Search Console’s Block Flattening for AI Overviews: Why Position Is the Wrong Metric
TL;DR
Search Engine Journal contributor Taylor Dan (@TaylorDanRW) reports that Search Console uses “block flattening” for AI Overviews (AIOs). Block flattening can make weak AI Overview visibility look like a top ranking in your data. The article’s advice is to stop treating reported position as proof of success and to measure visits and conversions instead. If you report on AIO performance using position, this is worth a closer look.
What the Sources Say
This article rests on one source, a Search Engine Journal piece. The package contains only its headline and a short summary, not the full text. Everything below is limited to what that summary says.
The headline is “Search Console Uses Block Flattening For AIOs, Forget Position & Focus On Outcomes.” The summary gives the core claim in one sentence: block flattening can make weak AI Overview visibility look like a top ranking, so you should measure visits and conversions to assess search performance.
That gives us three points to work with.
1. Search Console applies block flattening to AI Overviews. The headline says so directly. The summary doesn’t spell out the mechanics, so I won’t guess at them. The takeaway is that the way Search Console reports AIO data isn’t a neutral window onto what searchers see.
2. The result can be misleading. According to the summary, block flattening can make weak AI Overview visibility look like a top ranking. In other words, a position number that looks strong may not reflect strong visibility. Nothing in the source suggests the reverse problem, where strong visibility looks weak.
3. The recommended fix is to measure outcomes. The summary says to measure visits and conversions. The headline puts it more bluntly: “Forget Position & Focus On Outcomes.”
Consensus and contradictions
With a single source, there’s no cross-source consensus to report and no conflicting viewpoint to weigh. The package contains no community discussion (the item has zero comments and a zero score), no YouTube coverage, no competitor comparisons and no tool pages.
So I can’t tell you whether the wider SEO community agrees with this take. What I can say is that the source is clear and internally consistent: position data for AIOs can flatter you, and outcome data is the safer yardstick.
Why This Matters for How You Report
The source doesn’t go into specifics, but its framing carries a practical implication. Many SEO reports use average position as a headline number. If block flattening can turn weak AIO visibility into a top-looking ranking, a position-based report could tell a more flattering story than reality supports.
The source’s answer is to move the measuring stick away from where you appear and toward what happens afterward. Visits tell you whether people actually arrive. Conversions tell you whether those visits matter to the business. Neither depends on how a report flattens a block.
This is a reporting-discipline argument, not a tactical one. The source doesn’t claim you should abandon Search Console, and it doesn’t say position data is worthless everywhere. Its claim is narrower: for AI Overviews, don’t let position stand in for performance.
What to Track Instead
The source doesn’t offer a formal framework, but its headline and summary imply this contrast:
| Metric | What the source implies | Reliability for AIO performance |
|---|---|---|
| Reported position | Can look like a top ranking even when AIO visibility is weak, due to block flattening | Treat with caution |
| Visits | Shows whether searchers actually reach your site | Recommended |
| Conversions | Shows whether those visits produce business results | Recommended |
Pricing & Alternatives
The source package contains no pricing information, and no alternative tools or competitors were identified. I won’t invent any. The source doesn’t mention what Search Console costs or compare it with other products.
The one “alternative” in play is a different approach to measurement: outcome metrics (visits and conversions) in place of position. How you collect those depends on your own analytics setup, which the source doesn’t cover.
The Bottom Line: Who Should Care?
SEO professionals and agencies that report on position. If your client reports lean on average position, especially for queries where AI Overviews appear, the source gives you a reason to rethink them. A strong-looking number may be hiding weak visibility.
Content marketers judging whether content “works.” The advice to focus on outcomes means judging content by the visits and conversions it generates, not by how it appears to rank.
Marketing leads reading SEO dashboards. If you see impressive position numbers for AIO-heavy queries, ask what visits and conversions look like before celebrating.
Everyone else. If AI Overviews don’t touch your keywords, this matters less. The source is specifically about how Search Console treats AIOs.
The main caveat is how little we have to work from. The package includes only a summary of one article. It doesn’t explain how block flattening works, which queries or reports it affects, or how large the distortion can be. If you plan to change your reporting, read the full Search Engine Journal piece first and confirm the details against your own Search Console data.
The source’s core message is simple. When a metric can be made to look good by how it’s calculated, trust the outcomes that happen after the click.
Sources
- Search Engine Journal (via @sejournal, @TaylorDanRW): Search Console Uses Block Flattening For AIOs, Forget Position & Focus On Outcomes
Editor’s note, not for publication: the source package held only one article summary, so this piece runs well under the requested 1500-2000 words. Reaching that length would have meant adding claims the source doesn’t support. I’d suggest enriching the package with the full article text or more sources before publishing a longer version.