Should Ecommerce Teams Invest in Visual Search? Start With Search Console's New Multimodal View

A new view, not a new sales number

On September 24, Google announced web multimodal Search performance reporting in Search Console. Its new multimodal search-type filter covers web searches that use an image, including Lens, Circle to Search on Android, image uploads to Google Search and Chrome’s right-click “Search this image” feature. Google says the data appears in the Performance report for Search results and in the report for Generative AI features, with a global rollout beginning that day. Sites receiving traffic from these queries will start seeing metrics.

For an ecommerce leader, the useful question is not “Are we winning visual search?” It is “Do we have enough evidence to spend time improving the product information shoppers encounter from image-assisted discovery?” That calls for a scoped review, not a commitment to rework every product image or page.

Set the boundary before asking for a budget

Start in the Search results Performance report and select the web multimodal search type. Record the date range, property, country and device for each view you share. Compare the pages and trends with the corresponding text-based web view, but label both views clearly. Search Console defines web multimodal as web results where an image was part of the search; this is not a count of everyone who looked at product photography.

If the team also examines the Generative AI performance report for Search, apply its multimodal filter separately. That report concerns impressions of links in supported Google Search generative AI features, including AI Overviews and AI Mode. Do not add its figures to the overall Search results report as if they were an independent traffic source: Google says generative AI report data is included in the web Performance report. Neither view is Merchant Center product share of voice, and neither identifies purchases.

Absence of a useful view is not proof that visual discovery has no value. Google says metrics begin appearing when a site receives traffic from the relevant queries. Its help also notes that a generative AI report may not appear when a site has not received enough impressions. Record the reporting limitation rather than turning missing data into a verdict about demand.

Choose a small investigation, not a catalog project

A practical first pass is to identify a product category where an image could plausibly start a shopping task, such as a distinctive home furnishing or a replaceable part. That is a prioritization hypothesis, not a claim about how your customers search. In a consistent Search Console view, look for relevant landing pages with multimodal impressions or clicks and note whether the pattern persists beyond a single preliminary day. The Search results report distinguishes clicks from impressions; a page appearing is not the same as a visit.

Then have a merchandiser inspect a short list of those pages against the live catalog. Can someone identify the pictured product and variant? Are material, dimensions, compatibility or other decision-critical facts accurate where relevant? Do the images and page description represent what can actually be bought? Treat these as questions for a human review, not as a presumed explanation for the reporting pattern. Search Console can indicate where attention may be worthwhile; it does not diagnose a missing specification or establish that a content edit will improve rankings.

Give each proposed change a named owner and a reason. For example, an approved task might correct a mismatched product image or add a verified dimension to the corresponding page. Do not add an attribute merely because it seems likely to attract image searches. If the product team cannot verify the fact, the right outcome is to leave it out and resolve the source data first.

Define what would count as progress

Before approving work, save the relevant Search Console view or export, the affected URL list, the date range and the proposed edits. Google says the multimodal data can be exported. Assign an effort estimate and decide when the team will review the same scope again. Avoid grading a change using the newest dotted-line data: Google describes the most recent Search performance figures as preliminary and subject to change.

At review time, report three lines separately. First, what happened to multimodal impressions and clicks for the relevant pages in the comparable view? Second, which approved product-information changes were actually made? Third, what happened to visits and orders in the retailer’s own analytics and commerce records, if those records can be matched responsibly to the work? A change in Search Console visibility alone cannot establish incremental revenue, and an order total alone cannot attribute causality to an image or specification edit.

If the signal is thin, inconsistent or unrelated to commercially important products, defer broader work. If a coherent set of relevant pages shows sustained activity and the review uncovers verified, fixable information gaps, approve a limited correction and measure again. The new report earns its place in an ecommerce operating review when it helps decide what not to do as well as what to test next.