Credible Roots / Be the name AI answers with
Public record building
Be the name AI answers with
When someone asks an answer engine who the expert in your field is, a handful of names come back. This is the work that puts you in that set, and it is more mechanical than most people assume.
AI answer engines mostly compose replies from material they retrieve at the moment someone asks, then cite a small number of sources. Being named depends on three things, in order. First, access: if crawlers such as GPTBot, ClaudeBot, PerplexityBot or Google-Extended cannot reach your pages, no amount of quality will get you cited. Second, extractability: a passage that states a complete, specific fact can be lifted and attributed, whereas positioning language gives a retrieval system nothing to quote. Third, corroboration: a claim that appears only on your own site is treated as a claim, while a fact repeated across independent sources is one the system will assert. Structured entity presence, particularly Wikipedia and Wikidata, is repeatedly the strongest single lever.
How the work actually runs
Baseline
We run the questions your buyers actually ask across the major answer engines and record who gets named instead of you, and which sources those answers cite. That tells us what to build rather than what to guess.
Access
We check that the crawlers behind each answer engine can reach your material, and that your pages exist without JavaScript. Blocked or unrenderable pages are the most common silent failure, and it is usually a host setting nobody chose deliberately.
Entity resolution
Structured data, a canonical identity, Wikidata where you qualify. A system will not confidently name someone it cannot resolve.
Quotable material
Publishing work that answers a specific question directly, near the top, in complete sentences with names, dates and numbers. This is a writing discipline more than a technical one.
Corroboration and monitoring
Getting independent sources to repeat the same facts, then re-running the baseline queries so you can see the answers change.
What we do not promise
- That a given model will name you. These are probabilistic systems that change without notice.
- Consistency. The same question asked twice can return different answers.
- A share-of-voice number that means anything on its own.
- Results without underlying substance. There is no prompt trick that substitutes for being a credible source.
Who this fits, and who it does not
| A good fit | Not yet | |
|---|---|---|
| Subject | Known for something specific and nameable | Broad generalist positioning with no defined subject |
| Material | Willing to publish real views and specifics | Only wants approved marketing language |
| Corroboration | Has or can earn independent references | Expects on-site work alone to be enough |
| Measurement | Comfortable with directional evidence | Wants a guaranteed ranking number |
The whole method, published
The mechanical layer is documented in full, including how to check it yourself.
What the data says about being cited
One finding here matters more than everything else, and it reframes what this work actually is.
Published research
| Finding | Figure | Source |
|---|---|---|
| AI citations coming from earned media rather than owned content | about 84% | Muck Rack, May 2026 |
| Brands more likely to be cited through third parties than their own domain | 6.5x | AirOps, October 2025 |
| ChatGPT citation presence in professional services prompts | under 4% | Similarweb, May 2026 |
| AI referral traffic as a share of total web traffic | about 1% | Search Engine Land, 3.3bn sessions |
Read those together and the honest conclusion is unusual for a page selling this service. Optimizing your own site is a small part of it; most citations come from what other people published about you. And in professional services specifically, citation rates are the lowest of any category. This is worth building for the long term, not as a quick traffic channel.
Questions people actually ask
How do AI tools decide who to cite?
They retrieve pages relevant to the question, then quote the ones stating something clearly, factually and self-containedly. Pages that make a direct claim near the top and are corroborated elsewhere are far easier to cite than pages that bury the point.
Does blocking AI crawlers hurt visibility?
Directly. If your robots.txt or host settings block a crawler, that system cannot retrieve your pages to cite them. Some publishers block deliberately for licensing reasons, which is legitimate, but it should be a decision rather than an accident.
Can you guarantee ChatGPT will mention me?
No, and nobody can. These are probabilistic systems whose answers vary between sessions and change as models update. What can be improved is the odds, by making you retrievable, quotable and corroborated.
How is this measured?
By running the buying-intent questions your audience asks across several engines, in clean sessions, and recording who gets named and which sources are cited. Repeated over time that shows direction, which is the honest form of measurement here.
Read the method before you buy it
We publish how this works in full, including the parts that make a sale harder.
Sources
- OpenAI. Overview of OpenAI crawlers — GPTBot, OAI-SearchBot and ChatGPT-User.
- Anthropic. Crawler documentation — ClaudeBot, Claude-User and Claude-SearchBot.
- Google Search Central. Crawlers and user agents, including the Google-Extended control.
- RFC 9309. Robots Exclusion Protocol.
Where a claim rests on documentation, the documentation is linked above rather than summarized. Corrections go on our corrections page.
How this was made: written from the work we do for clients and from the research cited on this page, drafted with AI assistance, then reviewed and approved by the named author before publication. Our editorial standards.
See what AI says about you today
We will run the questions your buyers ask, show you who gets named instead of you and which sources those answers lean on, then map what would change it.
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