Does the average position in Search Console really mislead you about your true visibility?

Why is the average position such a complex metric to interpret?

The average position in Google Search Console calculates the position of your URL in search results, but this raw data does not take into account the visual complexity of modern SERPs. A page may technically appear in position 15, but if a Knowledge Graph panel, an image carousel, or a OneBox occupy the top positions, your result visually appears much lower on the screen.

The calculation itself poses problems. Google counts all elements: organic results, featured snippets, local packs, images, videos, People Also Ask. Your numerical position never aligns with your actual visual position. And it is this visual position that determines whether the user sees you or not.

In what cases does this metric become downright misleading?

Let’s take a concrete example: you are targeting a commercial query like "SEO agency Paris". GSC shows you position 8. However, in reality, the SERP contains a local pack (positions 1-3), three Google Ads above, a section of "People Also Ask" (4 accordions), and two images. Your organic result is thus actually displayed towards the middle of the second visible page, even if you are technically "top 10".

Informational queries with featured snippets create the same gap. You are in organic position 1, but Google counts your snippet as position 0. As a result, GSC may display position 2 even though you visually dominate the SERP. Or the opposite: position 3 displayed, but stuck under a large snippet and invisible without scrolling.

What does Google’s promised improvement actually mean?

Mueller mentions an ongoing effort to make this metric more useful without detailing the roadmap. We can imagine several avenues: distinguishing between organic position and visual position, weighting according to the size of SERP elements, or calculating the "Above The Fold" ranking. But nothing concrete has been announced.

In the meantime, this statement mainly confirms what practitioners have observed for years: the average position alone is not enough to evaluate your true visibility. It remains useful for detecting trends (rises, sudden drops), but it does not tell you if your users can actually see you.

• The average position does not account for the visual complexity of SERPs (OneBoxes, images, side panels)
• A page in position 20-50 may seem to be on the visible first page depending on the elements displayed above
• Google is working to improve this metric but without a precise timeline or technical details
• The gap between numerical position and visual position is widening on commercial and informational queries rich in features
• This metric remains useful for tracking overall trends, not for assessing the true visibility of a URL

Is this statement consistent with real-world observations?

Absolutely. Any SEO who has compared GSC positions with third-party rank tracking tools (SEMrush, Ahrefs, Ranks) has noted sometimes stark discrepancies. These tools generally capture visual position by simulating a real user, while GSC counts the technical position in the HTML returned by Google. The two rarely coincide on high-value queries.

The problem worsens with SERP personalization. Depending on geolocation, search history, and device, displayed elements vary. GSC aggregates all this into an average that smooths out differences. The result: you lose the granularity that would allow you to identify where you are truly visible.

What nuances should we consider regarding Mueller's assertion?

Let’s be honest: Google has every interest in keeping you focused on internal metrics within GSC rather than third-party tools. This statement can be seen as an attempt to justify the discrepancies observed between GSC and reality. "It’s complex, we’re working on it" — classic.

Furthermore, Mueller does not specify how Google plans to improve the metric. Will they distinguish between organic and visual positions? Will they weight according to the Above The Fold? Will they segment by SERP type? Nothing. This statement lacks actionable substance. [To be verified]: what is the timeline for these improvements? What calculation criteria exactly?

In what cases is this metric still reliable?

For queries with minimalist SERPs (10 blue links, few features), the average position remains relevant. Typically: niche queries, very specific long-tail, non-competitive B2B markets. If the SERP does not contain a featured snippet, a local pack, or a carousel, the numerical position corresponds to the visual position.

The metric is also useful for detecting sudden movements: if your average position drops from 5 to 25 overnight, it’s a reliable alarm signal, even if the exact numbers are debatable. Macro trends (gradual rise, drop after an update) remain exploitable. It’s the URL-by-URL granularity that poses a problem.

What concrete actions should you take to compensate for this GSC limitation?

Stop treating the average position as your sole success indicator. Always cross-reference it with your impressions and especially your CTR. A plummeting CTR despite a stable average position? You’re probably invisible due to SERP elements above you. A high CTR with a mediocre average position? You may be benefiting from a featured snippet or a rich result boosting your visibility.

Invest in a third-party rank tracking tool that simulates real searches and captures the visual position. Compare it with GSC. The discrepancies indicate which queries are muddied by SERP features. For those queries, optimize to capture the features (snippet, image, People Also Ask) instead of blindly aiming for organic position 1.

What mistakes should you avoid when analyzing your positions in GSC?

Never celebrate a "position 1" without visually checking the SERP. You may be technically first but stuck under three Ads blocks, a stolen featured snippet, and a local pack. Your real traffic won’t follow. Always open the SERP in private browsing, check the visual position, and identify competing elements.

Avoid also comparing your positions over long periods without considering SERP evolutions. A position 5 six months ago does not hold the same value as a position 5 today if Google added a video carousel and a "People Also Ask" block in the meantime. SERPs mutate constantly. Contextualize your data.

How can you ensure you’re measuring the right thing?

Create a dashboard that combines average position, impressions, CTR, and real traffic (Google Analytics 4). If these four metrics evolve consistently, your average position is likely reliable. If you see discrepancies (position rises, traffic drops), it’s a sign that the SERP has changed and the numerical position no longer reflects reality.

Manually audit your top 20 strategic queries every quarter. Note the SERP features present, their size, their position. Identify queries where you are invisible despite a good technical position. Prioritize optimization for features on those queries rather than pushing for classic ranking.

• Always cross-reference the average position, impressions, and CTR in GSC
• Use a third-party rank tracking tool to capture the real visual position
• Manually check the SERPs in private browsing for your strategic queries
• Optimize to capture featured snippets and rich results on high-value queries
• Create a dashboard combining GSC data and real traffic GA4 to detect inconsistencies
• Quarterly audit the evolution of SERP features on your top queries