A corrected canonicalization problem may not disappear from Google Search immediately. According to the supplied report, Google’s updated troubleshooting guidance says affected pages can remain in a duplicate cluster for up to two weeks after the underlying content issue has been fixed.
That distinction matters when evaluating a repair. The visible search result can lag behind the site change, so an unchanged canonical selection during this window is not, by itself, evidence that the fix failed.
What the two-week window does and does not mean
The source reports that Google added the timing clarification near the beginning of its canonicalization troubleshooting guide. The stated period is an allowance of up to two weeks, not a promise that every case will take that long or resolve at the end of a fixed countdown.
It is therefore best understood as an observation window. Once Google has processed the relevant update, teams may need to allow the full period before treating the continued clustering of a page as a persistent problem. Making another change too quickly can blur the result of the original repair and make diagnosis harder.
Page similarity is central to duplicate clustering
The reported guidance also explains an important condition behind canonicalization: pages must be sufficiently similar for Google’s systems to place them in the same duplicate cluster. Google then selects one version from that group as the canonical page.
This connects the timeline to the substance of the fix. If two URLs still present substantially similar material, changing a preference signal alone may not immediately alter how the system groups them. By contrast, the source says clearer differences in the content can help prompt faster reevaluation.
That does not make content differentiation a universal remedy. Some URLs are intentionally duplicate or near-duplicate versions and should remain consolidated. The useful question is whether the observed cluster reflects the site’s intended relationship between the pages.
A monitoring sequence that preserves diagnostic clarity
The two-week guidance supports a more disciplined way to assess canonicalization work:
Confirm that the underlying content issue has actually been corrected and that the intended relationship between the URLs is unambiguous.
Record when the corrected version became available for Google to process.
Observe the affected URLs during the reported window without repeatedly changing the same pages.
If the unwanted clustering persists after sufficient time has passed, reassess whether the pages remain similar enough to justify Google’s selection.
Separate a delayed response from a genuinely incorrect outcome before planning another intervention.
This sequence avoids treating every day of unchanged results as a new failure. It also preserves a cleaner connection between a particular change and the eventual search outcome.
Key takeaways
The supplied report says canonicalization fixes can take up to two weeks to appear in Google Search.
A page may remain in an existing duplicate cluster while Google reevaluates the corrected content.
Clustering depends on pages being sufficiently similar, so the actual relationship between their content remains important.
A continued canonical selection inside the reported window is not conclusive proof that a repair failed.
Teams can reduce unnecessary rework by documenting the change, allowing time for processing, and reevaluating only after the observation window.
Going forward, canonicalization reviews should pair technical correctness with patient measurement: make the intended page relationship clear, preserve a stable test period, and judge the result only after Google has had time to reconsider the cluster.
I’m tracking a growing Google Business Profile issue after several days of complaints from businesses that say reviews have disappeared from their local listings. Google has now confirmed that it is investigating the reports, and in some cases, review submissions on affected profiles appear to be paused.
What Google said. Google told us that when its systems detect suspicious review activity, it may take several actions, including removing reviews and temporarily pausing reviews on a profile to prevent further abuse. Google also said it is investigating the issue and will restore any reviews that were incorrectly removed.
What I’m seeing. As I documented on the Search Engine Roundtable, there are dozens of complaints in the Google Business Profile Forums from business owners and local SEOs who say their reviews have mysteriously vanished. In some cases, businesses are also unable to receive new reviews on their local listings.
From what I can tell, Google’s review spam detection systems may be identifying certain patterns and aggressively removing or blocking reviews on suspected Google Business Profiles. What remains unclear is whether this is tied to spammers abusing some profiles, a recent algorithmic adjustment, or Google’s systems becoming overly sensitive.
More details. Amy Toman, a volunteer Google Product Expert for Google Business Profiles, shared on LinkedIn that businesses or clients affected by this issue can post in the forum if they want to, but Google is already aware of the problem and working on it. She also noted that no timeline for a resolution has been provided yet.
She said she is seeing a new pattern where, after fake or spam reviews are reported, some Google listings receive a review block and all reviews are hidden. In at least one case, she said the rating was reduced to 0.
Why I care. If I noticed a sudden drop in reviews or stopped receiving new reviews this week, I would consider this issue a likely explanation. For local businesses, reviews can directly affect trust, visibility, and customer decisions, so even a temporary review disruption can be frustrating.
Google is investigating, and I’m watching to see whether missing reviews are restored and whether affected Google Business Profiles can begin receiving new reviews again.
Google’s June 2026 spam update completed a short global rollout that applied across languages and locations. The practical challenge now is determining whether a site’s changes are plausibly connected to the update rather than treating every movement as evidence of a spam penalty.
The two reports establish the rollout’s timing, scope, and purpose while also highlighting an important recovery distinction: correcting a policy problem can support improvement over time, but rankings previously gained through devalued spam links may not return.
Rollout timing, scope, and context
The launch report said the update began around noon ET on Wednesday, June 24, 2026. Google described it as a global update affecting all languages and indicated that deployment could take a few days.
The completion report said Google marked the rollout complete at 2 p.m. ET on June 26. It was the second announced spam update of 2026, following the March spam update. The launch report placed it within a wider run of changes that also included the February Discover update and the March and May core updates.
Key takeaways
The reported rollout ran from June 24 to June 26, 2026.
Google said the update applied globally and across all languages.
The sources described it as a standard spam update, not specifically as a link spam update.
Sites should evaluate changes against the rollout window and review compliance before making broad corrective changes.
What the update was designed to address
According to the launch coverage, spam updates improve Google’s automated ability to identify attempts to manipulate search rankings. The report cited SpamBrain, Google’s AI-based spam-prevention system, as an example of the systems involved in detecting established and emerging forms of abuse.
That purpose does not establish why any individual page gained or lost visibility. The completion report noted that spam updates can sometimes affect sites that were not deliberately trying to manipulate Google. It also characterized this rollout as feeling somewhat larger than the March spam update, but presented no measurement that would turn that impression into a general conclusion.
How to investigate a possible update impact
A useful assessment separates timing, scope, and cause. Because several named Google updates preceded this rollout, a ranking change should not be attributed to the June spam update solely because it occurred during a busy period.
Confirm the timing. Compare Search Console, traffic, and ranking patterns before, during, and after the June 24-26 rollout window.
Identify the scope. Determine whether the change is sitewide or concentrated among particular pages, queries, or content groups.
Check unrelated explanations. Review recent publishing, technical, tracking, and site-template changes that could produce a similar pattern.
Review Google’s spam policies. Examine the affected areas for practices intended to manufacture ranking signals or otherwise abuse search systems.
Match corrective work to evidence. Address confirmed policy or quality problems instead of making indiscriminate changes based only on temporal correlation.
Recovery depends on what caused the loss
The launch report said sites that violate Google’s spam policies may rank lower or disappear from results. After violations are corrected, improvement may occur over time if Google’s automated systems recognize that the site is compliant. This is not presented as an immediate or guaranteed recovery mechanism.
Link-related losses require a different interpretation. The same report explained that when Google neutralizes the ranking value of spammy links, the advantage previously produced by those links is lost; removing or cleaning up the links does not recreate that former benefit. However, neither source identified the June 2026 rollout as a link spam update, so that limitation should be applied only when the evidence actually points to devalued links.
The most defensible next step is continued monitoring paired with a focused compliance review. Decisions made from page-level evidence will be more useful than reacting to the rollout label alone, especially while post-update patterns become clearer.
I recently explored Google’s updated guidelines for site moves, specifically about handling all domain variants using their Change of Address tool. This update aims to clarify the process of moving your site from one domain to another, ensuring a smooth transition for all domain variations.
Google’s advice is straightforward: enter every domain variant in their Change of Address tool during a site migration. They emphasize this in their documentation to prevent potential indexing issues.
Google’s Note: They encourage submitting requests for each subdomain and the www and non-www variants of your previous domain. For instance, ensure you submit en.example.com, www.example.com, and example.com if you’re moving to new-example.net, even if these variants aren’t actively used. It’s crucial to have them verified in the Search Console for a seamless migration.
Understanding domain variants is key. These include subdomains and different TLDs, allowing for a comprehensive transition from your old site to the new one without hiccups.
Why It Matters: Proper domain migration ensures that all site variants migrate without issues, which Google confirms as the best practice for SEO. Following Google’s guidelines can significantly mitigate the stress associated with site migrations.
For any SEO practitioner or site owner, site moves can be daunting. However, adhering to these detailed steps can make the transition less overwhelming. The Change of Address tool is designed to expedite this process, so making the most of it is essential.
A Google manual action is more than a ranking problem for a business that depends on organic discovery. It can disrupt revenue, raise acquisition costs and place planned growth on hold while the organization investigates practices accumulated across content, links and commercial partnerships.
The practical response is to treat search compliance as an operating discipline. Prevention requires visibility into old and new risks, while recovery requires evidence that the underlying system has changed rather than a handful of questionable pages being removed.
Key takeaways
A manual action follows an identified policy violation and should not be diagnosed or managed like an algorithmic visibility change.
Legacy links, sponsored publishing arrangements and scaled content can remain liabilities long after the campaigns that created them have ended.
Prevention depends on recurring compliance reviews, clear ownership and controls that cover every team or partner able to publish or acquire links.
Recovery can take months and involve multiple reviews, according to the supplied CrushPress.AI article, so business continuity planning matters alongside SEO remediation.
A credible cleanup addresses the production and approval processes that allowed violations to accumulate, not only the URLs or links that were eventually discovered.
Diagnose the incident before designing the response
Manual actions and algorithmic changes can produce a similar visible symptom: declining search traffic. Their causes and remedies are different. The source article describes a manual action as a response to a verified violation of Google Search Essentials, whereas an algorithmic decline does not by itself establish that a reviewer found a specific policy breach.
That distinction prevents two costly mistakes. The first is treating a confirmed compliance issue as an ordinary ranking fluctuation and waiting for it to reverse. The second is assuming that every traffic decline is punitive, then making broad changes without evidence. Teams should establish what triggered the investigation, which properties and publishing systems are implicated, and whether the problem is isolated or systemic before choosing a remedy.
The business assessment should run in parallel. The supplied article reports that a manual action can affect revenue, customer acquisition costs and expansion plans, with effects that may continue after the policy problems are addressed. Leaders therefore need both a remediation owner and a continuity plan for the period in which organic visibility remains impaired.
Prevention starts with a map of accumulated risk
Compliance exposure rarely belongs to one recent page. The source article presents it as something that can erode gradually: an ecommerce company accumulates questionable links, a publisher embeds commercial content in its main site, a software company produces weak location pages, or a lead-generation operation expands supplemental content without sufficient editorial scrutiny.
A useful audit consequently looks beyond the current editorial calendar. It examines the historical footprint of the site and the business arrangements behind it. Paid placements, commercial guest posts and directory links from earlier campaigns may persist as unresolved liabilities, according to the article. A change in staff, agency or strategy does not remove what remains published or linked.
What a recurring compliance review should cover
Link acquisition: identify who can commission, purchase, exchange or approve links and whether old campaigns remain visible.
Third-party publishing: review sponsored, affiliate, partner and contributor content, including how closely it is integrated with the site’s trusted sections.
Scaled page systems: examine templates, feeds and automation for repetition, unsupported claims and pages whose primary difference is a keyword or location.
Editorial accountability: confirm that named owners can stop publication, demand evidence, update weak material and remove content that no longer meets policy or quality expectations.
Change records: preserve decisions, approvals and remediation evidence so future reviewers can understand how a risky pattern arose and what ended it.
These reviews should be independent enough to challenge established revenue practices. The source argues that even capable internal SEO teams can overlook exposure when the same organization designed or benefited from the underlying programs. Independence can come from a separate compliance owner, a cross-functional review group or qualified external scrutiny; the essential feature is freedom to question the system rather than merely inspect its output.
Publishing scale changes the control problem
Scale does not automatically make content problematic, but it multiplies the effect of weak judgment. The article identifies several patterns that can create exposure: nearly identical affiliate comparisons, cookie-cutter regional service pages, AI-assisted publishing with unsupported information and mass-produced destination material offering little original insight.
The shared weakness is not a particular production tool. It is a system that can publish more quickly than the organization can verify usefulness, originality and factual support. A responsible workflow therefore places controls at the point of production: evidence requirements, sampling rules, approval thresholds, duplication checks and a mechanism for pausing an entire template or pipeline when a pattern fails review.
Third-party content requires equally clear boundaries. The source warns that insufficiently supervised material can place the host publisher’s reputation and broader visibility at risk, including valuable sections unrelated to the problematic partnership. Commercial teams should not be able to bypass the standards applied to staff-produced content simply because a placement is contractually attractive.
Recovery must prove that the underlying system changed
The supplied article characterizes recovery as expensive and potentially prolonged, sometimes taking months and multiple reviews. That makes superficial cleanup a poor strategy. Removing a visible batch of pages while leaving the same incentives, templates, vendor relationships or approval gaps in place does not resolve the source of the exposure.
A defensible recovery sequence
Stabilize the environment. Pause related publishing, link acquisition or partner activity so the suspected pattern does not continue during the investigation.
Define the full scope. Inventory affected pages, links, templates, subdirectories, contributors, vendors and commercial programs rather than reviewing only the most obvious examples.
Trace causes to controls. Determine which incentives, permissions or missing checks allowed the pattern to develop and persist.
Remediate consistently. Remove, revise or otherwise address problematic material according to a documented standard, including older assets created under previous strategies.
Change the operating model. Add accountable owners, approval gates, monitoring and escalation rules that reduce the chance of recurrence.
Preserve evidence. Maintain a clear record of what was found, what changed and how the organization verified the work for any subsequent review.
Recovery ownership should extend beyond the SEO team when the causes involve sales partnerships, affiliate revenue, editorial operations, automation or agency management. Otherwise, the team responsible for cleanup may lack the authority to end the practices that created the violation.
Make search compliance part of business resilience
The strongest prevention program connects search risk to ordinary governance: vendor oversight, publishing permissions, revenue approvals, audit schedules and executive risk reporting. This turns compliance from an occasional technical exercise into a repeatable decision process.
Organizations should also plan for imperfect recovery timelines. Alternative acquisition channels, current customer communications and realistic internal forecasts cannot restore search visibility, but they can reduce the pressure to pursue another risky shortcut while remediation is underway.
As publishing systems and commercial models evolve, the next priority is to review controls before scale is added. A business that can explain who approved a tactic, what evidence supported it and how it will be monitored is better prepared to prevent compliance erosion before it becomes an operational crisis.
Google visibility is often discussed as if it could be improved through a single tactical change: choose a more successful headline pattern, add a machine-readable file, or imitate whatever appears to perform best across a large dataset. The source reporting points to a more demanding conclusion.
A study of Google Discover headlines shows how an apparent format advantage can be driven by publisher and audience differences, while Google’s reported guidance on llms.txt says the file has no effect on Search rankings. Together, these accounts offer a practical way to distinguish an observable characteristic from a credible visibility lever.
Visibility is not one outcome or one mechanism
The two source articles address different Google environments. The Discover analysis concerns how often editorial articles appeared across the 1492.vision fleet. Its metric was hits per article, which the source described as a proxy for visibility rather than a count of Discover clicks. The llms.txt article, by contrast, concerns whether a site-level file affects visibility in Google Search.
That distinction matters because a feature associated with frequent appearances on one surface is not automatically a ranking factor, a cause of traffic, or a general rule for Google visibility. A Discover headline can be correlated with exposure without causing it. A file can help another service understand a site while remaining irrelevant to Google Search. The surface, measured outcome, and proposed mechanism must therefore be identified before a result becomes actionable.
Headline format looks powerful until publisher context is added
The Discover report described an analysis of 1,674,518 English articles and 1,690,295 French articles from the 1492.vision corpus. When publishers were pooled, quote-led headlines produced 37% more hits per article than statements in English and 48% more in French. Questions also exceeded statements in the aggregate, by 7% in English and 16% in French.
Those figures appear to support a simple editorial prescription. Yet the report argued that the aggregate comparison mixed together publishers with different audiences, subject matter, editorial styles, and patterns of Discover exposure. Celebrity publications, regional news organizations, and outlets focused on trending topics were among the types said to use quotations more often. Their underlying visibility could therefore make the quotation format look more effective than it was.
The source identified this as an example of Simpson’s paradox: a relationship visible in pooled data can weaken, disappear, or reverse after the data is separated into meaningful groups. In this case, the relevant test is not simply whether all quote headlines outperform all statements. It is whether the formats perform differently within comparable publishers and contexts, with each publisher serving as its own baseline.
This does not make headline construction irrelevant. It changes the claim that the evidence can support. The reported aggregate results describe where visibility occurred across a mixed population; on their own, they do not establish that converting a statement into a quotation will create the same lift for an individual publisher.
Google’s llms.txt position removes a different false lever
The second source reported that Google updated its AI Search optimization guidance to say that llms.txt files do not affect Search rankings. According to that account, Google Search does not use the files, and publishers do not need to create new AI-oriented text or Markdown files to qualify for inclusion in Search experiences involving generative AI.
The reported guidance includes an important qualification: Google may still discover, crawl, and index various file types. That general ability does not mean llms.txt receives special ranking treatment. The source also noted that a site may maintain the file for other services without improving or damaging its Google Search visibility.
This is a more direct finding than the Discover correlation. The headline analysis asks whether an apparent advantage survives contextual controls. The llms.txt guidance says the proposed mechanism is not used for the claimed Google Search benefit. One tactic requires better causal analysis; the other has been explicitly ruled out as a Google ranking aid in the source’s account.
A stronger test for proposed visibility signals
The synthesis suggests that publishers should evaluate any claimed signal along three dimensions. First, the claimed outcome should be precise: ranking position, impressions, Discover appearances, clicks, or another measure. Second, comparisons should account for publisher, audience, topic, language, and surface whenever those factors could influence both the tactic and the outcome. Third, the proposed mechanism should be checked against Google’s stated use of the feature when relevant guidance exists.
For headline decisions, the most informative evidence would come from comparisons within the same publication and from controlled editorial tests that keep topic and distribution conditions as comparable as possible. Hits per article can reveal exposure patterns, but it should not be presented as click performance or as proof that punctuation and syntax independently caused the result.
For machine-readable files, the decision can be separated by beneficiary. An llms.txt file may be maintained for a non-Google service that uses it, but the reported Google guidance provides no basis for treating its creation as a Search ranking project. This prevents an implementation task from being justified with an unsupported visibility promise.
Key takeaways
Google visibility claims must name the surface and metric; Discover hits, clicks, and Search rankings are not interchangeable outcomes.
The reported quote-headline advantage appeared in pooled English and French data, but publisher and audience differences made a simple format-based explanation unreliable.
Within-publisher comparisons are more useful than global averages when editorial conventions and baseline visibility vary across outlets.
According to the llms.txt source, Google Search does not use the file as a ranking aid, although sites may keep it for other services.
An observable pattern becomes actionable only after plausible confounders and the proposed mechanism have been examined.
As new visibility tactics emerge, the durable editorial advantage will come from asking what was measured, what else could explain it, and whether the platform recognizes the proposed mechanism. That discipline leaves room for experimentation while keeping correlation, platform guidance, and causal claims in their proper roles.
When I heard that Google had added a new help document to its search developer documentation, I knew I needed to dive in. This new document, “Google Search’s guidance on using third-party SEO tools, services, and advice,” provides updated insights into the world of SEO, especially revolving around the hot topic of generative AI optimization.
Google also revamped its “Do you need an SEO?” guide, adding fresh content around generative AI topics. The intent behind these updates, as stated by Google, is to highlight what to consider when evaluating third-party tools and to simplify existing documentation. They want us to be cautious about trusting these tools and advice without proper verification.
Reading through Google’s new guidance, I found some valuable advice on thoughtfully evaluating third-party SEO services. Here’s how they suggest approaching it:
Evaluate external SEO advice against Google’s official guidelines, think critically about third-party tools, and always verify the claims made by these services.
Evaluate and verify external SEO advice against official Google guidelines
Think critically about using third-party SEO tools and services
Assisting in sitemap generation
Establishing indexing directives
Offering to generate “SEO-optimized” content for you
Providing advice to improve the ranking of existing content
Promising improvements for AI experiences and search formats (“AEO” or “GEO” tools)
While Google doesn’t endorse any third-party tools, they emphasized using Google Search Console for credible data directly from Google Search. We need to be wary of tools claiming to guarantee success since they lack access to Google’s internal ranking data.
With the updated “Do you need an SEO?” document, Google has also covered topics like Optimizing for generative AI. It includes essential reminders that if an SEO uses a third-party tool, one should not assume it’s approved by Google, and during audits, access to Search Console should be limited initially.
In essence, before making any site changes based on third-party audits, it’s crucial to cross-reference their advice with Google’s official resources, especially when it comes to AI optimization strategies.
If your SEO offers an audit, scrutinize what’s involved and avoid granting write access to Search Console at first.
Understanding these updates helps us not only in improving our own SEO strategies but also in promoting ethical and effective use of tools.
The document updates come as a reminder for us to regularly check Google’s official documentation. Staying informed about new guidelines ensures that we’re always on the right path in our SEO journey.
Hey there, have you heard about Google’s latest feature within Google Discover? They’ve just launched Search profiles in the U.S., and it’s a game-changer for publishers like me. These profiles act as enhanced landing pages where my audience can not only follow me but also see a collection of my latest articles, videos, and social media posts all in one convenient spot.
Google has been working on this for quite some time, refining and testing it over several months. They’ve even made some tweaks, such as adding shortnames, which make it even easier to share these profiles.
“Search profiles give publishers and creators a central place to showcase their latest articles, videos, and social posts. People can easily follow sources from their profile, so they’re more likely to see that content on Discover, found on the home screen of the Google app.”
It’s described as a “new way for publishers and creators to shape their presence on Search. Search profiles are a dedicated, shareable space to highlight content across platforms and help audiences find accurate, up-to-date information about sources on Search.”
What it looks like: Curious to see it in action? Here’s a video demonstration:
Managing Your Search Profile: If you’re a publisher or creator with a significant following on a major social or video platform, you’re in luck! You’ll be able to claim your Search profile, personalize it with an avatar, bio, and links to your website and social media platforms.
Once you claim your profile, it might even create a Knowledge Panel for you, or enhance your existing one with updated details and a direct link to your profile.
If you’re interested in setting up your own Search profile, check out this guide for creating a profile, claiming an existing one, and managing it.
Availability: Currently, this feature is available in the U.S. for users and publishers who meet a certain follower threshold. Here’s what you need:
TikTok: 300,000 followers
YouTube: 100,000 subscribers
Instagram: 100,000 followers
X: 100,000 followers
Why This Matters: As a publisher, I’m always looking for ways to get more visibility. Google’s new feature allows us to increase our reach not just on Google platforms but across our entire digital presence. It’s an exciting time, though one has to ponder whether this will be enough in the fast-paced world where AI continues to evolve.
As someone who eagerly follows Google’s updates, I was thrilled to learn about the latest developments in Google Search Console. Recently, Google has started to roll out new Search Generative AI performance reports. These reports, along with a feature to block your content in AI responses, are designed to give website owners more control.
Currently, these features are being introduced to a select group of website owners in the UK, but there are plans to expand access in the near future. This gradual rollout allows us to get accustomed to these changes before they become widely available.
Exploring the Search Generative AI Performance Report
The new AI performance report in Google Search Console is something I’ve been anticipating. Although it doesn’t cover everything, it does provide some important insights into how our content is performing within AI responses, AI Mode, and AI Overviews on Google Search. The report includes data on impressions, pages, countries, devices, and dates. However, a notable omission is click data, so we’re left guessing about the exact number of searchers clicking through to our sites from AI responses.
Google stated:
– We’re rolling out new insights for website owners regarding their pages’ appearances in generative AI Search features. These insights include impressions metrics and information on which pages appear in AI responses and in which countries. We’re working closely with website owners to determine what insights would be most helpful and will expand the metrics available over time.
Additionally, Google shared more details about the metrics we can expect:
– Impressions: Frequency of your site’s URLs appearing in generative AI features in Search and Discover.
– Pages: Identifying URLs that appeared within AI features.
– Countries: Understanding visibility on a country basis.
– Devices: Identifying the devices used to view your website. Available for Search results.
– Dates: Monitoring performance with hourly, daily, weekly, and monthly granularity.
I inquired about click data from a Google representative, who mentioned that they are exploring additional metrics that will help inform our strategies in the future.
Initially, this report is available to a subset of users in the UK, with plans to expand globally in the future.
Another exciting feature Google introduced is the ability to block your content from appearing in AI search features like AI Overviews, AI Mode, or AI Discover. Google described this as a “new toggle” within Google Search Console, allowing us to decide whether or not our site should be part of these AI search features.
Google notes that opting out will prevent your site from receiving traffic or impressions from these features. Importantly, this control won’t affect your ranking in standard search results outside of generative AI Search features, so there’s no risk of negatively impacting core web search visibility.
Again, like the performance report, this toggle is currently available to a subset of UK website owners, with plans to widen access as they complete further testing. Google had promised these controls after facing some backlash from the EU, and it’s promising to see them starting to roll out now.
One study even showed that 1/3rd of SEOs are willing to block Google from showcasing their content in AI search features.
Why It Matters
As site owners and publishers, many of us have been asking for control over how and if our content appears in Google’s AI features. Now, we have just that. Although it’s initially limited, I’m hopeful these features will eventually be available to all.
Moreover, we’ve been requesting AI Search reporting from Google from day one. With Google’s announcement following Bing’s release of its own AI performance report, we’re taking a significant step forward. While Google’s report currently targets UK site owners and lacks click data, it holds promise for a global rollout soon.
Your traffic graph dropped during the May core update, and now you need to know whether to rewrite pages, change your SEO strategy, or simply wait. Start by resisting the urge to make sitewide edits. A core update can expose weak content, but it can also coincide with changes in demand, search-result layouts, competitors, or tracking.
The useful response is a page-level diagnosis. You want to identify where visibility changed, determine what those pages now fail to deliver, and improve them without destroying content that still works.
Anchor your diagnosis to the actual rollout
The official rollout ran from May 21 through June 2. Noticeable ranking movement appeared by May 23 and continued into the following week. This was the second core update of 2026, so earlier changes in your reporting may belong to a different event.
Build clean comparison periods
In Google Search Console, compare May 7-20 with June 3-16. These are equal 14-day periods immediately before and after the rollout, without mixing rollout days into either side. If your business has strong weekly or seasonal patterns, compare each period with the equivalent days from a normal prior period as a second check.
Export clicks, impressions, click-through rate, and average position by query and page. A chart of total clicks is not enough. It can tell you that performance changed, but not why.
Separate ranking losses from other traffic losses
If positions declined across several important queries for the same pages, investigate relevance, usefulness, and competition. If impressions declined while positions remained broadly stable, check whether search demand or the set of queries triggering those pages changed. If positions and impressions held steady but click-through rate fell, inspect the live results for new answer features, stronger titles, or a changed search intent.
Also rule out unrelated technical problems. Check whether affected URLs are indexed, canonicalized as intended, crawlable, and returning the correct status code. Review analytics changes, security incidents, migrations, and major template releases. A core-update diagnosis cannot fix a broken canonical or missing tracking tag.
Find the losses that actually need intervention
Sitewide averages hide the decisions you need to make. Group affected URLs by topic, search intent, template, author, and content type. Then calculate the change for each group. A fall concentrated in old comparison pages calls for a different response than a decline across every page using the same template.
Start with URLs that combine three traits: a material visibility loss, meaningful business value, and a problem you can clearly describe. Do not prioritize a page merely because its percentage decline looks dramatic. A page that fell from ten impressions to two is usually less urgent than one that lost a large share of qualified visits.
Inspect the queries that disappeared
For each priority URL, compare its pre-update and later query sets. Ask whether it lost its main query, a cluster of secondary questions, or visibility for terms that never matched its real purpose. Losing poorly matched impressions may not require a repair. Losing the queries that express the page’s central promise does.
Search those important queries manually and examine the pages now appearing above yours. Look for differences in intent, scope, specificity, first-hand evidence, freshness, and format. The goal is not to copy competitors. It is to understand what searchers can accomplish with the current results that they cannot accomplish with yours.
Look for patterns across winners and losers
Your unaffected and improving pages are useful controls. Compare them with declining pages from the same site. If both groups share the same design, author box, and schema, those elements are less likely to explain the difference. If losses cluster around thin location pages, outdated tutorials, or articles built from the same generic outline, you have a stronger hypothesis to test.
Audit for satisfaction, not an imaginary update factor
The update was intended to favor relevant and satisfying content. That direction is more useful than hunting for a new word-count target, schema type, or keyword-density rule. Google has not provided a single prescribed fix for pages that lost visibility.
Test whether the page fulfills its promise
Read the title, opening, and major headings without relying on your memory of the page. They should define one clear task or question. Then check whether a reader can complete that task without returning to search for missing steps, definitions, evidence, or limitations.
Remove introductions that delay the answer. Put the central answer or decision criteria near the relevant heading, then support it with explanation. If the query requires a procedure, make the sequence explicit. If it requires a choice, explain who each option suits and what changes the decision.
Add value that another generic page cannot reproduce
A rewrite that merely changes wording preserves the original weakness. Add the missing substance: a worked example, a transparent method, a limitation, an expert interpretation, a screenshot that proves a step, or an explanation of what happens when the standard advice fails. Keep only material that helps the reader act or decide.
For factual or high-consequence claims, make the basis visible. Identify the responsible organization or expert where that identity matters. Link to supporting material you actually used. Show when the page was reviewed, and update that date only after a meaningful review. An unexplained assertion does not become trustworthy because it sounds confident.
Check ownership, duplication, and internal competition
Decide which URL should own each core intent. Several pages targeting the same question can divide internal links and leave each version incomplete. Consolidate genuine duplicates when one stronger destination can serve the reader. Keep separate pages when the intents, audiences, or required answers are materially different.
Update internal links so descriptive anchor text points to the intended owner. Make sure related pages support one another instead of repeating the same opening-level information. Do not delete a large group of URLs solely because traffic fell during the rollout; first determine whether each page has a distinct, supportable purpose.
Improve search and AI visibility without conflating them
A Google core update and visibility inside frontier language models are not the same measurement system. A decline in Google rankings does not prove that ChatGPT, Claude, or another answer engine stopped citing you for the same reason. Track conventional search performance and AI citations separately, even when the same content improvements may benefit both.
For answer-oriented visibility, make important facts easy to locate and interpret. Use descriptive headings, answer the stated question directly, name entities consistently, and keep qualifications beside the claim they modify. Tables should represent real comparisons, while lists should represent genuine steps or criteria. Formatting cannot compensate for an unsupported answer, but it can make a strong answer easier to extract correctly.
Apply JSON-LD only when it accurately describes visible content and the page’s real entity relationships. Schema is packaging, not evidence. Adding more markup will not repair stale facts, unclear authorship, duplicated intent, or an answer that misses the query.
Measure AI visibility with a stable set of prompts tied to your customers’ questions. Record whether your brand is mentioned, cited, represented accurately, or omitted. Keep that record beside, but not merged into, your Search Console analysis. This prevents a gain in one channel from concealing a loss in another.
Make controlled changes and preserve what you learn
Create a change log for every priority URL. Record the date, the affected query or intent, your diagnosis, and the substantive edits. That turns recovery work into a testable process. Without a log, several teams can modify the same page and leave you unable to connect later movement with a plausible cause.
Work in related batches rather than changing the entire site at once. Start with a small group that shares a documented weakness. Recheck query-level performance after those pages have accumulated enough impressions for a meaningful comparison. Keep the changes if the intended queries recover without harming conversions or accuracy; revise the hypothesis if they do not.
Do not judge success only by restored clicks. A revised page may attract fewer but better-matched visits. Review conversions, qualified leads, engaged visits, and the queries now associated with the page. The objective is durable visibility for the right need, not the recreation of every impression that existed before May 21.
Key takeaways
Use May 21 through June 2 as the rollout window, and keep those dates out of your before-and-after comparison periods.
Diagnose changes by page and query; total traffic alone cannot distinguish ranking, demand, click-through, and technical problems.
Prioritize valuable pages with a clear loss and a specific weakness instead of rewriting the whole site.
Improve intent match, distinct value, evidence, ownership, and internal linking before reaching for more schema.
Measure Google rankings and AI-answer visibility separately, with a written change log for both.
Your next move is simple: export the two 14-day comparison periods, select the five affected URLs with the greatest business value, and write one testable diagnosis for each. Make only the changes that diagnosis supports. That gives you a recovery plan you can measure instead of a collection of update myths.
