Google Search Console is rolling out a Multimodal option inside the Web search type of the Performance report. It separates web results reached through a search involving an image—such as Google Lens, Circle to Search on Android, an image upload, or Chrome’s “Search this image” feature—from text-based Web search. For GEO work, that is a meaningful new reporting segment: it shows which landing pages are being surfaced when visual input is part of discovery.
The immediate analytical consequence is more important than the interface change itself. Google’s reported position, relayed by seroundtable.com, is that this data was not previously included in Search Console’s counts and that the report contains new data. Teams should therefore annotate the appearance of the filter and build a new baseline. Do not casually interpret the beginning of a multimodal series as a change in page demand, image quality, or GEO visibility.
A new segment for image-led discovery
The new filter sits under Web, which Search Console now divides into text-based and multimodal results. Multimodal means web results in which an image was used as part of the search, according to searchenginejournal.com. It is not a generic Image Search report and it is not a report on every image associated with a site.
That distinction matters. A multimodal click tells you that a user reached a page from a web search where an image formed part of the search interaction. It does not establish which image the user supplied, what object or scene it depicted, or what text they may have added to the search. The reporting is about the landing page’s presence in that search path, not a forensic record of the user’s camera input.
For practitioners working on GEO, this is useful precisely because visual search and generative search are difficult to reduce to conventional keyword reporting. A page can be surfaced because a system can connect its visual material, product information, surrounding text, and page-level relevance to an image-led task. Search Console does not expose all of those signals. But it now exposes a measurable outcome: impressions and clicks for pages appearing in this particular kind of Web discovery.
The query blind spot changes the analysis
Multimodal reporting does not include the Queries dimension. Google’s explanation is direct: because multimodal searches mostly use images rather than text, specific text-query data is unavailable; the Queries dimension is consequently unavailable when that search type is selected, as reported by searchenginejournal.com.
This removes the default SEO workflow of identifying a growing query, inspecting the ranking page, and mapping demand to an optimization decision. It also limits the temptation to pretend that image-led discovery can be fully explained with a keyword list. The absence of query data is an information constraint, not evidence that text has no role in these searches.
The workable analysis shifts toward pages and context. Search Console reporting can still be compared by page, country, device, and time, according to searchenginejournal.com. That makes the following questions more useful than “which multimodal keywords are we winning?”
- Which pages receive multimodal impressions and clicks at all?
- Are the pages products, category pages, editorial guides, location pages, or something else?
- Does visibility vary by country or device?
- Do the pages that receive multimodal activity also perform differently in text-based Web reporting?
- After traffic reaches those pages, does the team’s own analytics show a materially different downstream outcome?
The last question is intentionally outside the Search Console announcement. The supplied reporting change establishes a new acquisition segment; it does not itself explain conversion quality, user intent, or revenue. Those are questions teams will need to evaluate in their own measurement environment.
Why the reporting break needs an annotation
The evidence on historical treatment deserves care. searchenginejournal.com noted that Google’s post did not specify whether the data includes history from before rollout or whether the new split affects existing Web totals. That is a real limitation in the public description.
But a stronger clarification subsequently reported by seroundtable.com says Google checked with its team and confirmed that the data “wasn’t previously in the counts” and that the report has new data. This is the practical basis for treating the segment as a new measurement series.
That does not mean every Web chart is necessarily broken in the same way. The supplied material does not settle every implementation detail, including whether all properties will receive historical multimodal values or precisely how legacy Web comparisons will display once the split is available. It also says rollout began globally on September 24, 2026, while some properties may not see the option immediately.
What it does mean is that teams should preserve reporting discipline. A dashboard annotation should record when the Multimodal filter first became available in the property and identify the first complete reporting period used as a benchmark. If a stakeholder sees new multimodal impressions or clicks, the correct initial interpretation is “newly reported measurement,” not “a newly created audience surge.”
Build a page-level baseline before making optimization claims
Once the filter appears, export the data. Google specifically directs users to the Export function to download it for analysis in other tools, according to seroundtable.com. The first export is not merely operational housekeeping; it is the baseline from which later change can be evaluated.
I would record a compact baseline with the reporting date range, clicks, impressions, the pages receiving activity, and country and device cuts where volume makes them interpretable. Then compare the same pages in text-based Web reporting. This does not prove causality, but it creates a durable record of which content has exposure across both text-led and image-led paths.
For pages that show meaningful multimodal activity, review the actual on-page experience rather than reacting with indiscriminate image edits. The third supplied source argues that original images, descriptive alt text, meaningful filenames, relevant surrounding content, responsive presentation, and useful product imagery can help make visual material and its landing page more understandable, while warning against keyword stuffing in alt text or filenames nrstechnologies.com. These are plausible audit dimensions, but the new Search Console report does not prove that changing any one of them will increase multimodal visibility.
That distinction is central to credible GEO work. Measurement has improved, but attribution remains narrow. The report can identify candidate pages for investigation; it cannot reveal the image input, the user’s full task, or the exact reason a page was selected.
Keep multimodal and generative reporting separate
Google is also rolling multimodal data into its generative AI performance report, but that report counts impressions rather than clicks, according to searchenginejournal.com. Do not merge those datasets into one undifferentiated “AI search” metric. They answer different questions.
Multimodal Web reporting can show page-level impressions and clicks from image-involved Web searches. Generative AI reporting, as described in the supplied coverage, is an impressions measure. A shared visual-search mechanism does not make the metrics interchangeable.
The real value of this release is not that it completes visual-search attribution. It does not. Its value is that it turns one previously opaque discovery path into a named Search Console segment. Establish the baseline, label the reporting change, analyze pages rather than imaginary query lists, and let subsequent periods—not launch-week enthusiasm—show whether there is a durable pattern worth acting on.