices are already engaging with search in non-text ways, and that this behavior is widespread enough to warrant dedicated reporting infrastructure.
From a competitive intelligence perspective, the ability to export this data is particularly valuable. Teams can now isolate multimodal query performance, compare it against text-based query performance, and identify which pages or content types are most frequently surfaced in visual search contexts. This creates an opportunity to understand which images, product photos, infographics, or visual assets are driving discoverability in ways that were previously untrackable.
The rollout also carries implications for how content teams think about image optimization. Historically, image SEO has been treated as a secondary concern, focused mainly on alt text and file naming. Now that performance data exists for visual search specifically, there is a concrete business case for investing in higher-quality imagery, structured image metadata, and content formats that lend themselves to visual discovery. Brands in verticals such as e-commerce, travel, food, fashion, and home decor stand to benefit most directly from this shift.
What to do
- Log into Search Console immediately and apply the new multimodal search type filter in your Performance report to establish a baseline of current visual search traffic for your site, even if volumes appear low at first.
- Export your multimodal performance data regularly and track it over time in a dedicated reporting view, so you can identify trends, growth patterns, and which specific pages or content types gain the most traction through visual queries.
- Audit your existing image assets across high-traffic pages and ensure they are technically optimized for visual search, including proper use of structured data for images, descriptive file names, and comprehensive alt text that reflects what is visually depicted.
- Cross-reference your multimodal search performance with your Generative AI features report to understand how your visual content is appearing within AI-driven search experiences, and identify any content gaps or opportunities in that emerging format.
- Prioritize investment in original, high-quality visual content on pages where you want to build multimodal search presence, particularly in product categories or editorial topics where image-based discovery is a natural user behavior.
- Share the multimodal search type filter and its data with your broader marketing and content teams to build awareness that search performance now extends beyond text, and that visual asset strategy directly influences measurable organic traffic outcomes.
Site owners can now quantify and track traffic driven by visual and multimodal queries, enabling data-driven optimization of image content and visual assets for a channel that was previously invisible in standard analytics. This update opens a new dimension of SEO strategy centered on image relevance, visual discoverability, and multimodal search presence.