Your Buyer Asked An AI About You And Got Somebody Else's Answer
Be the source the model quotes
Your prospect no longer opens ten tabs. They ask ChatGPT which consultant handles webinar funnels, or ask Perplexity what a course launch funnel should cost, and they act on the three names that come back.
You were not one of them. Not because you are worse, but because your site was not structured in a way the model could read, quote and attribute. That is a solvable problem and most of your competitors have not touched it yet.
I structure your content, your entities and your technical setup so AI systems can find you, understand what you do, and cite you when your buyer asks.
This work goes by several names. Answer engine optimization, generative engine optimization, AI search visibility, LLM optimization. The terminology has not settled and the acronyms will keep changing. The job underneath is the same one: making your expertise readable, quotable and attributable to you.
Why does AI never mention my business?
Six reasons. Most sites have four of them at once.
- Your pages render in the browser rather than on the server, so a crawler that does not execute JavaScript sees an empty page
- Your service pages are anchor links on the homepage rather than real URLs, so there is nothing specific for a model to point to
- Your content answers no question directly. It describes what you offer instead of answering what people ask
- Your claims carry no figures or sources, and models skip unverifiable statements when assembling an answer
- Your business name, role and specialty are stated inconsistently across your site, LinkedIn and directories, so no clear entity forms
- Everything you publish lives on someone else's platform, so the citation goes to LinkedIn rather than to you
None of these are ranking problems. A page can rank on Google and still be invisible to an answer engine.
Ask an AI the question your best client would ask before hiring you. Whatever comes back is where this starts.
Models cite what they can extract, not what ranks
Search engines rank pages. Answer engines assemble answers. Those are different jobs and they reward different things.
A model composing an answer needs a passage it can lift: a direct statement, attached to a clear question, attributable to a named source, and specific enough to be worth quoting. A page that buries its answer under three paragraphs of positioning is unusable, however well it ranks. A page that states a price, a timeline or a number in one clean sentence gets quoted, even from a domain with little authority.
This is why the AEO opportunity is real for small businesses right now. Ranking rewards accumulated authority, which takes years. Extraction rewards structure and specificity, which takes weeks. A well structured consultant site can be cited alongside sources with a thousand times its traffic.
That window will narrow as bigger players restructure. It has not narrowed yet.
Who this is for
- You sell something people research before buying, which means they are asking AI about it
- Your competitors appear in AI answers and you do not
- Your site was built as an experience rather than as a document, and crawlers see very little of it
- You publish real expertise that currently sits on LinkedIn or YouTube rather than on your own domain
- You want to move before this becomes standard practice rather than after
Who this is not for
- Nobody asks AI about your category yet. Some local and impulse purchases are not researched this way. Worth checking before investing
- You want guaranteed citations. Nobody controls what a model outputs. What is controllable is whether your content is extractable, which is a precondition rather than a promise
- You have nothing distinctive to say. Models cite sources that add something. Content restating what twenty other pages say gives no reason to pick yours
- You want this instead of SEO. They overlap heavily and compete for none of the same budget. Answer engines still crawl, and crawlers still need pages
Any of that ring true? Say so early, because this is the service where expectations are easiest to set wrong.
What is included in an AEO engagement?
- Visibility baselineWhat ChatGPT, Perplexity, Claude and Google AI Overviews currently say when asked the questions your buyers ask. Who gets cited, what they say about you if anything, and where the gaps are. Recorded so change is measurable later.
- Crawlability and access testingWhether AI crawlers can actually read your site. Server rendering, robots rules, JavaScript dependency, blocked user agents. This is the failure that silently invalidates everything else, and it is common on modern site builds.
- Question researchThe questions your buyers actually ask a model, which are longer and more specific than search queries. These become the structure the content gets built on.
- Content restructuringExisting pages rewritten so answers appear directly under question headings, in extractable form, near the top rather than after the positioning.
- Entity consistencyYour name, business, role, specialty and credentials stated identically across your site, LinkedIn, directories and any profile a model might read. Inconsistency prevents a stable entity from forming.
- Structured dataSchema for organization, person, service, FAQ and article, so the machine readable layer agrees with what the page says.
- llms.txt and technical setupThe emerging conventions for declaring what your site contains and how it may be used, implemented alongside the standard technical work.
- MeasurementRe-testing the same questions on a schedule, so movement is visible rather than assumed.
What gets restructured?
- Service pagesRebuilt so each answers the questions asked about that service, with the answer stated before the argument for it.
- Question and answer contentDedicated pages for the specific questions buyers ask, written to be extractable rather than to be long.
- Case studies and proofResults stated as specific figures with named clients and dated screenshots, which is what makes a claim quotable rather than skippable.
- Entity profilesSite, LinkedIn, directory and profile listings aligned so they describe the same business in the same terms.
- Technical layerServer rendering, crawler access, schema, sitemap and llms.txt.
- Owned publishingExpertise currently living on third party platforms brought onto your own domain, so the citation points at you.
What this looks like in practice
AEO work is running with clients now and the measurement periods are still open, so what follows describes the method rather than claiming outcomes. When there are results worth showing, they will appear here as screenshots with dates like everything else on this site.
- Baseline before anything changesThe same set of buyer questions gets asked across ChatGPT, Perplexity, Claude and Google AI Overviews, and the answers get recorded. Without that record, later improvement is a story rather than a measurement.
- Crawlability tested, not assumedSites get fetched the way a crawler fetches them. Modern builds frequently return almost nothing without JavaScript, and the owner has no idea, because it looks fine in a browser. This test comes first because everything downstream depends on it.
- Answer first, argument secondA page states its answer directly under the question heading, then supports it. This reads slightly blunter than marketing copy usually does, and that bluntness is what makes it quotable.
- Specificity over adjectives"$2,000 to $10,000" gets cited. "Pricing varies by project" does not. Every claim gets a number, a date, or a named source attached, or it gets cut.
- Entity alignment across platformsThe same description of the business everywhere a model might read it. This is unglamorous work and it is frequently the difference between a model recognizing a business and treating three mentions as three unrelated things.
- Re-tested on a scheduleThe same questions asked again at intervals. Movement in AI answers is slower and noisier than search ranking, so a single check proves little.
- Run on this site firstI ran this audit on marketerzee.com before selling it. Seven indexed pages, 105 impressions across three months, and twenty two case studies sitting behind modals no crawler could open. The findings and the numbers are published in full: I audited my own site for AI search.
That post exists because this page would otherwise be the only service here with no evidence behind it.
How much does AEO cost?
- From $1,200AI visibility auditBaseline testing across the major answer engines, crawlability and access testing, entity consistency review, and a prioritized findings list. No implementation.
- From $3,000Foundation buildEverything above plus technical fixes, schema, llms.txt, entity alignment across platforms, and restructuring of your core service pages.
- From $5,000Ongoing programFoundation work plus question research, new answer content published on a schedule, and re-testing over a defined period. Minimum three months, because a single measurement point tells you nothing.
Sites needing a rebuild to become crawlable at all are quoted separately, because that is development work rather than content work.
Terms are 50% upfront, balance on delivery.
Start with the audit if you are unsure this applies to you. It answers the only question that matters first: are people asking AI about your category, and is your site even readable when they do.
And if the audit finds your site is not crawlable, that gets fixed before anything else. Publishing more content onto a site a model cannot read is spending money to change nothing.
Send me the questions you tried and the answers you got back. That is the baseline everything gets measured against.
How long does AEO take?
Set expectations on the lag. Technical and structural fixes take effect when systems next crawl and refresh, which is not immediate and is not on a published schedule. Movement in AI answers typically shows over months rather than weeks, and it moves unevenly across different engines.
| Scope | Timeline |
|---|---|
| AI visibility audit | 1 to 2 weeks |
| Foundation build | 3 to 5 weeks |
| Ongoing program | 3 months minimum |
How the project runs
- BaselineBuyer questions asked across the major answer engines and recorded, plus crawler access tested against your live site.
- Fix accessRendering, crawler permissions, schema and sitemap. Nothing else matters until a model can read the page.
- Restructure and publishExisting pages rewritten for extraction, new answer content built from real buyer questions, entity details aligned everywhere.
- Re-testThe same questions asked again at intervals, with results compared against the baseline rather than against impressions.
Questions people ask before hiring me
What is the difference between AEO and GEO?
In practice, none worth billing separately for. Answer engine optimization usually describes being cited in a direct answer. Generative engine optimization usually describes being represented in generated content. The technical work, the content structure and the entity alignment are identical, and anyone selling them as two services is selling you the same thing twice.
Is this just SEO with a new name?
There is overlap, mainly on the technical side, and the two support each other. The difference is what each optimizes for. SEO works toward ranking a page. AEO works toward a passage being extractable and attributable inside a generated answer. A page can do one well and the other badly.
Can you guarantee ChatGPT will cite me?
No, and anyone who does is selling something they do not control. Model outputs vary by phrasing, by user, and by version. What is controllable is whether your content can be read, understood and quoted at all, which is where most businesses currently fail.
How do you measure it?
The same buyer questions asked across engines on a schedule, with answers recorded and compared. It is slower and noisier than rank tracking, so measurement periods are months rather than weeks.
Does this need new content or can you fix what exists?
Usually both. Existing pages get restructured first, because they carry whatever authority you already have. New content follows for questions nothing on your site currently answers.
What is llms.txt?
A file at your site root declaring what your site contains and how AI systems may use it, similar in spirit to robots.txt. Adoption is still uneven across providers. It is cheap to implement and worth having in place before it matters.
Should I wait until this settles down?
The mechanics will keep changing. The underlying requirement will not: content that can be read, understood and attributed. That work does not become obsolete when a provider changes its approach.
Will this hurt my Google rankings?
Structural clarity, direct answers and valid schema are what search engines have asked for anyway. The technical fixes involved usually improve both.
The Window Has Not Closed Yet
Most of your competitors have not touched this yet. That is the entire opportunity, and it has a shelf life.