DEV Community: Alexander Todosuik

Google Search Console in 2026: What Your Data Is Actually Telling You (And What It's Not)

Alexander Todosuik — Mon, 20 Jul 2026 09:43:11 +0000

Most people open Google Search Console, look at the numbers, feel vaguely informed, and close it. The metrics look authoritative. They're not always telling you what you think.

Here's what GSC is actually measuring in 2026 — and the traps that make the data misleading.

The Average Position Problem

GSC "average position" is a median, not a mean. If your page ranks #1 for 500 branded queries and #35 for 20 non-branded queries, GSC shows you an average position close to 1. This looks excellent. It means almost nothing about your visibility for the queries that matter to growth.

Fix: Filter by page, then switch to the Queries tab. Sort by impressions. You can now see position by individual query. The branded/non-branded split becomes visible immediately.

Impressions vs. Visibility

An impression is counted when your URL appears in a result that was served to a user — even if they never scrolled to see it. A page at position 8 on desktop generates impressions; most users stop at position 3-4.

What impressions measure: how often Google considers you relevant enough to include.
What impressions don't measure: whether anyone actually saw your result.

CTR is the corrective metric. But CTR norms changed in 2026.

CTR Benchmarks Are Different Now

Pre-AI Overview (2023-2024) CTR by position roughly followed:

Position 1: 22-28%
Position 2: 12-15%
Position 3: 8-11%

Post-AI Overview (2026), when an AI Overview appears above results:

Position 1: 8-11%
Position 2: 5-7%
Position 3: 3-5%

The same ranking now generates roughly half the clicks in queries where AI Overviews appear. GSC doesn't automatically separate these — you have to filter by Search type and look at "AI Overviews" results specifically.

A CTR that looks "bad" at 6% for position 1 might be normal if AI Overviews dominate that query. A CTR that looks "good" at 15% for position 3 might mean there's no AI Overview for that query — worth noting as a different opportunity.

The Query Report Is Where Work Happens

The most actionable part of GSC is the least-used: the query report filtered to positions 4-15 with impressions above 100.

These are pages Google is actively testing — they appear in results but don't get clicked. Common reasons:

Title tag doesn't match the search intent (informational title for a transactional query)
Meta description doesn't differentiate from the pages above you
Result looks like the same answer users can already see in positions 1-3

For these pages, a title tag rewrite often moves the needle within 2-4 weeks. No new content needed.

What's New in 2026

GSC added two data streams that weren't there before:

AI Overviews report: Shows when your content is cited inside an AI Overview response. Being cited doesn't always generate a click, but citation frequency correlates with topical authority signals. Worth tracking separately from standard position data.

Social and video search: YouTube results, Instagram reels, and other social content now appear in Google search results. GSC tracks these separately. If you publish on YouTube, you can now see exactly when your videos appear in Google search — and whether they generate clicks through to your channel or website.

The Weekly Review That Actually Helps

Check impressions trend (16-month view) — looking for structural changes, not week-to-week noise
Filter: Queries, sort by impressions, filter positions 4-15 — identify title/meta opportunities
Filter: Pages, sort by clicks drop (compare last 28 days vs. prior period) — catch pages losing traction
Check Coverage report — any new "Excluded" items or crawl errors

15 minutes, once a week. More useful than daily checks of the same numbers.

Full guide with CTR tables by position, index coverage diagnostics, and CWV interpretation for 2026: Google Search Console in 2026: What Your Data Is Actually Telling You

Which GSC metric do you find most misunderstood in your experience? The average position trap gets people every time.

Google AI Max for Shopping Is Replacing Performance Max — What E-Commerce Sites Need to Know

Alexander Todosuik — Mon, 20 Jul 2026 08:25:25 +0000

Google announced AI Max for Shopping at Google Marketing Live in May 2026. It's the successor to Performance Max for e-commerce advertisers, and the transition is already underway.

Here's what actually changed, what stays the same, and what you need to do before you migrate.

The Core Structural Shift

Performance Max spread your budget across all Google surfaces: Search, Display, YouTube, Gmail, Maps, Shopping. The algorithm decided the mix.

AI Max for Shopping concentrates on shopping inventory specifically: the Shopping tab, product listing ads in search results, and YouTube placements with clear purchase intent. If you were using Performance Max for brand awareness on Display, you'll need separate campaigns for that.

Feed-Driven Creative — The Biggest Change

Performance Max required you to upload asset groups: headlines, descriptions, images, videos. The algorithm assembled ads from those assets.

AI Max for Shopping generates ad creative directly from your Merchant Center product feed. Product titles, descriptions, and attributes become the primary input.

This has a direct implication: the quality of your product data is now the main variable in ad quality. A product title like "Blue Shoes" gives the system almost nothing. A title like "Nike Air Zoom Pegasus 41 Men Blue Size 10 Road Running" gives it everything it needs to match the right queries.

Feed optimization was always important. In AI Max for Shopping, it's the job.

Product-Level Bidding

Performance Max optimized bids at the campaign level with some asset group segmentation. AI Max for Shopping operates at a more granular product level, using individual product performance signals to set bids.

For accounts with diverse product catalogs — different margins, different conversion rates by category — this can meaningfully improve ROAS by automatically pushing budget toward higher-performing products.

What Stays the Same

Smart Bidding remains the underlying bidding mechanism
Merchant Center feed structure is unchanged
Audience signals are still supported
GA4 conversion tracking carries over without changes
No mandatory migration deadline has been announced

Migration Checklist

1. Audit your Merchant Center feed first.
Check: do product titles include primary search terms? Are descriptions complete? Are GTINs accurate? Are images at least 800x800px?

2. Export your Performance Max baseline.
Download 90 days of data filtered to your target market: ROAS, conversion rate, cost per conversion by product category. You'll need this to evaluate AI Max performance.

3. Separate non-shopping goals.
If your Performance Max campaigns run Display or YouTube for brand awareness, create separate campaigns for those before migrating.

4. Set conservative ROAS targets during learning.
Lower your target ROAS by 10-15% for the first 4-6 weeks. The learning period needs room to optimize without triggering budget pauses.

5. Avoid peak sales periods for migration.
The learning phase during Q4 or a major promotional period is a bad combination.

Timing

Google hasn't announced a forced migration date. Eligible accounts will see an upgrade prompt in the Performance Max interface. Running both campaign types simultaneously during a transition period is allowed and gives you a direct comparison.

For full migration timing recommendations and market-specific considerations: Google AI Max for Shopping Is Replacing Performance Max

Is your Merchant Center feed ready for AI Max for Shopping? What's your current feed optimization approach?

Google Ads Deleted Your Historical Reporting Data on June 1, 2026 — What's Gone and What to Do

Alexander Todosuik — Mon, 20 Jul 2026 07:51:44 +0000

If you manage Google Ads accounts and haven't checked your historical reporting data recently, here's something you need to know: on June 1, 2026, Google permanently deleted large chunks of historical reporting data without warning to most advertisers.

This isn't a UI change. The data is gone from the system.

What Was Deleted

Google's updated data retention policy removed:

Search terms report: data older than 18 months (previously kept indefinitely)
Auction insights: data older than 13 months
Placement report (Display/YouTube): data older than 24 months
Custom column history: affected by the above

If you're comparing performance from early 2024 and earlier, you're working with a gap now.

What Still Remains

The deletion was selective:

Campaign-level performance metrics (impressions, clicks, cost, conversions) remain unaffected
Keyword performance data is intact
Ad group and ad-level data is intact
Audience segment reporting is intact

What Google removed is the query-level detail - the specific search terms that triggered your ads and the specific competitors/placements that appeared alongside you. That's the strategically valuable historical context that's now gone.

Why Most Advertisers Are Finding Out Late

The policy update was announced in Google Ads Help documentation, but there was no in-product notification or email to account managers. Most advertisers found out when they tried to pull a year-over-year search terms comparison and noticed pre-2025 data missing.

For agencies managing multiple accounts, this compounds quickly.

What You Can Do Now

Immediate:
Export any remaining data you care about now. In Google Ads, go to Reports > Predefined reports > Search terms, set the date range to maximum available, and download. Do the same for Auction Insights and Placement reports.

Looker Studio:
If you had Looker Studio reports pulling this data, check whether cached/stored report data survived. Some do, depending on how the connector was configured.

BigQuery Data Transfer:
The most future-proof solution is setting up the Google Ads BigQuery Data Transfer. Once configured, it streams daily snapshots of your Google Ads data into BigQuery where you control retention.

Setup overview:

Enable BigQuery API in Google Cloud Console
Go to BigQuery > Data Transfers > Create Transfer
Source: Google Ads
Connect your MCC or individual account
Set destination dataset and schedule

This won't recover deleted data, but it prevents future losses.

Third-party tools:
If you use Optmyzr, WordStream, or similar platforms, check whether they cached your historical search term data before June 1. Some retention policies vary by tool.

The Practical Impact

For most ongoing account management, this change doesn't affect daily operations. Campaigns, keywords, and audience data are intact.

Where it hurts:

Year-over-year seasonal analysis using specific search terms
Competitor tracking via auction insights history going back 2+ years
Display campaign placement analysis beyond 24 months
Ad copy and landing page audit trails tied to specific search queries

For accounts with clean BigQuery integration already in place, this is a minor inconvenience. For accounts that relied entirely on the Google Ads interface for historical queries, it's a more significant gap.

Full Documentation

For a complete breakdown of what was deleted, what remains, new retention windows by report type, and a step-by-step BigQuery setup guide, see the full article: Google Ads Deleted Your Reporting Data on June 1, 2026

Have you already set up BigQuery Data Transfer for your Google Ads accounts? What's your current solution for long-term ads data retention? Let me know in the comments.

Google Search Console Now Tracks YouTube and Social Media in Search: July 2026 Update

Alexander Todosuik — Mon, 20 Jul 2026 06:40:14 +0000

Google updated Search Console in July 2026 to include performance data from YouTube videos and social media content appearing in Google Search results. This changes how you measure your total search presence.

What Changed

Before this update, Search Console only tracked your website's pages. If your YouTube video appeared in Google Search and someone clicked it, that click was invisible in Search Console. Same for LinkedIn company pages showing up in branded search results.

The July 2026 update adds a new data layer:

YouTube video impressions and clicks from Google Search results
Social platform content (LinkedIn, Instagram public posts) appearing in Google Search
Cross-platform comparison - website vs. video/social for the same queries

Why This Matters for Developers and Site Owners

If you maintain a site alongside a YouTube channel or active social presence, you have been missing part of the picture. Google Search regularly surfaces YouTube content above organic web results for tutorial, how-to, and review queries.

For example: you might have a blog post on "how to set up hreflang tags" ranking at position 4. But your YouTube tutorial on the same topic might be appearing at position 1 in the video carousel - and generating more clicks than the article. Until now you could not see this in one place.

The new data lets you answer:

Is my YouTube channel or my website driving more Google Search clicks for tutorial content?
Which queries surface my social profiles prominently in Google Search?
Where should I invest content creation time - text or video?

How Google Search Actually Uses Social and Video Content

YouTube carousels appear for how-to, tutorial, and entertainment queries. Google surfaces them prominently because YouTube is Google-owned and deeply integrated into the indexing pipeline.

Social profile appearances mostly happen for branded queries. Search for a company name and you will usually see their LinkedIn page, Twitter/X profile, or Instagram account in the results alongside the company website.

Indexed social posts - some public posts (Twitter/X, LinkedIn articles, Facebook public pages) get individually indexed and can appear as standalone search results.

Setting It Up

Go to Google Search Console
In Settings, look for the option to add additional properties or associate external platforms
Add your YouTube channel as a property (or associate it with your existing domain property)
Once verified, YouTube data will appear under Performance with a filter for video/social search type

The verification process is similar to verifying a website property - you confirm ownership via Google account association.

Practical Patterns to Look For

High video impressions, low video clicks in Google Search: Your YouTube videos appear in search but users are not clicking from Google. This often means the video thumbnail or title is not compelling enough in the search context, even if the video performs well directly on YouTube.

YouTube driving more Google Search clicks than your website for specific queries: This is the most actionable finding. It means video is the preferred format for those queries on Google Search, and investing in more video content for similar topics would likely outperform additional text articles.

Social profiles appearing for branded queries: If your LinkedIn or Instagram is appearing prominently when people search your brand, this is your branded search footprint. The new data shows whether users are clicking these social appearances or going directly to your website.

The Connection to AI Overviews

Google also added AI Overview performance tracking to Search Console in June 2026 (a separate update). Between the two updates, you can now see:

How your website pages perform in standard organic search
How your website content performs when cited in AI Overviews
How your YouTube videos and social content perform in Google Search

Together this gives a complete picture of your total Google Search footprint across all content types.

More detail on using both new reports for multiregional SEO strategy: yositeup.com/en-us/blog/google-search-console-social-video-platforms-2026/

Has anyone verified their YouTube channel in Search Console yet? Curious whether the data matches what you expected from your YouTube analytics, or if there are surprises in which queries drive Google Search clicks vs. direct YouTube views.

Google Search Console Added AI Overview Reports: What the June 2026 Update Means for SEO

Alexander Todosuik — Mon, 20 Jul 2026 05:44:31 +0000

In June 2026, Google quietly rolled out something SEO professionals have been asking for since AI Overviews launched: a dedicated performance report in Search Console that separates AI Overview traffic from standard organic traffic.

If you have been staring at your Search Console data wondering why impressions went up but clicks went down, this report is what you need.

What the Report Actually Shows

Before June 2026, Search Console showed one combined number for organic impressions and clicks. When an AI Overview appeared above your result and users read the answer there instead of clicking through, that behavior was invisible in your data.

The new AI performance report adds a filter under Performance > Search type that isolates:

AI Overview impressions - how many times your content appeared in or alongside an AI Overview
AI Overview clicks - how many users clicked from an AI Overview context to your site
Standard organic impressions and clicks - unchanged from before

This separation finally lets you answer a question that was previously impossible to answer from GSC alone: is my traffic drop caused by losing rankings, or by keeping rankings but losing clicks to AI Overviews?

How to Find It

Open Google Search Console
Go to Performance > Search results
Click the "Search type" filter (previously showed Web, Image, Video, News)
You will now see an AI Overview option in the dropdown
Select it to isolate AI Overview performance data

The data goes back to when AI Overviews started rolling out, so you can compare periods.

Three Patterns the Data Reveals

Pattern 1: High AI impressions, near-zero AI clicks

Your content is being cited inside AI Overviews (Google pulls from it to generate the answer) but users are not clicking through to your site after reading the overview. This is the most common pattern for informational content. It means your content is authoritative enough to be cited, but the AI Overview is satisfying the user's intent completely.

Pattern 2: High AI impressions, significant AI clicks

Your content is driving clicks even when an AI Overview is present. This happens when the AI Overview cites your site prominently and users want more detail. FAQ-structured content and in-depth guides show this pattern more often than basic overviews.

Pattern 3: Zero AI impressions despite ranking well

Your content ranks in standard organic results but is not being pulled into AI Overviews. This can mean the content format is not AI-Overview-friendly, or the topic is not one Google generates AI Overviews for (commercial transactional queries often don't trigger AI Overviews).

What This Means for Content Strategy

The most actionable insight from the new report: if your content has high AI impressions but near-zero AI clicks, the AI Overview is replacing your traffic, not supplementing it. The standard SEO response of "keep ranking #1" is not the full answer anymore.

Content that earns AI Overview citations AND clicks tends to:

Answer the core question in the first 2-3 sentences
Provide additional data, context, or case examples the AI Overview cannot fully replicate
Use clear FAQ structure (Google's AI Overviews pull FAQ content heavily)
Include original numbers or analysis that add value beyond the summary

The goal shifts from "rank above the AI Overview" (impossible) to "be cited inside it, and give users a reason to click through for more."

The US Market Specifically

AI Overviews appear on an estimated 40-50% of informational queries on Google.com. That is higher than any other regional Google version. If your site targets US traffic, the new Search Console AI data is especially important to check now - the US market is where the AI Overview impact on CTR is most pronounced.

Getting Started

Connect your YouTube channel in Search Console while you are there. Google also added social and video platform tracking in July 2026, meaning you can now see how much Google Search traffic your YouTube videos generate separately from your website traffic.

Full breakdown of both updates and how to use them for US, Polish, and Ukrainian market SEO: yositeup.com/blog/google-search-console-ai-performance-reports-2026/

Have you checked the new AI Overview report for your site yet? What patterns are you seeing? The data is surprisingly different depending on whether your content is informational vs commercial.

hreflang in 2026: 5 Mistakes That Still Break International SEO

Alexander Todosuik — Sun, 19 Jul 2026 11:20:58 +0000

hreflang is one of those things that looks simple in the documentation and causes real problems in production.

We manage multiregional websites across the US, Polish, and Ukrainian markets. hreflang implementation issues are the most common reason why international sites lose rankings after migrations, CMS updates, or region expansions. The errors are usually not random - they cluster around the same five patterns.

Here they are, with what actually happens when each one occurs.

1. Missing self-referencing hreflang

Every page in an hreflang set must include a reference to itself.

If your English US page has hreflang tags pointing to French and German versions but does not include hreflang="en-US" pointing to itself, Google treats the self-reference as absent. The page may not be correctly associated with its own language+region signal.

The fix: every page in the set must have a complete hreflang list that includes itself.

<!-- On the en-US page, include ALL of these: -->
<link rel="alternate" hreflang="en-US" href="https://example.com/en-us/page/" />
<link rel="alternate" hreflang="pl-PL" href="https://example.com/pl/strona/" />
<link rel="alternate" hreflang="uk-UA" href="https://example.com/uk/storinka/" />
<link rel="alternate" hreflang="x-default" href="https://example.com/en-us/page/" />

2. Inconsistent canonical + hreflang pairing

hreflang signals must point to the canonical version of a page.

If page A has canonical="B" and page B has hreflang pointing back to page A, Google receives contradictory signals. The canonical says "B is the real page" but hreflang says "A is the regional version." Google will typically follow canonical and may ignore the hreflang.

This happens frequently after CMS migrations where URL structures change but hreflang tags are copied from the old sitemap without updating to match new canonicals.

What to check: for every URL in your hreflang set, confirm the canonical tag on that page points to itself (or to the URL you specified in hreflang). If the canonical differs from the hreflang URL, one of them is wrong.

3. x-default pointing to a redirecting URL

x-default is supposed to handle users who do not match any specific language. Most implementations set it to the homepage or the English version.

The problem: if x-default points to a URL that redirects (e.g., /en/ redirects to /en-us/), the signal degrades. Google follows redirects, but a redirect chain in the hreflang set is a reliability issue, especially on sites with complex redirect logic.

Set x-default to the final destination URL after all redirects resolve. Run a crawler periodically to confirm that hreflang URLs in your sitemap return 200, not 301.

4. hreflang implemented in sitemap but not in page HTML

Google accepts hreflang signals from three sources: HTTP headers, page HTML <head>, or XML sitemap.

Sitemap implementation is common because it centralizes management. The problem: if the sitemap is not fetched recently or has errors, the signal disappears entirely for affected pages.

Page HTML <head> implementation is more resilient because the signal travels with the page on every crawl.

For large sites where HTML implementation is impractical, use both: sitemap as the primary source and spot-check a sample of high-priority pages to confirm HTML <head> implementation matches.

5. Language codes that do not match actual page content

hreflang="ru-PL" tells Google: "this page is in Russian, intended for users in Poland."

If the page is actually in Polish (not Russian), the signal is wrong. Google's language detection on the page content will not match the hreflang declaration, and the signal will be partially or fully discarded.

This happens when teams copy hreflang templates across regions and forget to update the language code. It also happens when multilingual sites serve pages in a fallback language (e.g., English) for regions where a local translation does not exist, but still declare hreflang for the local language.

If a full translation does not exist for a region, either do not include that region in the hreflang set, or serve actual content in the declared language. Placeholder or template content in the wrong language is worse than no hreflang signal.

Practical audit process

Before auditing hreflang, pull all URLs from your sitemap and confirm each one returns 200. Any 301 or 404 in the hreflang set invalidates signals for all pages in that group.

Then check three things per page:

Self-reference present in hreflang
Canonical URL matches the hreflang URL for this page
x-default URL returns 200 with no redirect

For sites with 10+ regional versions, automated crawlers handle this better than manual audits. Screaming Frog and Sitebulb both have dedicated hreflang reports. Run them after any URL structure change, CMS migration, or sitemap rebuild.

hreflang is not the most technically complex thing in SEO. But it is one of the highest-leverage things to get right for international sites. A misconfigured hreflang set can split ranking signals across regional versions for months without any obvious diagnostic signal in Google Search Console.

The five patterns above cover roughly 80% of the hreflang issues we find in site audits. Check these first before looking for more exotic causes.

Alexander Todosuik is the founder of YoSiteUP, an SEO agency working across the US, Polish, and Ukrainian markets: yositeup.com

Google Core Updates in 2026: What Actually Changed and How to Diagnose Your Site

Alexander Todosuik — Sun, 19 Jul 2026 07:28:00 +0000

Google rolled out three core updates in the first half of 2026. Here is what changed, what the data shows, and a practical diagnostic process for sites that were affected.

What changed in 2026 core updates

The pattern across 2026 updates follows a consistent theme: Google is adjusting how it weights content that answers questions directly versus content that creates genuine value beyond the answer.

This sounds abstract until you look at the data. Sites that lost rankings in the March 2026 update mostly fell into two categories:

Content built specifically to match query intent without any differentiation from the existing top results
Sites where the majority of traffic came from AI-generated or templated content at scale

Sites that gained fell into two different categories:

Primary sources — original research, firsthand data, case studies from real accounts
Authoritative guides with clear expert attribution and specific, attributable claims

How to diagnose whether a core update hit your site

Open Google Search Console. Do not start with rankings tools.

Step 1: Identify the date

In GSC, look at the Performance report on the Pages tab. Switch to a date range that shows 6 months. Look for a sharp drop in impressions (not just clicks). If the drop corresponds to within 2 weeks of a confirmed core update date, you have your answer.

Step 2: Identify which content was affected

Sort the Pages report by impressions, descending. Find the pages where impressions dropped most significantly in the affected period. These are your diagnostic pages.

Step 3: Classify the affected content

For each affected page, ask:

Does this page cite primary data, or does it repeat information available elsewhere?
Is the author or source clearly identifiable and credible for this topic?
Would a user who gets the answer still benefit from reading the full page?

If the answer to all three is no, the page is at risk and needs reworking rather than optimization.

What does not help after a core update

Changing meta descriptions, adding schema markup, or increasing word count on affected pages will not reverse a core update impact. Core updates are about site-level quality signals, not individual page optimization.

The only reliable recovery path: improve the actual quality of the content that was affected, then wait for Google to recrawl and reassess. This typically takes one to three months after the next core update.

The one metric that predicts core update resilience

Before publishing any new piece of content, ask: if Google's AI summarized this page in one sentence, would there be any reason for the user to still click through?

If yes, the content has intrinsic click value — something unique, a tool, a dataset, a specific perspective. These pages hold up through core updates.

If no, the content's only job is to intercept a query. These pages are at risk whenever Google's understanding of what "quality" means shifts.

YoSiteUp tracks ranking and traffic data across US, Polish, and Ukrainian markets. More SEO data and analysis at yositeup.com/en-us/blog

We Ranked #1 on Google. Our Client Traffic Dropped 59%.

Alexander Todosuik — Sun, 19 Jul 2026 02:15:28 +0000

We Ranked #1 on Google. Our Client's Traffic Dropped 59%.

This is not a hypothetical. This is data from a real client, in a real market, in 2026.

The site held position #1 for a target keyword. It had been there for 11 months. Ranking was stable. We had done everything right: technical SEO, content depth, backlinks, Core Web Vitals.

Then Google rolled out AI Overviews broadly in the US.

The ranking did not change. The traffic dropped by 59% on that query.

The measurement problem

Most SEO teams still measure success with rankings. Position tracking is the default metric in every tool on the market.

But rankings and clicks are no longer the same thing.

A ranking tool will tell you that you are in position #1. Google Search Console will tell you that your CTR on that query dropped from 27% to 11%. Those two facts can exist simultaneously. The ranking tool shows green. The business loses more than half its organic traffic on a specific keyword.

We ran this analysis across a set of clients in the US market. The pattern was consistent. Queries where Google introduced an AI Overview above the organic results showed CTR drops of 40% to 75% depending on query type and the quality of the AI Overview generated.

The overall average for position #1 results in affected queries: from 27% CTR to 11% CTR. A 59% drop.

What types of queries are most affected

The impact is not uniform across all search queries. There is a clear pattern:

Queries where AI Overview appears AND extracts a complete answer: CTR drop of 60-80%. These are definitional queries, simple how-to questions, basic fact lookups. The user gets what they need inside the search result. There is no reason to click.

Queries where AI Overview appears BUT requires task completion: CTR drop of 10-25%. These are commercial queries, service lookups, product research where the user ultimately needs to do something a search result cannot do for them.

Queries with NO AI Overview: No meaningful change.

The practical implication: content built around answering questions directly - which was the dominant SEO strategy for the last five years - is now the content most at risk. The better your content answers the question, the more likely Google uses it in an AI Overview, and the less likely the user clicks through to your site.

How we changed the measurement approach

The immediate fix was separating query types in reporting.

We pulled all queries from Google Search Console and segmented them by whether they were likely to trigger AI Overviews (based on intent: informational, definitional, procedural) versus unlikely (transactional, local, navigational, branded).

For the informational/AI Overview category: we tracked citation appearances rather than clicks. Being cited in an AI Overview generates brand impressions even when it does not generate clicks. That has value, even if it does not match the old traffic model.

For the non-AI-Overview category: standard CTR and traffic tracking continued normally.

For the client where the 59% drop occurred: once we separated these two buckets, it became clear that non-AI-Overview traffic had actually increased 12% over the same period. The site was performing well. The specific traffic source that declined was queries where the user's question was fully answered before the click.

What we are testing as a response

Three changes we have implemented across affected accounts:

One: Moving editorial focus away from pure informational content toward content that requires user action. Tools, calculators, configuration flows, comparison tables that need interaction. These create a reason to click that an AI Overview cannot replace.

Two: Optimizing specifically for AI Overview citation. There is brand value in being cited even without the click. Content that cites primary data, takes a clear position, and uses Q&A structure is more likely to be cited. We have seen citation rates increase with structured content.

Three: Tracking branded search volume as a secondary metric. If AI Overviews increase brand awareness for cited sites, branded search should reflect that. Early data is inconclusive but we are watching it.

The metric that actually matters now

Ranking is a leading indicator. Traffic is a lagging indicator. Both are now less reliable as direct revenue predictors because a ranking can coexist with a traffic drop.

The question worth asking about every piece of existing content: if Google puts this answer in an AI Overview, does the user still have a reason to visit our site?

If yes: the content is well-positioned for the current environment.

If no: the content needs to evolve into something that creates a reason to click, or you need to accept that its job is now brand awareness through citation rather than direct traffic.

Neither answer is wrong. But you need to know which one applies to each piece of your content strategy before your next planning cycle.

YoSiteUp is an SEO agency working across the US, Polish, and Ukrainian markets. Data referenced in this article comes from client accounts in the US market, January-June 2026. Full analysis: yositeup.com/en-us/blog/google-ai-overviews-ctr-drop-2026