Google Search Console AI Reporting 2026: Block Flattening, Multimodal Filters, and New Ad Metrics

The key change shaking up the digital marketing landscape in September 2026 is Google Search Console's application of 'block flattening' for AI Overviews and the simultaneous launch of a dedicated multimodal search filter. These updates fundamentally alter how publishers and advertisers measure visibility, challenge traditional attribution models, and directly intersect with the new reporting tools arriving in Google Ads for AI-driven campaigns.

What Is Block Flattening and Why Does It Break Traditional SEO Metrics for AI Ads?

Block flattening is a reporting methodology that treats an entire AI-generated summary (like an AI Overview) as a single block. Every link featured within that block is assigned the same top position in the Performance report, regardless of whether the user actually saw or interacted with it. As reported by Search Engine Journal, this means that for AI Overviews, you should "forget position and focus on outcomes."

Search Console Uses Block Flattening For AIOs, Forget Position & Focus On Outcomes

Why This Matters for AI Advertisers

For advertisers running AI Max or Performance Max campaigns, block flattening creates a dangerous gap between perceived visibility and real traffic. If your landing page is cited in an AI Overview, Search Console might report it as being in position 1—the same as the top organic result—even if the link is deeply buried in a lengthy block of AI-generated text or if the user received the complete answer directly in the overview and never scrolled far enough to see the link.

This inflates your reported impressions while the actual click-through rate may plummet. Traditional return on ad spend (ROAS) calculations that rely on Search Console data become unreliable because the platform cannot distinguish between a featured snippet click and an AI Overview citation that generated zero clicks. Advertisers pushing for top rankings based on Search Console data alone are optimizing for a metric that no longer reflects user behavior.

The Practical Shift: From Positions to Outcomes

Industry analysts now advise advertisers to completely abandon position-based optimization for queries that trigger AI Overviews. Instead, the focus should be on outcomes: actual site visits, conversion rates, and assisted conversions. The block flattening update makes it clear that Google views the AI Overview as an integrated feature, not a competition between links. Your goal should be authority and inclusion in the block, not a specific position slot.

The New Multimodal Filter: Tracking Image-Based Searches

On September 24, 2026, Google officially announced web multimodal search performance reporting in Search Console. This new feature adds a filter to the Performance report specifically for searches where users incorporate an image—via Google Lens, Circle to Search, or direct image uploads.

For publishers and ecommerce advertisers, this is a significant expansion of search visibility. According to Search Engine Journal, the multimodal filter allows site owners to see which pages are being reached by these image-based queries, providing page-level reach data.

Google Search Console Adds Multimodal Filter For Image-Based Searches

Implications for AI Ads and Visual Commerce

For advertisers using AI-driven ad platforms, the multimodal filter is particularly valuable. Ecommerce brands running product ads can now see if their product pages are generating organic visibility from visual searches. This data can be cross-referenced with Google Ads performance to determine whether product images are effectively driving both organic and paid visual discovery.

However, there is a major limitation: Google currently provides page-level reach data but does not reveal the specific queries used. Advertisers know that a page was found via an image search, but not what the user was looking for. This limits the ability to reverse-engineer visual search intent or optimize ad copy for those scenarios.

AI Mode and the Traffic Redirection Problem

Beyond the metrics changes, publishers face a deeper challenge. According to a detailed report from Adjacent Media, Google's AI Overviews are "quietly redirecting traffic away from publishers." The report describes how AI Overviews sometimes route clicks to external websites and other times keep users within Google's own AI Mode experience, obscuring this behavior in the metrics available through Search Console.

Google's AI Overviews Quietly Redirect Traffic Away From Publishers

The Walled Garden Concern

This creates a significant attribution problem. An advertiser might see strong impressions in Search Console for a page that is frequently cited in AI Overviews, yet the actual traffic to the site might be declining because users are consuming the content directly on Google. The reported "reach" in Search Console no longer correlates directly to clicks.

For advertisers running AI Ads, this means that Search Console data alone can overstate the value of organic placements in AI Overviews. When calculating assist value or view-through conversions, advertisers must adjust their models to account for the fact that a high impression count does not equate to high user engagement. The introduction of the ability to filter AI Mode prompts in Search Console provides a dedicated lens for this traffic, but the opacity of the redirection logic remains a challenge.

Bridging Search Console to Google Ads AI Max Reporting

While Search Console provides the organic view, Google Ads is introducing its own transparency layer for AI-driven campaigns. On September 24, 2026, alongside the Search Console update, Google announced AI Max reporting, which shows advertisers the complete path from a search term that triggered an ad to the creative shown and the landing page visited.

Google Ads Adds AI Max Reporting and Expands AI Brief

How They Fit Together

The convergence of Search Console's AI Overviews reporting and Google Ads' AI Max reporting gives advertisers a powerful, if complex, workflow:

Feature	Search Console (Organic AI)	Google Ads (Paid AI)
Visibility Metric	Block flattening positions / Page reach	Complete journey from query to landing page
Query Data	Limited (no queries for multimodal; block-level for AIOs)	Full search term path (in beta for AI Max)
Attribution	Opaque (traffic redirection concerns)	Transparent (ad creative to conversion)
Primary Use	Content authority & inclusion optimization	Campaign path optimization & ROAS

For advertisers, this means the old model of optimizing organic and paid search separately is dead. If you are cited in an AI Overview and your AI Max campaign targets the same semantic intent, the Search Console data informs your ad copy and landing page strategy. Meanwhile, the AI Max reporting tells you which specific user journeys converted. Running them in isolation gives an incomplete picture.

Practical Implications for Advertisers and Publishers in 2026

1. Stop Optimizing for Position in AI Overviews

Block flattening makes position meaningless within AIOs. Optimize for authority, structured data, and inclusion. Focus on whether your content is cited, not where it appears in the block.

2. Install and Monitor the Multimodal Filter Immediately

The multimodal filter is live. Segment your traffic to establish a baseline for image-based search performance. For ecommerce brands, this data is critical for understanding how Google Lens and visual search are driving discovery of your product pages.

3. Adjust Attribution Models for AI Overviews

Given the traffic redirection patterns reported by Adjacent Media, treat Search Console impression data for AIO-linked pages with skepticism. Supplement it with server-side analytics and AI Max reporting to get a true picture of user acquisition costs.

4. Use AI Max Reporting as Your Paid-Side Truth Source

The AI Max reporting view is designed to solve the exact opacity issues Search Console introduces. Rely on it for journey-level data and cross-reference it with Search Console's organic data to understand the full ecosystem.

5. Prepare for Walled Garden Behavior

The trend is toward Google keeping users in its ecosystem. Advertisers must diversify their traffic sources and not become entirely reliant on Google-reported metrics for valuation. Content that answers queries completely within an AIO may drive brand authority but yield zero organic clicks.

Why This Matters Right Now

The simultaneous release of these updates—block flattening, multimodal filters, and AI Max reporting—signals a coordinated shift. Google is acknowledging that the search landscape is no longer a list of blue links, and its reporting tools are evolving to reflect that reality. For advertisers and publishers, the window to adapt is narrow. Those who continue to rely on traditional position-based metrics will find themselves optimizing for a model that no longer exists, while those who embrace outcome-based analysis and cross-platform reporting will have a significant competitive advantage in the AI-ad era.