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By Eric Richmond, Founder of CiteMetrixTeams are being briefed on agentic readiness, and many of those briefs begin with...
10/15/2026

By Eric Richmond, Founder of CiteMetrix

Teams are being briefed on agentic readiness, and many of those briefs begin with content: what to publish, how to structure it, and how to make it easier for AI systems to understand.

Those are reasonable questions. They are not the first questions.

The harder questions are operational:

- Who owns the accuracy of a fact?
- Who approves it before publication?
- Who verifies that a correction actually changed what AI says?

That is the beginning of brand knowledge governance. Optimization comes later.
Related reading: Our companion piece, The Holiday Shopper Might Arrive as an Agent — and Your Feed Is Now Your Storefront, covers readiness for agent-mediated commerce — product feeds, structured data, and agent routes to purchase. Read that piece for the commerce context. This one focuses on ownership, approval, and verification.

By Eric Richmond, Founder of CiteMetrix Teams are being briefed on agentic readiness, and many of those briefs begin with content: what to publish, how to stru

By Eric Richmond, CiteMetrixAI can use your page to build an answer without ever naming your brand.That is not a rare ed...
10/14/2026

By Eric Richmond, CiteMetrix

AI can use your page to build an answer without ever naming your brand.

That is not a rare edge case. It is the default in a significant share of AI citations, according to research from Semrush and Kevin Indig. In its September 21, 2026 article, “AI citation outreach: a Semrush & Claude workflow,” Semrush reported that 62% of AI citations produce no brand mention.

They call these ghost citations.

The distinction matters because a citation is not credit. A source attribution and a brand mention are two different events. Conflating them is one reason AI visibility reports can look healthy while brand preference does not move.
AI visibility is four different states
Most AI visibility discussions compress several distinct outcomes into one metric. In practice, there are at least four states:

- Retrieved: An AI platform fetched or accessed your page.
- Cited: Your URL appears as a source in the answer.

By Eric Richmond, CiteMetrix AI can use your page to build an answer without ever naming your brand. That is not a rare edge case. It is the default in a sign

“Web content may also confirm facts or be linked to within Google’s AI after a response is generated, but those instance...
10/13/2026

“Web content may also confirm facts or be linked to within Google’s AI after a response is generated, but those instances don’t qualify for AI contribution.”
That line, shown in screenshots of Google’s help text, is the most important part of the company’s new AI contribution pilot.

Google has written down, in plain language, that confirming a fact or being linked inside an AI answer does not count as a paid contribution.

The implication is uncomfortable:

Being cited is not being credited. Being linked is not being believed.

There is an important caveat. This is an early-stage, invitation-only pilot for selected publishers. It is not a program brands can sign up for, and it is not a general licensing scheme.

But the pilot is still valuable to study because Google’s own accounting reveals how it thinks about value in an AI answer.

“Web content may also confirm facts or be linked to within Google’s AI after a response is generated, but those instances don’t qualify for AI contributio

By Eric RichmondMost generative engine optimization advice focuses on tactics: add structured data, improve your content...
10/12/2026

By Eric Richmond

Most generative engine optimization advice focuses on tactics: add structured data, improve your content, publish an llms.txt file, or earn more third-party mentions.

The harder question is what happens next — how do you know whether those changes worked?

Olaf Kopp’s framework, published in Search Engine Land on September 16, 2026, is useful because it separates GEO into three measurable pillars:

- LLM readability
- Brand context
- Agentic commerce

This is Kopp’s framework, not CiteMetrix research. But it gives teams a practical way to connect GEO work to distinct signals instead of treating “AI visibility” as one mysterious number.

By Eric Richmond Most generative engine optimization advice focuses on tactics: add structured data, improve your content, publish an llms.txt file, or earn mo

By Eric Richmond, Founder of CiteMetrixA recent survey of search experts described branded search volume as “the new lin...
10/09/2026

By Eric Richmond, Founder of CiteMetrix

A recent survey of search experts described branded search volume as “the new link.”

That is a useful way to think about the shift, but it is important to be precise about what the evidence does and does not show.

In its Google Ranking Factors Expert Survey 2026, published September 9, 2026, Zyppy Signal, led by Cyrus Shepard, surveyed 131 search professionals. Brand signals were named among the top three factors by 27.0% of respondents. In a companion Google AI Ranking Factors article published September 16, “Brand / Entity in LLM Memory” ranked third among the surveyed AI factors, with an average rating of +2.08 on a scale from -3 to +3.

These are expert opinions, not measured performance data. Zyppy’s contributors also noted the uncertainty around how Google and AI systems work. The survey should not be read as proof that branded search volume is a direct ranking input or that increasing it guarantees more visibility.

By Eric Richmond, Founder of CiteMetrix A recent survey of search experts described branded search volume as “the new link.” That is a useful way to think

By Eric RichmondTwo stories from this week only make sense when you put them next to each other.First, Google’s AI contr...
10/08/2026

By Eric Richmond

Two stories from this week only make sense when you put them next to each other.

First, Google’s AI contribution pilot says that web content linked inside an AI answer, or used to confirm facts after the answer is generated, does not qualify for payment.

Second, as reported by Search Engine Watch on September 23, Google AI Mode is serving sponsored product carousels as conversational continuations of an AI answer. They are labelled “Sponsored,” but they read more like advice than a traditional ad unit.

The synthesis is simple:

The citation is worth nothing. The adjacent slot is for sale.

That does not mean Google is doing something improper. Sponsored placements are labelled, and advertising inside a new search format is ordinary product development.

But it does mean that one of our most comfortable assumptions about AI search is no longer reliable:
AI visibility is earned media.
Some of it is earned. Some of it is paid.

By Eric Richmond Two stories from this week only make sense when you put them next to each other. First, Google’s AI contribution pilot says that web conten

By Eric Richmond, CiteMetrixSemrush’s September 8, 2026 study of the manufacturing vertical found that only two domains ...
10/07/2026

By Eric Richmond, CiteMetrix

Semrush’s September 8, 2026 study of the manufacturing vertical found that only two domains appeared in both its top-mentioned and top-cited lists. That finding is more important than it may look.

If the brands AI talks about most are not the same domains it uses as sources, then AI visibility is not one measurement.

It is a set of related outcomes. At minimum, you need to separate three:

- Being mentioned
- Being cited
- Being recommended

These outcomes overlap, but they do not mean the same thing. They have different causes, different business implications, and different fixes.
The three layers of AI visibility
1. Mentioned: your brand appears in the answer
A brand is mentioned when its name appears in an AI-generated response.

For example, someone asks:
“What are the leading suppliers of industrial automation equipment?”
If the answer includes your brand name, you have earned a mention.

By Eric Richmond, CiteMetrix Semrush’s September 8, 2026 study of the manufacturing vertical found that only two domains appeared in both its top-mentioned a

If your team already has a working SEO program, you are not starting from zero with GEO marketing.You already understand...
10/06/2026

If your team already has a working SEO program, you are not starting from zero with GEO marketing.

You already understand crawlability, content quality, technical hygiene, search intent, authority, and measurement. Those fundamentals still matter because AI assistants draw from the open web. Strong SEO gives AI systems more useful, accessible, and authoritative information to retrieve.

What changes is the destination.

Traditional SEO is largely about earning visibility in a search results page. GEO marketing, also called generative engine optimization, is about helping AI systems retrieve, understand, synthesize, and cite your brand in an answer.

GEO is not a replacement for SEO. It is the second half of the same search visibility program.
Why SEO teams are well-positioned for GEO marketing
Teams with established SEO practices already have several advantages.
Authority carries over
AI systems need sources they can use to construct answers.

If your team already has a working SEO program, you are not starting from zero with GEO marketing. You already understand crawlability, content quality, techni

By Eric Richmond, CiteMetrixSearch Engine Land recently published a useful warning for anyone measuring AI visibility.In...
10/05/2026

By Eric Richmond, CiteMetrix

Search Engine Land recently published a useful warning for anyone measuring AI visibility.

In a 30-day study of 15 commercial-intent SaaS keywords across six platforms, the publication logged 298 appearances split this way:

Platform
Logged appearances

Gemini
104

Google AI Mode
95

Claude
59

ChatGPT
32

Grok
4

Perplexity
4

Those figures come from Search Engine Land’s September 14, 2026 article, “Two GEO experiments challenge conventional AI visibility advice”, by Zeeshan Yaseen.

The twist is more important than the chart.

In the earlier experiment, ChatGPT led.

Same general questions. Different platform. Different answers. Different month.

That is the central measurement problem in AI search: AI visibility is not one number. It is a distribution.

And if your reporting collapses that distribution into one blended score, you may be hiding the information your team needs most.
A blended score can hide the real picture
A composite score is useful.

By Eric Richmond, CiteMetrix Search Engine Land recently published a useful warning for anyone measuring AI visibility. In a 30-day study of 15 commercial-int

By Eric Richmond, CiteMetrixA chatbot can recommend your brand and help create a purchase. It can also surface a limitat...
09/30/2026

By Eric Richmond, CiteMetrix

A chatbot can recommend your brand and help create a purchase. It can also surface a limitation, repeat an outdated detail, or point the buyer toward a competitor.

That two-sided influence is the important finding in new research from Semrush and Exploding Topics.

In their survey of 2,338 adults in the United States, published by Semrush on September 7, 2026, 73.58% of respondents who used AI at least weekly said they had purchased a product based on an organic AI recommendation. At the same time, 57.5% of AI users said they had decided not to buy something based on information from a chatbot.

The same channel produced a purchase decision for 73.58% of weekly AI users, and talked 57.5% of AI users out of one.

That is not simply a funnel.

It is an influence layer with two directions.

By Eric Richmond, CiteMetrix A chatbot can recommend your brand and help create a purchase. It can also surface a limitation, repeat an outdated detail, or poi

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