This has a name now. Kevin Indig called it the ghost citation, and a study he ran with Semrush put a number on how common it is. Across 3,981 domain appearances from 115 prompts, run in 14 countries across ChatGPT, Gemini, Google AI Overviews and Google AI Mode, 61.7% of appearances were citations with no brand mention in the answer. Only 13.2% got both. Put differently: 74.9% of appearances included a citation, but only 38.3% included the brand name.

Your content can be doing all the work while your brand stays completely invisible to the person reading.

The engines are not doing the same job

The split between engines is severe enough that a single visibility score is close to meaningless.

• Gemini names the brand in 83.7% of appearances but generates a citation link only 21.4% of the time. It answers from what it already knows about you.
• ChatGPT does the reverse: cites 87% of the time, names the brand in 20.7%. It reads like a paper with footnotes.
• Google AI Overviews sit between the two and lean towards citing.

In the study’s data there was almost no overlap between the brands ChatGPT cited and the brands Gemini named for the same prompt. On 100 of 454 prompt and domain combinations, the engines disagreed on whether to name the brand at all. So if you are tracking one engine and reporting it as “AI visibility”, you are reporting one behaviour of one system.

The content type doing the damage is the one you produce most

This is the finding that should change what a small marketing team publishes next month.

Informational content, the “what is”, “how does”, “explained” format that most business blogs are built from, earned an 89.3% citation rate and an 18% mention rate. Comparative content, the “best”, “versus”, “recommended” format, produced a 43.3% mention rate, roughly 2.4 times more brand mentions. How-to content sat at 42.8%. Commercial queries reached 35.6% mentions against an 84.4% citation rate.

The logic is uncomfortable but obvious once you see it. Informational content is raw material. The model reads it, absorbs the fact, writes the fact in its own words, and links the source out of politeness. Comparative content forces the model to name things, because a comparison without names is not a comparison.

So the agency that spent eighteen months building a definitive glossary of industry terms has produced the single most citable and least brand-visible asset available. Meanwhile the competitor with six honest “X versus Y” pages, including the cases where they lose, gets named.

Why the model will not repeat your claim

There is a second layer under the format question, and Forbes framed it well this week: every brand claim an AI repeats without independent backing is a claim the AI is vouching for itself. Systems tuned against Google’s quality rater guidelines weight first-hand experience heavily, and a product page describing your own jacket as the warmest available has an obvious incentive problem. A forum thread describing a Colorado winter in that jacket does not.

This is where most GEO advice goes vague, so here is the concrete version. If your only evidence for a claim lives on your own domain, expect the model to use the surrounding information and skip the claim. Corroboration that actually shifts this looks like: a named customer willing to be quoted with specifics, a third-party review platform with enough volume to be more than a testimonial page, a trade publication write-up you did not pay for, forum and community threads where customers describe outcomes in their own words, and comparison content that names competitors honestly enough to be credible.

None of that is fast. That is the point. There is no schema markup fix for a claim nobody else has ever repeated.

What to actually do

A sequence that fits inside a normal fortnight:

1. Pull the ten prompts that matter most to your business. Run each one in ChatGPT and Gemini separately, and record two columns: cited, and named.
2. Find the pages that are cited but never named. These are your ghost pages, and they are usually your best informational content.
3. For the top three, add a comparison or evaluation section that names real alternatives, including where you are not the right choice.
4. Pick one claim you make constantly and find or build one piece of third-party evidence for it that is not a testimonial on your own site.
5. Re-run the ten prompts in six weeks. Compare the named column, not the cited column.

Query phrasing matters too, and it cuts against most keyword habits. Short conversational prompts produced brand mention rates near 100% in the study, while long structured prompts on the same topic produced 2% to 3%. Test the short version of your question, because that is how people actually ask.

What can go wrong here

The obvious risk is over-correcting. If you decide informational content is worthless and stop making it, you lose the citations that build the model’s familiarity with your domain in the first place. Citations and mentions come from different places: citations reflect domain authority and original work, mentions reflect brand familiarity and positioning. You need both, and killing one to chase the other is how sites lose ground in both.

The second risk is measuring this too often. Answers vary run to run. A single check on a single day tells you almost nothing, which is exactly the trap the sample-of-one approach falls into. Six-week intervals, ten fixed prompts, two engines minimum.

And this may not be worth your time at all. If you sell into a market where buyers do not use assistants for discovery, if your pipeline is referral and relationship driven, or if you are a publisher whose business model runs on the citation link rather than the name, then citation rate is the correct metric and the ghost citation is not your problem. Check who your buyers actually are before rebuilding a content plan around this.

The one thing worth taking away: stop treating a citation as proof of visibility. It is proof your content was useful to a machine. Whether it was useful to your business is a separate question, and it has a separate column in the spreadsheet.

The full dataset is in the ghost citations study, and the trust argument is set out in this piece on AI search and branded content. If you want the other half of the picture, what these systems can and cannot read on your site, we covered that in how AI builds a B2B shortlist before anyone calls you.

Editor’s note: This area changes quickly, so check the latest platform policy before making compliance decisions.

The post AI Search Is Citing Your Blog and Not Saying Your Name. Here Is What Changes That. appeared first on Mark8ng.com.

What buyers are actually saying

Sam Huston, svp of media at Dept, said there is not a client who would say no to testing AI visibility ads, given how disruptive GEO has already been to some businesses. But Stephan Kopp, managing director of Mediaplus Performance, argued the opposite: you can try to influence a large language model with paid content, he said, but it will not happen, and it is only a matter of time before AI developers tune their systems to ignore the workaround, the same way Google has repeatedly rewritten its search algorithm to close loopholes. A WARC study cited in the same reporting estimated that 63% of a brand’s visibility in AI answers comes from long-term brand equity, and only 26% from current marketing activity. If that number holds up, most of what a GEO vendor is selling you is a way to move a small slice of a much bigger picture.

The tools are shipping faster than the proof

None of that skepticism is slowing the vendor side down. Onclusive launched GEO Analytics in the US this week, tracking how brands appear across five AI engines, Gemini, ChatGPT, Grok, Claude, and Perplexity, and scoring which sources most influence what those engines say. It joins a growing list that includes Scrunch and Profound, all promising a dashboard where a founder or marketing lead used to have a spreadsheet and a lot of manual searching. The pitch is reasonable. The open question, the one none of these tools can fully answer yet, is whether what they are measuring actually predicts anything about revenue.

What you can check before paying anyone

A two-person marketing team at a regional B2B services company does not need a subscription to start. Pick the ten questions a prospect would plausibly type into ChatGPT, Claude, or Perplexity before hiring a company like yours, run them once a week by hand, and log which brands get named. Do the same for your closest three competitors. After four weeks you will know, without paying for a platform, whether your brand shows up at all and whether that changes week to week. That log is also the only way to sanity check a vendor’s dashboard later, because you will already know what the honest numbers look like.

When the paid version is worth it, and when it is not

A GEO tool earns its cost once you are tracking more brand and competitor combinations than a person can reasonably check by hand, or once someone above you wants a number to report every month regardless of what it means. This probably is not worth paying for if your marketing budget is still in four figures a month and you have not run the manual version for at least a month first. The risk is buying a dashboard before you know what question you are trying to answer with it, and then mistaking a rising citation count for a rising number of customers. Those are not the same thing, and nobody selling the dashboard is incentivized to remind you of that.

Editor’s note: This area changes quickly, so check the latest platform policy before making decisions based on AI visibility data.

If you already run Microsoft’s free topic-level AI visibility data, start there before you evaluate a paid tool. It will not give you the polish of a GEO Analytics dashboard, but it is free, and free is the right price for a category this unproven.

The post The GEO Tool Market Is Booming. Media Buyers Still Are Not Sure It Works. appeared first on Mark8ng.com.

Microsoft Advertising’s August product update added Topic Insights to the AI Visibility reporting inside Microsoft Clarity. Instead of listing individual citations, it groups them by subject: which topics AI systems associate with your brand, how often those topics come up, and where you are absent.

Three metrics worth understanding

Microsoft defined the vocabulary alongside the release:

• Grounding queries: the retrieval searches an AI system runs before it writes an answer
• Citation share: how often your domain shows up as a cited source
• Share of authority: how often your domain is cited compared with competing sources

Grounding queries are the interesting one. When somebody asks an assistant a messy conversational question, the system does not search for that string. It writes its own retrieval queries first. Those queries are the actual demand you need to be present for, and they are usually not what your keyword tool shows you.

Microsoft’s own recommendation, in the August Microsoft Advertising update, is to compare grounding queries against your existing search terms report, pull new keywords and negatives out of the difference, and adjust landing pages where competitors are cited instead of you.

What a small team should do with this

A concrete version. A software company selling scheduling tools to dental practices ranks for “dental appointment software” and buys that term. Topic Insights shows the brand cited on “practice management” and almost never on “patient no-show reduction”, where three competitors appear instead.

That is not a keyword gap in the traditional sense, because almost nobody types that phrase into a search box. It is a topic the retrieval layer generates on its way to answering “how do I stop patients missing appointments”. The action is a page that answers that question properly, not a keyword inserted into an existing one. It takes a day. The alternative is continuing to buy the term you already own.

The rest of the August update

Two Performance Max experiment types are now available: uplift experiments, which measure what PMax adds on top of existing campaigns, and upgrade experiments, which compare an existing Search or Shopping campaign against PMax after migration. Microsoft’s setup guidance is at least 30 conversions in the previous 30 days, identical bidding targets and settings between test and control, and four to twelve weeks before reading results.

That last number is the one people will ignore. A four week read on a low volume account is noise wearing a result’s clothing.

Ad Preview Hub now covers Performance Max as well, and adds Bing results page previews, so creative can be reviewed and signed off through a shareable link before spend starts rather than screenshotted afterwards. For an agency chasing legal or brand approval on assembled creative, that is a small workflow change that removes a recurring argument.

What can go wrong

The obvious limit: this is Microsoft’s view of AI citation behaviour, drawn from what Clarity can observe. It is not a complete census of every assistant. Treating share of authority as a precise market share figure will lead you somewhere silly.

Microsoft also continues to cite an average 8% increase in incremental conversions from Performance Max. That is a vendor figure about a vendor product. It is a reason to run the uplift experiment, not a substitute for running it.

And this may not be worth your week at all. If you are a local business with a small Bing footprint, the reporting is real but the audience it describes may be too small to build a process around. Check the volume before you commit anyone’s Tuesday to it.

The uncomfortable part

Every platform is now shipping its own AI visibility report, each measuring a slightly different thing, none of them agreeing with the others. Google shows AI impressions in Search Console. Microsoft shows citation share in Clarity. Neither tells you whether a person saw your name and remembered it.

The honest use of these tools right now is directional: find the topics where you are absent and competitors are present, fix the content, check again in a quarter. Anyone building a board-level KPI on these numbers this year should expect to rebuild it. We made a similar point about what Google’s AI impressions number does not mean.

Editor’s note: This area changes quickly, so check the latest platform policy before making compliance decisions.

Update, 11 August 2026: Clarity now splits branded from non-branded AI citations

Microsoft has added a distinction to the AI Visibility reporting described above: citations are now separated into branded and non-branded. Branded citations come from prompts that already contain your company name. Non-branded citations come from prompts that do not.

That split matters more than it sounds. A healthy-looking citation share made up almost entirely of branded prompts tells you that people who already know you can find you, which was never in doubt. The non-branded number is the one that tells you whether an assistant recommends you to somebody who has never heard of you, and on most accounts it is dramatically smaller. Microsoft is also explicit that the figure represents your share within what Clarity observes, not your share of the entire AI search market, which is worth repeating to anyone about to put it in a board deck.

The advice in the original post stands unchanged. Compare grounding queries against your search terms report, act on the topics where competitors appear and you do not. The only thing that changes is which number you report: filter to non-branded before you write anything down, and track that figure over time rather than the combined total.

The post Microsoft Will Tell You Which Topics AI Links to Your Brand appeared first on Mark8ng.com.

Here is what the control actually does, what it quietly takes with it, and why most small businesses arguing about this are arguing about the wrong decision.

What the setting covers

The control lives under Settings in Search Console, labelled Search generative AI. Google is rolling it out to a subset of verified properties, so it may not be in your account yet. Google’s own Search generative AI control documentation is the only source worth trusting on the specifics, because the behaviour has already changed once.

Leave it on the default and your content can appear as links inside AI Overviews, AI Mode, and the generative features in Discover, and it can be used to ground those answers. Switch it to exclude and your site drops out of all of that, links included. Google says it began respecting these changes on 17 June. Processing takes a few days, then content usually falls out within a day or two, though caching can stretch that.

What it does not do matters just as much:

• It is not a ranking signal. Your position in regular search results should not move.
• It does not override Merchant Center or Google Ads. Shopping participation stays a separate decision.
• It does not stop your content being used for AI training. That runs through Google-Extended in robots.txt, which is a different lever entirely.

Those three distinctions catch people out constantly. If your goal is to keep your writing out of model training, this toggle does nothing for you.

The part nobody mentions in the setup guide

Google treats AI features and regular results as separate things. Google’s actual results page does not always agree.

Top Stories carousels have started rendering inside AI Overviews. John Shehata of NewzDash put the rate at roughly 1 in 6 US trending news queries, or 15.5% of tracked results where Top Stories appeared, with the UK figure at 17.46%. His reading is that opting out of AI features will likely pull publishers out of Top Stories when the carousel sits inside an AI Overview.

Two caveats worth holding onto. NewzDash sells news visibility tracking, so it has commercial interest in the finding, and it has not published sample sizes or collection dates. Google has not confirmed how the control handles a traditional feature displayed inside an AI feature. Search Engine Journal covered the full detail of the opt-out trade-offs if you want the longer version.

Still, the principle holds even if the number moves: a property-level switch can remove placements that were never described as AI placements.

You cannot currently measure what you would lose

This is the real problem with the decision.

The generative AI performance report, also rolling out to a subset of accounts, shows impressions from AI features broken down by page, country, device and date. Impressions only. No clicks. No queries. Your analytics can show Google organic referrals, time on site and conversions, but it cannot separate a visit that came from an AI Overview from one that came from a blue link.

So the maths is: unknown traffic value, unknown conversion value, against a change you can reverse but only after several days of processing and caching. The UK’s Competition and Markets Authority has required Google to supply click data and click-through rates, with most of those measures starting in December, and page-level controls by March 2027. Until then you are guessing.

A worked example

Take a six-person accountancy firm in Manchester running a blog on tax deadlines and allowances. Their content is exactly the kind that gets summarised: short factual answers with numbers in them. The partner reads about AI Overviews eating clicks and wants to opt out.

Before touching anything, the useful questions are:

1. Does the property even have the control yet? If not, the decision is theoretical.
2. What does the generative AI report show in impressions, and how does that compare to total search impressions? If AI features are 3% of impressions, this is not where the business is won or lost.
3. What is a blog visit actually worth here? For that firm, a tax-deadline article is not monetised by the pageview. It is monetised when someone reads it, trusts the firm, and calls. Being cited inside an AI answer with a link still supports that. Being absent supports nothing.

That third point is where most of these conversations go wrong.

The uncommon takeaway

The opt-out is a publisher’s tool wearing a webmaster’s clothes.

It makes sense if your revenue comes from impressions on your own pages, because in that model an AI answer that satisfies the user is a direct substitute for your business. That is the situation news publishers are in, and it is why the CMA forced the control into existence.

Most small businesses are not in that model. They sell services, software or products, and their content exists to get them in front of someone who might buy. For those sites, opting out removes a discovery surface and protects nothing measurable. The honest recommendation for the large majority is to leave it alone and spend the same hour on getting cited inside AI answers instead.

What can go wrong

Three things, in rough order of likelihood.

You lose placements you did not know were connected. The Top Stories pattern is the known case. There may be others that nobody has tracked yet, because the boundary between AI surfaces and traditional ones keeps moving.

You cannot prove the decision either way. With impressions-only reporting, you will not be able to show anyone, including yourself, whether opting out helped. That is an uncomfortable position to be in six months later when traffic has drifted for unrelated reasons.

It is all or nothing. The control works at property level. If you have one section of the site where being summarised genuinely costs you and another where visibility helps, you cannot split them until page-level controls arrive in 2027.

This may not be worth thinking about at all if AI features are a small share of your impressions, if you sell something with a considered buying process, or if your property has not received the setting yet.

Editor’s note: This area changes quickly, so check the latest platform policy before making compliance decisions.

What to do this week

Open Search Console and check whether the Search generative AI control and the generative AI performance report exist on your property. If they do, record your current AI impressions figure and today’s date somewhere you will find it again. Then wait. The click data Google has been required to supply starts arriving in December, and that is the first point at which this becomes a decision you can actually make with evidence rather than instinct.

If you find yourself impatient with that answer, ask what you would do differently tomorrow if the numbers came back either way. For most sites, honestly, nothing.

The post Google’s AI Search Opt-Out Is Live. Here Is What You Give Up. appeared first on Mark8ng.com.