Tag: search engine optimization

Google has added a paragraph to its “Creating helpful, reliable, people-first content” page warning site owners against fabricated author identities. It sits in the section on who created the content. Google’s page now shows a last-updated date of October 5, 2026 (UTC), and trade reports place the first appearance of the paragraph around October 1 to 2. Google announced no ranking update alongside it.

This piece sets out what the page says, what is new and what is not, and what the evidence does and does not show about bylines. It is written for teams responsible for search engine optimization and content marketing, and it ends with a short audit you can run on your own author pages.

What Google’s page says now

Read from Google’s documentation, the section on who created the content does three things in sequence. It encourages adding accurate authorship information, such as bylines, where readers might expect it. It tells site owners to avoid deceptive authorship information. And it says that fabricating creator profiles, for example with AI-generated headshots, made-up names or false credentials meant to make content look as if human experts wrote it, is a form of deception.

The consequence is stated plainly. Deception, Google says, “makes a page untrustworthy to both users and our automated quality systems.” The page adds that it is a signal of a low-quality page.

Two things about that wording matter. The target is fabrication: invented people, fake faces and false credentials. And the stated purpose is to make content appear human-expert written, which ties the problem to misleading readers about who is behind the content.

What is new, and what is not

The paragraph itself is new. Search Engine Journal’s Matt G. Southern reported on October 2 that an archived copy of the page from June 8 lacked it. The same revision added a definition of main content and four attributes that Google says its raters assess: effort, originality, talent or skill, and accuracy, with a higher bar for accuracy on topics that affect health, finances, safety or well-being.

The principle is not new. Google’s Search Quality Rater Guidelines already treat deception as grounds for the lowest rating. Section 4.5.3 of the September 11, 2025 edition covers deceptive information about a website or its content creators, and says pages using deception should be rated Lowest. Search Engine Journal adds that those guidelines already named fake creator profiles. Relevant Audience makes the useful point that what changed is where the statement appears: in public documentation aimed at site owners, not only in guidance for raters.

The date, checked at Google’s page

This is where care is needed. The date on Google’s page is the date of the latest revision, not necessarily the date the paragraph was added. Search Engine Journal described a version dated October 1 on October 2, and the page now says October 5, so it has been revised since. SEO consultant Marie Haynes said the change was made on October 2. Search Engine Journal also reported that Google’s documentation updates page did not list the edit, and we did not find an entry for it either.

The safest wording is that the paragraph appeared in early October 2026 and that Google has not published a dated announcement for it.

What it does not say

The guidance leaves several things open, and some readings going around go further than the page does.

It announces no ranking update, no system name and no penalty. It does not explain how Google would detect a fabricated profile. Google’s page also notes that its raters do not control how pages rank, so the rater attributes describe what quality evaluation looks for, not a published ranking formula.

It does not say bylines help you rank. Google’s Search Liaison said in January 2024 that “Just adding a byline doesn’t give a ranking boost.” The new paragraph does not contradict that. It says deception is a risk, not that honest authorship is a lever.

And it is not a ban on AI. The sentence concerns fabricated people presented as human experts. Our reading is that a clearly labeled editorial team, or AI assistance disclosed where readers would wonder, is a different situation from an invented doctor with a generated photo. Google’s page does suggest disclosing automation where readers would reasonably ask how content was made.

Bylines and AI citation: what the evidence shows

It is tempting to treat real authors as a way to win citations in AI answers. The evidence does not support that yet, so we would not frame it that way.

The most direct data we found comes from Discovered Labs, a vendor that sells answer engine services, so read it with that in mind. It tested Perplexity only, using 400 questions and 5,770 pages from Google’s first results page. Pages published by companies were cited more often than pages by individual authors: 39.5% against 27.1%. The study calls the gap an association, not proof of cause. It also classifies a staff byline on a company blog as company content, so it does not test bylines directly. It cites a separate study of 497 Google results across 30 queries that found no measurable effect from bylines and credentials on citation.

That is thin evidence in both directions. What it supports is modest: treat authorship as a trust and risk matter, not as a citation tactic. Real people behind your content protect you from the downside Google has now named, and they help readers judge whether to trust you. They are not a proven way to get cited.

What counts as a fabricated profile

Google’s sentence names three examples. In practice, a team should check for these:

An author who does not exist. A name invented to give content a face, with no real person who wrote, reviewed or answers for it.

A photo that is not the person. An AI-generated headshot or stock image presented as the author.

Credentials that cannot be verified. Titles, years of experience, degrees or licenses that the person does not hold.

A fourth case sits close to the line, and it is our reading, not Google’s. A real expert’s name placed on content they did not write or review. Google’s separate instruction to avoid deceptive authorship information is broader than the fabricated-profile sentence, so this is worth treating as a risk.

A byline audit you can run this week

Start with a list of every author name that appears on your site, including old posts and contributors who have left.

Check that each name belongs to a real person who can confirm they wrote or reviewed the content. If a byline is a pen name, replace it with a transparent label such as your editorial team, and say so.

Check the photo. Use a real photograph of that person, or no photo.

Check the credentials. Every claim should be something the person can document: a license, a publication, a role at a named employer.

Check the author page. Google’s page asks whether bylines lead to further information about the author and the topics they write about. Each byline should link to a page with a real bio, links to their professional profiles and a list of their work. A bio at the end of an article with no link to a profile page leaves that question half answered.

Check sensitive topics. Where content covers health, legal or financial decisions, the accuracy bar is higher. Name the expert reviewer and the review date. Teams in healthcare and legal fields should be the strictest.

Check AI disclosure. Where AI assisted the draft, decide what readers should be told, and make sure a named person is accountable for the final text.

Fix, do not delete by reflex. If an author profile cannot be verified, correct the byline, label it accurately, or have a qualified person review and sign off on the content. Removing posts without a plan can cost you pages that were working.

Why this matters for AI search visibility

AI assistants and answer engines draw on pages that readers and search systems already treat as credible. Our guide to how AI search works explains how a page can be cited without ranking at the top, and why clear answers, specific claims and self-contained sections matter more than decoration. For generative engine optimization, the practical lesson from Google’s change is to build content on accurate, attributable information so that no part of it depends on a fake face. Our full guide to generative engine optimization covers that groundwork.

The same logic applies to answer engine optimization. Answers drawn from your pages carry your name, so the people and claims behind them need to hold up. Our look at why third-party mentions matter in AI search makes a related point: independent credibility is earned, and it is hard to fake.

To see where your brand and its experts are actually mentioned, a free AI Visibility Audit checks real questions across platforms. Our complete guide to the AI Visibility Audit explains the method.

Where this leaves you

The confirmed facts are these. Google’s people-first content page now warns that fabricating creator profiles, such as with AI-generated headshots, made-up names or false credentials, is a form of deception that makes a page untrustworthy to users and automated quality systems. The page shows a last-updated date of October 5, 2026, and trade reports place the paragraph’s first appearance at October 1 to 2. Google announced no ranking update, penalty or detection method, and the page does not say bylines improve rankings.

The practical response is an audit, not a rewrite. Make sure every byline is a real person, every photo is that person, every credential can be verified and every author has a page that proves it. Whether the aim is generative engine optimization, answer engine optimization or plain search engine optimization, treat that as a baseline for trust, not as a trick.

Frequently Asked Questions

1. What did Google add to its people-first content guidance?
A paragraph in the section on who created the content saying that fabricating creator profiles, such as with AI-generated headshots, made-up names or false credentials to appear expert, is a form of deception.

2. When did Google add it?
Google’s page shows a last-updated date of October 5, 2026, which is the latest revision. Trade reports place the first appearance of the paragraph around October 1 to 2. Google has not published a dated announcement for it.

3. Is this a ranking update?
Nothing announced says so. Google named no update, system, penalty or detection method. The wording describes what quality evaluation looks for.

4. Do author bylines improve rankings?
Google’s Search Liaison said in January 2024 that adding a byline does not give a ranking boost. Google’s page encourages accurate bylines for readers, but does not call them a ranking factor.

5. Does this ban AI-generated content or AI headshots?
No. The sentence concerns fabricated profiles presented to make content seem expert-written. Google’s page does suggest disclosing automation where readers would wonder how content was made.

6. Will real authors help me get cited in AI answers?
There is no solid evidence that they do. One vendor study of Perplexity found company pages cited more often than individual-author pages, and a second study it cites reported no measurable byline effect. Treat authorship as trust, not a citation tactic.

7. What should I do first?
List every author on your site, confirm each is a real person with a real photo and verifiable credentials, and make sure each byline links to a genuine author page.

If you want to know how your brand and its experts appear across Google and AI answer engines today, that is exactly what we look at in a free AI Visibility Audit.

Every marketer working on AI visibility has the same suspicion: if AI assistants lean on third-party sources, the shortest route to a mention is to create those sources. A policy update from Anthropic, the company behind Claude, puts a line through part of that idea. Announced on October 8, 2026 and effective November 12, it prohibits using Anthropic’s products to seed the sources AI systems draw answers from with content that misrepresents who is behind it.

The wording is narrower than some headlines suggest, and the policy binds users of Anthropic’s products, not the web at large. This piece sets out what the text says, what it does not say, and the practical test it offers brands deciding between earned mentions and planted ones. It is written for teams planning generative engine optimization and digital PR programs.

What the policy says

The change sits in a new section of Anthropic’s usage policy on deceptive campaigns and artificial activity. Read from the policy page, it prohibits using Anthropic’s products to create fake personas, accounts, media outlets or organizations, or to impersonate real ones. It prohibits hiding the sponsorship of content meant to influence opinion or decision-makers, and spreading content through networks of fake or ostensibly independent sites that share a common source. It also covers building tools for deceptive campaigns and marketing any of these activities.

The clause that matters here prohibits manipulating the sources from which search engines or AI systems draw answers, by “seeding them with content that misrepresents its origin, authorship, or independence.” The policy’s own example is a network of sites posing as unaffiliated sources that corroborate the same claims.

Notice what triggers the rule. It is not seeding, volume or the use of AI. It is misrepresentation: content that hides its origin, its author or its lack of independence.

Who it binds, and who it does not

The policy applies to anyone who submits inputs to Anthropic’s products. That covers individuals using Claude.ai or Claude Code, businesses using the API, customers who reach Claude through cloud providers or resellers, and end users of products built on Claude. A marketing tool built on Claude puts its own users under the same rules, as Relevant Audience points out.

It does not bind search engines, other AI companies or the open web, and it does not govern how Claude ranks or cites content. Mike King of the GEO consultancy iPullRank makes the same point in his analysis: the policy is about how people use Claude.

Enforcement works against the account, not the website. Anthropic’s Safeguards Team monitors for violations, and if one is suspected Anthropic may warn, throttle, limit, suspend or terminate access to its products. That differs from Google’s spam policies, which act on sites.

A new rule, or a clearer one?

Search Engine Journal reads the update as a clarification, not a brand-new ban. The 2025 policy did not mention search engines or AI answers, but Anthropic says it already prohibited fake-account networks and fake news sites, spread across other sections. The new text states the principle directly and applies it to the sources AI draws on.

Search Engine Journal also describes the case Anthropic linked to the section. According to that report, Anthropic found a network of around 70 sites posing as independent local news outlets, tied to a France-based advertising agency. The network used Claude to produce articles designed to “boost their site’s authority rankings on search engines.” It published at least 8,913 articles in about 20 languages, though most got little engagement. Anthropic removed the account and banned the organization.

Two cautions apply. The coverage does not say whether those sites improved their rankings or appeared in AI answers, so the case shows the tactic being attempted, not working. And Search Engine Journal does not link the full text of Anthropic’s report, so its details rest on that outlet’s summary.

Where the line sits

Relevant Audience reads the clause as aimed at deception about who is behind content, not at producing content for AI visibility. In its reading, the policy does not ban using Claude to write content, structure pages for AI answers or publish at volume. That is the publication’s interpretation of the text, which Anthropic has not spelled out for edge cases. For example, Anthropic has not said how it would treat several openly branded sites run by one company, and the policy text points to misrepresented independence as the trigger.

Read together, the sources suggest a useful test, which Relevant Audience frames as its own and not Anthropic’s: would the tactic still work if every reader knew who wrote the content and who paid for it? King puts a similar idea in terms of durability, arguing that manufactured independence has “an expiration date.”

Earned versus planted mentions

That test separates two things that can look alike from outside.

An earned mention exists because someone independent chose to write it. A journalist cites your original research. An expert quotes you. A customer reviews your product. A publisher runs a contributed article under a real byline. A sponsored placement is labeled as sponsored.

A planted mention only looks independent. A network of sites that recommend the same brand while hiding common ownership. Reviews from fake personas. Undisclosed paid listicles. Forum answers posted by accounts that conceal their affiliation. iPullRank, which sells GEO services and so has an interest in the framing, lists these among the tactics to avoid. The policy text itself names fake personas, hidden sponsorship and networks of ostensibly independent sites.

This is the distinction our earlier piece on why third-party mentions matter for AI search turns on. The reason independent sources carry weight in AI answers is that they are independent. Faking independence takes away the thing that made the mention valuable, and it now carries account-level risk for anyone doing it with Claude.

What to do before November 12

None of this requires a strategy rewrite. It asks for a short audit.

Check your own content network. If you or an agency have used Claude to produce content for several sites that appear independent but share an owner or a sponsor, review it now. Search Engine Journal suggests this audit.

Ask vendors direct questions. Relevant Audience recommends asking agencies and tools how they build AI visibility and whether any sites in their plans are owned by them without saying so. A vague answer is information.

Label sponsorship. Where a placement is paid, say so on the page. Where a comparison page is brand-owned, make that obvious.

Use real bylines and real experts. Contributed content should carry the name of the person who wrote it and a verifiable role.

Fund the earned route. Original data, expert commentary and useful tools give journalists and publishers a reason to cite you. That is the work behind digital PR and ethical link building, and the slower route is the durable one.

Measure what you earn. Track whether your brand is mentioned and cited across AI platforms, and which sources drive the mentions. A free AI Visibility Audit does this across platforms and shows where earned coverage is missing.

What this does not tell you

The policy is not evidence that seeding works, or that it fails. The reporting does not show whether the network Anthropic banned gained rankings or appeared in AI answers.

It does not describe how detection works beyond general monitoring, and it does not cover other AI companies. ChatGPT, Gemini and Perplexity have their own terms, and Google has its own spam policies. Do not read this one document as a rule for all of GEO.

It also does not tell you that AI-written content is off limits. The text turns on misrepresentation, though edge cases remain untested. If you use AI tools to draft, the safe course is the same as it has always been: a real author, accurate claims and no pretense about who is speaking.

Why this matters for AI search visibility

AI assistants increasingly shape which brands get recommended, so the temptation to manufacture sources will not disappear. What this update does is move one major provider’s rules in the opposite direction, and mark provenance as the thing platforms are watching. For answer engine optimization, the safest assets are the ones that can survive scrutiny: clear answers, original information, real authors and accurate facts. Our full guide to optimizing for AI search covers that groundwork, and sound search engine optimization supports all of it.

Where this leaves you

The confirmed facts are these. Anthropic announced an updated usage policy on October 8, 2026, effective November 12. A new section prohibits using its products to seed the sources search engines and AI systems draw answers from with content that misrepresents its origin, authorship or independence. Enforcement is against accounts. The policy binds users of Anthropic’s products, not other companies or the open web.

The practical response is to build mentions that would still work if everyone knew who was behind them. That favors original research, real experts, labeled sponsorship and honest digital PR and link building, backed by measurement of what AI platforms actually say about you. Whether the aim is generative engine optimization, answer engine optimization or plain search engine optimization, the same provenance rules apply.

Frequently Asked Questions

1. What did Anthropic’s updated usage policy change?
It added a section on deceptive campaigns and artificial activity, which prohibits using Anthropic’s products to seed the sources search engines and AI systems draw answers from with content that misrepresents its origin, authorship or independence. It takes effect November 12, 2026.

2. Does it ban GEO?
No. The trigger is misrepresentation, not optimization. Writing clear content, structuring pages for AI answers and earning mentions are not what the clause describes, though Anthropic has not addressed every edge case.

3. Who does the policy apply to?
Anyone who submits inputs to Anthropic’s products, including individuals, API developers, customers using Claude through cloud providers and end users of products built on Claude. It does not bind search engines or other AI companies.

4. What happens if someone violates it?
Anthropic may warn, throttle, limit, suspend or terminate access to its products. In the case Search Engine Journal describes, Anthropic removed the account and banned the organization.

5. Is it a new rule?
Search Engine Journal reads it as a clarification. Anthropic says fake-account networks and fake news sites were already prohibited under other sections, and the update names the search and AI answer context directly.

6. How do I tell an earned mention from a planted one?
Ask whether the tactic would still work if readers knew who wrote and paid for the content. Independent coverage, real reviews, labeled sponsorships and bylined expert content pass. Fake personas, hidden-owner site networks and undisclosed paid listicles do not.

7. What should I do before November 12?
Audit any Claude-made content running across sites that appear independent, ask agencies and tools how they build AI visibility, label sponsored content and use real bylines. Then measure your actual mentions across AI platforms.

If you want to know where your brand is mentioned and cited across Google and AI answer engines today, and which sources are driving it, that is exactly what we look at in a free AI Visibility Audit

Picture a Monday morning report. Your rank tracker says a key page has fallen out of the top 10, and the pages that replaced it look unrelated. The usual reaction is to start rewriting. A new question belongs first: did the ranking change, or did the tool receive the wrong results page?

On October 10, 2026, the rank-tracking company Nozzle published research claiming that since September, Google has been returning complete, normal-looking results pages to its rank trackers with the real results swapped out. Nozzle sells rank tracking, and Google has not commented. This piece sets out what was reported, what is and is not established, and how to check before you react. It is written for teams responsible for search engine optimization reporting.

What Nozzle reported

Nozzle’s page analyzes 27.5 million search results pages from its customer datasets, collected between August 20 and October 9, 2026, across 49 countries, desktop and mobile.

From August 20 to September 9, about 0.17% of pages were poisoned, which is Nozzle’s baseline. On September 13, requests to Google began failing in large numbers. The first poisoned pages appeared on September 20. They peaked at roughly a quarter of all pages between September 27 and 29, at 24.9%, 26.7% and 27.0%. Since October 1, daily rates have run at about 4% to 11%. Across the period since September 13, Nozzle puts it at 8.0%.

The word poisoned matters. Google does not refuse these requests, according to Nozzle. It answers with a full page of wrong results. Nozzle puts it this way: “A poisoned request succeeds.” There is no error, no captcha and no change in the page template, so the only way to spot it is to compare a keyword’s results over time.

How it was measured, and a caution about the 8.0%

A keyword’s usual sites are those in the top 10 on at least 60% of its baseline pages. A page counts as poisoned when fewer than half of them appear on any page of the results, and they return later. Those thresholds are the study’s own choices.

Several limits apply. Detection is inferred from each keyword’s history, not from a signal Google has confirmed. The sample comes from Nozzle’s own customers, and the last few days are still filling in. And the headline 8.0% does not state its denominator: the daily table is labeled “All SERPs,” while the country and industry tables calculate against judged pages. Cite it as “Nozzle reports about 8%,” not as a measured rate of Google behavior.

What a poisoned page looks like

Nozzle reports these patterns on poisoned pages, compared with its baseline.

Organic results kept only 20.7% of the previous page’s sites, against 88.5% at baseline. A tracked project’s own site fell out of the top 10 on 58.6% of poisoned pages, against 2.7% at baseline. Reddit rose from 20.8% to 28.8% of top-10 appearances, and Facebook from 28.3% to 33.8%. An AI Overview appeared on 34.9% of poisoned pages, against 54.2%. Ads and shopping results were largely stable.

One example shows how complete the swap can be. For the desktop, US search “white label local seo,” all nine page-one sites on October 4 were the usual vendors. On October 7, all nine had been replaced by unrelated results, including a WordPress tool, a steakhouse and government sites.

The effect is usually brief. About 80% of poisoned spells lasted a single page, and 77.9% of poisoned pages had their usual sites back within three days. A real ranking change persists, which is how the two can be told apart.

Where it appears to hit hardest

Nozzle’s tables show wide variation. Since September 13, the poisoned share was 8.5% in the United States, 10.5% in Canada and 11.5% in Australia, with the United Kingdom lowest at 3.0%. Treat country figures as indications, since they depend on Nozzle’s sample sizes.

“Near me” searches were poisoned more often (11.4%) than other queries (7.8%), and navigational brand searches least often (5.3%). If you manage local SEO reporting, that is worth knowing.

By industry in the US, legal was highest at 15.9%, peaking at 51.3% on September 27. Pets was lowest at 4.3%. Firms in the legal sector should be the most careful about reacting to a single day.

The tools matter too. On the same days, one collection route returned 1% to 7% poisoned pages while another returned 9% to 30%, so how your vendor collects data affects what it sees.

A second vendor, and a reporter’s concern

Nozzle is not alone. DemandSphere, another rank-tracking company, posted on October 7 that Google returns spurious results when it suspects bot traffic, affecting about 11% of its daily results pages. PPC Land reported the figure on October 13. DemandSphere’s post does not describe a method or sample size. Both figures are vendor-reported and unaudited, and they agree on the mechanism and rough scale, little more.

Barry Schwartz of Search Engine Roundtable reported on October 12 that third-party rank tracking is returning incomplete or inaccurate data. He relayed the three tactics that Nozzle’s Derek Perkins described: wide IP blocking aimed at large residential proxy networks, a big increase in captchas, and injecting bad data into suspect pages. Schwartz singled out the third: “The third approach, injecting bad data, concerns me the most.” His reasoning is that tools may not notice it, so they can appear to work while their data is wrong. Several vendors, including Sistrix, SE Ranking and DataForSEO, reportedly posted notices about data problems.

What is not established

Google has not publicly commented on Nozzle’s or DemandSphere’s figures or on the September changes. Everything about motive comes from vendors and the trade press.

Nozzle reads the pattern as Google’s response to bulk collection of its results for AI grounding, which rank tracking resembles. DemandSphere’s founder makes a similar argument. Schwartz’s view, as reported, is that Google is aiming at AI bots and scraping services, not SEO tools. Roger Montti of Search Engine Journal adds that altered pages could also confuse spammers reverse-engineering rankings, a point Nozzle did not raise. None of these readings is confirmed.

There is also a confound. Google’s September 2026 spam update ran from September 24 to October 8, according to PPC Land and Looploop, so real ranking volatility and altered data overlapped in the same weeks. Our earlier piece on the September spam update covers the real-volatility side. A single dashboard showing a drop in that window could not tell the two apart.

Even first-party data can lag. Looploop reports that the Search Console Performance report ran more than 64 hours behind on October 11, so check the date range first.

How to tell a real drop from a poisoned page

Start with Search Console. If it still shows impressions and clicks for the same queries and dates, the site very likely did not drop. Confirm that its data is current first.

Compare against history. Look at the keyword’s usual top 10 over several weeks, not just yesterday, because yesterday may also have been poisoned.

Wait one to three days. Most altered pages clear quickly, while a real change persists.

Read the shape of the page. Nozzle says fewer AI Overviews, fewer “People also search for” modules, more image packs and social or forum sites, and shorter pagination are suggestive, but none is reliable alone.

Cross-check tools. A drop that only one tool reports is a question, not a conclusion.

Ask your vendor how it detects swapped pages and what its error rates are. Relevant Audience, citing PPC Land, reports that most do not yet publish comparable figures.

Hold off on changes. Do not rewrite pages from one chart. Our guide to reading your own traffic before you change anything sets out a three-step method that works here too.

What to change in your reporting

Make first-party data the reference. Search Console, analytics and conversions should anchor the monthly report, with the rank tracker used for trends. Our look at Google’s AI visibility reports in Search Console explains what that data does and does not include.

Set a rule for alerts. A drop seen on one day, in one tool, should trigger a check, not a client email. Require it to persist, or to appear in Search Console, before it is reported as a ranking loss.

Annotate your dashboards. Mark September 13 to October 9 as a period of suspected data problems, so later readers do not mistake a poisoned dip for a penalty.

Why this matters for AI search visibility

Nozzle’s data shows AI Overviews appearing less often on poisoned pages (34.9% against 54.2%). Any measurement that infers AI visibility from collected Google pages may pick up the same noise. That is our inference, not Nozzle’s finding, and tools that measure AI answers by other methods may behave differently.

The practical response is to avoid relying on one source. Generative engine optimization and answer engine optimization are about being cited and recommended in AI answers, and measuring that well means testing real buyer questions across several platforms, not reading a single scraped page. Keep the basics of generative engine optimization and answer engine optimization strong: clear answers, accurate information and consistent entities. Our complete guide to the AI Visibility Audit explains how that cross-platform measurement works. Strong search engine optimization remains the base for all of it.

Where this leaves you

The confirmed facts are these. Nozzle published research on October 10, 2026, covering 27.5 million results pages, and reports that since September 13 about 8.0% were poisoned, against 0.17% at baseline, with a peak near 27% in late September. DemandSphere reports about 11% on its own data. Google has not commented, the mechanism is Nozzle’s account, the motive is interpretation, and both figures come from vendors who sell rank tracking.

The lasting lesson is about method. A rank tracker is a sample of what Google returned to a tool, not a record of what your customers saw. Before reacting to a drop, check Search Console, compare with history, wait a few days and look at more than one source.

Frequently Asked Questions

1. What did Nozzle report about Google and rank trackers?
On October 10, 2026, Nozzle reported that since September, Google has returned complete, normal-looking results pages to rank trackers with the real results swapped out. It measured 8.0% of 27.5 million pages as poisoned since September 13, against 0.17% at baseline.

2. Has Google confirmed this?
No. Google has not publicly commented on Nozzle’s or DemandSphere’s figures or on the September changes. The explanations come from vendors and trade press.

3. Can I trust the 8.0% figure?
Treat it as Nozzle’s reported estimate. It is from a rank-tracking vendor and inferred from keyword history.

4. How do I know whether my ranking drop is real?
Check Search Console for the same queries and dates, compare with several weeks of history, and wait one to three days. Altered pages usually clear within days, while a real ranking change persists.

5. Does this affect Search Console data?
Nozzle’s study concerns data collected from Google results pages, not Search Console. Search Console can lag, though, so confirm the date range first.

6. Does this change how I should track AI visibility?
Tools that infer AI visibility from collected Google pages may pick up the same noise, which is our inference. Testing real buyer questions across several AI platforms does not depend on one scraped page.

7. Should I stop using my rank tracker?
No. Use it for trends, and confirm important changes in Search Console and analytics. Ask your vendor how it detects swapped pages and what its error rates are.

If you want to know how your brand appears across Google and AI answer engines, measured from real answers and not a single dashboard, that is exactly what we look at in a free AI Visibility Audit.

For most of the last two decades, a search choice screen was a way of picking between conventional search engines. A proposal from the UK’s Competition and Markets Authority (CMA) would change that. It would put AI assistants such as ChatGPT and Perplexity on the screens Google shows UK users, and it would attach a condition: any provider listed must fairly attribute the publisher content it uses.

This is a proposal, not a rule, and it applies to the UK only. But it shows a regulator treating AI assistants as search alternatives, and source attribution as a formal requirement. This piece sets out what the CMA proposed, how it would work, what is undecided and what teams responsible for AI visibility should watch.

What the CMA proposed

On September 23, 2026, the CMA published strengthened proposals to give UK users of Google’s Android and Chrome products greater choice and more control over their search services. The CMA says it listened to publishers, search providers and consumer groups, and that the update responds to services such as ChatGPT and Perplexity.

The core elements are these. Google would show Android and Chrome users a choice of search services when they first use an Android phone or open Chrome. Users would be prompted again every year to choose their default. AI assistants could be included on the choice screens if they meet the relevant criteria, including technical and security requirements. And search providers on the screens would have to fairly attribute publisher content when it is used, so that people can easily reach the original sources.

Sarah Cardell, the CMA’s Chief Executive, said the CMA is “responding quickly to the rise of AI assistants”, which people increasingly use as search services but which do not appear on Google’s choice screens today.

The consultation closed at 5pm on October 9, 2026. The CMA expects to make its final decision on this requirement by the end of 2026.

Where this sits in the CMA’s wider approach

Google was designated as having strategic market status in general search and search advertising in October 2025, which lets the CMA set conduct requirements for it. According to the CMA, it imposed publisher controls on June 3, 2026, and fair ranking and data portability requirements on June 17. The user choice requirement is the one still being decided, an updated version of a January 2026 proposal.

How a choice screen would work

The press release gives the outline. The CMA’s consultation document, which runs to 71 pages according to PPC Land, holds the detail. We could not open that PDF, so the following comes from two independent analyses of it, by the trade publication PPC Land and by the law firm Bratby Law, which agree on the main points.

According to those analyses, the screen would list up to 12 providers. If more than 12 qualify, Google would be expected to show the five most popular plus seven chosen at random. Providers would appear in random order, and users would have to scroll the whole list before confirming. Users could trial a provider for at least a week. The screen would be unskippable on new Android devices and fresh Chrome installs, and a skippable reminder would bring it back at least once a year.

These details come from analysis of a proposal that may change, so treat them as the current draft.

How an AI assistant could qualify

The CMA says AI assistants “could in theory be able to be listed”, a phrase quoted by Bratby Law from the consultation document. Nothing guarantees a place. Per those analyses, a service would have to meet three criteria.

First, it must adequately address the full range of use cases of a general search service. The CMA’s notes describe four types of query: navigational, transactional, simple informational and more complex informational.

Second, it must provide a functioning general search experience. That covers technical operation, compatibility with Android, minimum security requirements and credible plans to operate sustainably.

Third, a significant proportion of its UK users must consider it a general search service. The notes say this means a meaningful proportion, not a majority.

A service does not need its own web index. A syndicated index is acceptable.

Who decides matters too. Under the proposal, Google, not the CMA, would run the eligibility process every six months, deciding within two months and sending written reasons for any rejection to the applicant and the CMA. Bratby Law notes that the draft contains no appeal route to the CMA against those decisions, and that the written reasons are the main check. That is one lawyer’s reading of a draft.

The condition for publishers

The attribution condition is the part most relevant to anyone who creates content. Per the CMA, search providers on the choice screens would have to fairly attribute publisher content when it is used, so people can easily access the source. In the analyses of the consultation document, any generative AI summary would have to attribute web content clearly and accurately, with a clear route to the source, and each provider could choose how to do it.

Three points deserve care.

The condition is a requirement of being listed on the screen, not a general rule for all AI products. Because the CMA can impose requirements only on Google, it works as a condition of access to Google’s distribution. Bratby Law argues that it therefore becomes a de facto standard for any rival that wants a place, though that is the author’s view.

The condition does not, in anything we reviewed, require payment to publishers or guarantee any amount of traffic. It concerns attribution and a way to reach the source.

How it would be enforced, and how fairness or accuracy would be judged, are not set out in the press release. Watch the final text.

What is not decided

A lot remains open. The requirement has not been imposed, and the criteria, slots, attribution wording and timing could all change after consultation responses. Google has not commented, according to press reports.

Timing is also uncertain. The final decision is expected by the end of 2026. According to PPC Land’s reading, some obligations would start about a month after the requirement is imposed, and the rest within six months, so screens showing AI assistants may not reach UK users until some time after that. Do not plan around a date.

Geography matters too. This is UK law, covering UK users of Android and Chrome. It changes nothing for users in the United States, so for mainly American clients it is a signal to watch, not a task for this quarter.

Why teams working on AI visibility should watch it

There are three reasons.

AI assistants are being treated as search. The CMA describes them as increasingly used as search services and wants them offered as alternatives. For anyone working on generative engine optimization, that confirms what many teams assume: visibility in AI answers is becoming part of search visibility, in the eyes of regulators as well as users.

Attribution is becoming a formal concept. If a regulator makes fair attribution a condition for AI assistants to reach users, it normalizes the idea that answers should point back to sources. That could affect how assistants display citations over time, but it is a possibility, and we found no evidence yet of any change.

Distribution could shift. If more UK users chose an assistant, more searches might begin there, which would raise the importance of answer engine optimization, being cited and recommended in AI answers. That is a scenario. The proposal does not say how many people would pick an assistant.

None of this reduces the value of traditional search engine optimization. The sensible view is that search is widening, not being replaced.

What to do now

You do not need to change strategy because of a consultation. A few low-cost steps keep you ready.

Measure AI referrals now. Check your analytics for traffic from ChatGPT, Perplexity, Gemini and other assistants, and note how it changes. A baseline lets you see any shift later, whatever the cause.

Make attribution easy. Use clear titles, visible authorship and dates, stable canonical URLs and descriptive headings, so any assistant that wants to credit you can do so accurately.

Check how you are cited. Run real customer questions in several assistants and record whether your brand and pages appear and are attributed correctly. A free AI Visibility Audit does this across platforms.

Keep your source pages strong. Pages that answer a specific question clearly and carry original information are the likeliest to be cited, which is the same work that supports search engine optimization and generative engine optimization.

For UK clients, set a review date. Look again when the CMA publishes its decision, and read the final attribution wording before advising anyone.

Where this leaves you

The confirmed facts are these. On September 23, 2026, the CMA proposed that Google show Android and Chrome users in the UK a choice of search services at first use and prompt them annually. AI assistants could be listed if they meet the criteria, and providers listed would have to fairly attribute publisher content. The consultation closed on October 9, and a final decision is expected by the end of 2026. It is a proposal for the UK only.

The lasting lesson is about direction. Regulators are beginning to treat AI assistants as search services, and attribution as something that can be required, which matters for answer engine optimization planning. For teams reviewing how a brand appears in AI answers, that is a reason to measure now and watch the final wording.

Frequently Asked Questions

1. What did the CMA propose on September 23, 2026?
It proposed that Google show UK users of Android and Chrome a choice of search services at first use and prompt them again every year. AI assistants could be listed if they meet the criteria, and listed providers would have to fairly attribute publisher content.

2. Is this a final rule?
No. It is a proposed conduct requirement. The consultation closed on October 9, 2026, and the CMA expects to make its final decision by the end of 2026.

3. Will ChatGPT and Perplexity definitely appear on the screens?
No. The CMA says assistants could be listed if they meet the criteria, and analyses of the proposal describe three: covering the full range of search queries, providing a functioning search experience and being considered a general search service by a significant proportion of UK users.

4. Who decides which services are listed?
Under the proposal, Google decides, through an eligibility process every six months, with written reasons for rejections sent to the applicant and the CMA. Bratby Law notes that the draft contains no appeal route to the CMA.

5. What does the attribution condition require?
Providers on the screen would have to fairly attribute publisher content when it is used, so users can reach the original source. Analyses of the consultation document say generative AI summaries must attribute web content clearly and accurately. We found no requirement for payment or traffic.

6. Does this affect businesses outside the UK?
Not directly. It applies to UK users of Android and Chrome, but it signals how regulators are treating AI assistants and attribution.

7. What should I do about it now?
Measure traffic from AI assistants, make your pages easy to attribute and check how assistants cite you. Review again when the CMA publishes its final decision, rather than changing strategy on a proposal.

If you want to know how your brand appears across Google and AI answer engines today, that is exactly what we look at in a free AI Visibility Audit.

On September 24, 2026, Google began rolling out its September 2026 spam update. Spam updates usually finish in a couple of days, so most site owners are used to a short burst of volatility followed by a clear before and after. This one is different. Google says the rollout may take up to two weeks, which means that for a full fortnight, every ranking change you see is a reading from a moving target.

That changes how you should respond. This piece covers what Google has confirmed, what it has not said, what early volatility data does and does not show, and a practical plan for the days between now and the end of the rollout. It is written for anyone responsible for search engine optimization at their company, whether you run a small site or manage a large content library.

What is confirmed

The core facts come from Google’s Search Status Dashboard and are consistent across Search Engine Land, Search Engine Journal and Search Engine Roundtable.

The update began on September 24, 2026, at 9:15 a.m. Pacific time. It applies globally and to all languages. Google’s dashboard says the rollout may take “up to two weeks to complete”, which puts the latest possible finish around October 8. It is the fourth spam update of 2026, following releases in March, June and August.

The rollout window is what stands out. The dashboard lists the earlier 2026 spam updates at 19 hours and 30 minutes for March, 2 days and 1 hour for June, and 2 days and 16 hours for August. Two weeks is several times longer than any of them. One point of precision matters here: two weeks is the announced maximum, not a measured duration. The update could finish sooner, and until Google marks it complete, nobody outside Google knows how long it will really take.

What Google has not said

Google has not said what this update targets. According to PPC Land, Search Central described it only as a normal spam update, with no new policy, no named category and no figures on how many queries are affected. That gap matters, because much of the commentary this week has filled it with confident claims about which sites are being hit and why. Treat those claims as hypotheses. The only firm statement from Google is that sites which see a change should review its spam policies. Anything more specific is inference from other people’s data.

What early data shows, and what it does not

Search Engine Roundtable reported that a long list of volatility trackers showed significant movement across the first weekend, September 25 to 27. The tools it named include Semrush Sensor, AccuRanker, Mozcast, Sistrix, Algoroo and several others. When that many independent trackers move at once, it is a reasonable signal that something real is happening in the results.

Glenn Gabe, a well-known analyst of Google updates, reported big drops across a number of sites in multiple verticals and countries. He described AI-generated content sites and programmatic content farms as among those losing rankings. That is one experienced observer’s read of the sites he tracks, and it fits how Google’s spam policies treat scaled content, but it is not confirmed by Google and it is not a full picture of who is affected.

There are three reasons to be careful with early data.

First, volatility is not damaging. Trackers measure how much results moved, not who won or lost. A large reading can come from a few sites moving a long way.

Second, the update is not finished, so the pattern on day five may look different by day ten.

Third, you are reading a mix of signals. Seasonal demand, your own recent changes, other Google systems and ordinary news cycles all move traffic at the same time. Attributing a dip to the spam update before it ends is a guess.

What to do while it rolls out

The most useful thing to do during a long rollout is resist the urge to react. Here is a working plan.

Record a baseline. Before anything else, capture your current position. Export Search Console performance data for the last 90 days by page and by query, along with clicks, impressions, average position and the countries you care about. Note recent changes such as redesigns, migrations, new content batches and link campaigns.

Annotate the timeline. Mark September 24 in your analytics and reporting tools, and add a note when Google marks the rollout complete.

Compare like with like. Weekday traffic and weekend traffic behave differently for many sites. Compare the days since September 24 with the same weekdays in earlier weeks.

Segment before you conclude. A sitewide traffic drop is rarely uniform. Split the data by page type, by folder, by template and by query group. If the loss is concentrated in one section, such as a batch of AI-assisted pages or a subdirectory of third-party content, that tells you far more than a total.

Do not make sweeping changes. Deleting hundreds of pages, rewriting templates or disavowing links mid-rollout makes it impossible to tell what caused what. If you suspect a policy problem, plan the fix and stage it.

Fix what is clearly broken. If you find hacked content, injected links, broken redirects or a security issue, fix it immediately.

Hold your publishing rhythm. Search Engine Land’s coverage advises sites that are not affected to keep doing what they were doing.

Audit against Google’s spam policies now

Whether or not you see a drop, this is a good week to check yourself against the policies Google points to. Google’s documentation names categories including cloaking, doorway abuse, expired domain abuse, hacked content, hidden text and links, keyword stuffing, link spam, scaled content abuse, scraping, site reputation abuse, sneaky redirects, thin affiliation and user-generated spam.

Three of these tend to matter most for modern content teams.

Scaled content abuse is about producing large volumes of low-value pages in order to manipulate rankings, whether the pages are written by people, generated by AI tools or scrapped. The test is value per page, not the tool used. A large batch of near-duplicate location pages or templated question pages with thin answers is the pattern to look for.

Site reputation abuse covers publishing third-party content on an established site mainly to borrow its ranking strength. Sponsored sections or partner content hubs on an established site are examples.

Link spam covers buying, exchanging or generating links mainly to manipulate rankings. If you have inherited a backlink profile from a past agency, this is the moment to review it critically, not defensively.

If you find something that fits, note what it is, how many pages it affects and what you would do about it. You need not act during the rollout, but be ready to.

What recovery looks like

If you are affected, it helps to set expectations early. Google’s spam update documentation says that fixing problems may help a site improve if its automated systems learn “over a period of months” that the site complies with its policies. It also warns that for link spam, changes may not bring an improvement, because ranking benefits from those links cannot be regained.

So recovery is not a matter of days, and it is not guaranteed. The right frame is a remediation plan measured in months, not a quick reaction to a bad week.

Spam updates also occasionally catch sites that were not breaking the rules. Search Engine Land notes that this should not typically happen but sometimes does. If you believe you were caught unfairly, audit yourself carefully, document your evidence and keep monitoring.

Why this matters beyond classic rankings

Most teams now think about visibility in more places than the ten blue links. Generative engine optimization and answer engine optimization are about being cited and recommended in AI answers, which draw on the wider web and on search results. No one has published data showing how this specific spam update affects citations in AI Overviews, ChatGPT or Perplexity, and it would be a mistake to claim otherwise.

What can be said is narrower and more practical. Pages that lose organic visibility in Google lose a route to being seen and cited, and the qualities that spam policies punish, such as thin, repetitive, mass-produced content, are also poor candidates for being quoted in an AI answer. Strong search engine optimization, generative engine optimization and answer engine optimization all tend to rest on the same base: original, useful pages that answer a real question well. If you are building visibility for AI search, the spam policies are a sensible floor.

If you track AI citations, set that baseline now too, and compare again after Google says the update is complete.

Where this leaves you

The confirmed facts are these. Google started the September 2026 spam update on September 24, it is global, and it may take up to two weeks. It is the fourth spam update this year and the longest announced window. Google has not said what it targets. Early volatility is real, and some analysts report losses among AI-generated and programmatic sites, but that is observation, not confirmation.

The practical response for any search engine optimization team is patience with discipline. Take a baseline, mark the dates, segment your data, audit your own site against the spam policies, fix genuine defects and hold back on big changes until the rollout ends. A two-week update rewards teams that measure carefully, not teams that react fastest.

Frequently Asked Questions

1. When did Google’s September 2026 spam update start, and when will it finish?
Answer: It began on September 24, 2026, at 9:15 a.m. Pacific time. Google says the rollout may take up to two weeks, so the latest expected finish is around October 8. It could end sooner.

2. Why is this spam update considered the longest of 2026?
Answer: Because the announced window of up to two weeks is far longer than the earlier 2026 spam updates, which the dashboard lists at 19 hours and 30 minutes, 2 days and 1 hour, and 2 days and 16 hours. Two weeks is a maximum, not a confirmed actual duration.

3. What does the September 2026 spam update target?
Answer: Google has not said. It applies worldwide to all languages. Some analysts report ranking losses among AI-generated content sites and programmatic content farms, but that is their observation, not a statement from Google.

4. Should I change my site while the update is rolling out?
Answer: Not in a sweeping way. Record a baseline, annotate the dates, and segment your data. Fix clear defects such as hacked content or broken redirects immediately, but avoid large deletions, rewrites or disavows until the rollout is complete.

5. How long does it take to recover from a spam update?
Answer: Google says recovery can take months, because its automated systems must learn over time that a site follows its spam policies. For link spam, ranking benefits from those links may not return at all, even after cleanup.

6. Does the spam update affect visibility in AI answers?
Answer: No data has been published on that yet. Pages that lose Google visibility lose one route to being cited, and low-value mass-produced content is a poor candidate for citation anyway. Measure AI citations before and after the rollout and compare, and do not draw conclusions from one week.

7. How can I check whether my site is at risk?
Answer: Audit against Google’s spam policies, especially scaled content abuse, site reputation abuse and link spam. Then compare your Search Console data by page type and query group against a 90-day baseline.

If you want to know where your brand appears, and where it is missing, across Google and AI answer engines, that is exactly what we look at in a free AI Visibility Audit.