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AI search optimization
AI search optimization is the work of making a brand eligible to be named in the answers ChatGPT, Perplexity and Google AI Overviews give to buying questions — by being present, accurately, on the sources those answers are built from.
I do it as a placement program for one business at a time: three months minimum, from $1,500 a month. It starts from a measured category source map and an AI traffic check, works through the sites that decide your category and the fixes your logs call for, and re-measures every month in the identical mode. Whether an engine picks you is decided inside the engine. What is guaranteed is the work and the measurement.
Independent consultant, not an agency. Everything is delivered in writing; no call is required.
The discipline is also called GEO, generative engine optimization, or AEO, answer engine optimization. The labels are interchangeable. The methods behind them are not.
The mechanism
Two kinds of question, two different jobs
Across twenty tracked purchase queries on a live store, one split held without a single exception, and it decides what work is worth doing.
Questions of fact
Who delivers to this city today? What is in stock? What does it cost? These are answered from your own pages. Publish the checkable fact and the engine can quote it. Whether it picks you is decided elsewhere.
Questions of judgment
Which brand is best? Who is trustworthy? These are answered from other people's pages. Your own site barely participates. Winning here means getting into the sources the engines already quote — a slower, different job.
Most of the money spent on AI visibility is spent writing content for judgment questions on the brand's own site, where it cannot work. The first week of any engagement is spent establishing which of your questions fall on which side, because that determines everything after it.
Where the answers come from
The citation layer is category-specific, and it must be measured, not assumed
Two categories measured three days apart, same protocol, opposite results:
Consumer electronics, UAE
Around twenty third-party domains carry the category: local ranking guides, price aggregators, one review platform. A poor review score on a third-party site changed the wording of an answer directly, downgrading a major retailer inside the text.
GEO services, English
About ninety per cent of citations are the vendors' own websites. Across sixty-odd answers there was not one review platform and not one forum thread. Building reviews for citation here would be wasted work.
The same prescription applied to both categories would fail in one of them. This is the single most common reason a GEO engagement produces nothing: a generic playbook, applied without measuring where that particular category's answers are sourced from.
Engagement
Three months, measured every month
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Start — baseline and prediction
The category source map and the AI traffic check, if you do not have them already: your questions, three runs each across two engines in one fixed mode, and fourteen days of server logs. A written prediction of what will move and what will not, registered before any work starts.
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Month 1 — the sites that decide your category
In most categories two to four third-party sites carry the answers: a ranking, a review platform, a comparison table. Listings, applications, corrections and review programmes on exactly those sites. A paid placement buys a crawl; only your name in the text gets quoted — the brief says so.
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Month 1 — the pages engines enter through
On a measured site the live fetcher took the homepage on 84% of its visits; on a young domain the engines read only the pages external links pointed to. Those entry pages get the checkable facts — assortment, prices, delivery windows, stock — in plain text.
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Month 2 — what the logs showed
Crawler permissions, structured data that contradicts the page, placeholder URLs, redirects. One change at a time, each verified in the server logs within days. Necessary, and on its own it moves nothing in the answers — I will say so rather than bill it as a strategy.
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Every month — monitoring
ChatGPT's live fetcher, tagged clicks and direct visits side by side. If the channel drops, you know the same day — and whether it was lost tracking, lost visits, or something on the site.
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Every month — re-measurement
The same questions, the same runs, the same mode. The report separates what the work caused from what merely happened at the same time, and includes the failures: on the reference deployment, thirty pages built for one content pattern earned zero citations in eleven days, and that is written up as plainly as the wins.
Evidence
The reference deployment, and my own zero
Eight weeks on a bootstrapped specialty e-commerce store in the UAE, no ad budget: ten of twenty tracked purchase queries reached the top five in ChatGPT from a baseline of zero. That is an observation, not a proof: there was no control group, and in October ChatGPT's live fetches of the same store fell fourfold with no change to the site. The site's own phrasing did come back verbatim inside answers.
The same page should tell you the other half. This site was measured against ten of its own buyer questions and scored zero out of ten in both engines. The prediction that it would score zero was written down before the measurement was run, and the re-test date is fixed. Six of those ten questions return no vendor list to anybody, which is exactly the finding the method is built to produce early.
A consultant whose own site is not yet cited is either honest about it or hiding it. The measurement is published here for the same reason I will hand you your raw answers: numbers you cannot check are not evidence.
Limits
Three things I will not sell you
A ranking, or a "top 3 in ChatGPT"
Positions do not exist in answer engines. The same question, asked in the same minute on two accounts in an identical mode, returned a five-name shortlist to one and no shortlist at all to the other. What is measurable, and what I report, is the share of answers that name you on a fixed question set.
An llms.txt strategy
Across roughly 2,100 verified crawler fetches on two sites, the number of requests to /llms.txt from GPTBot, ChatGPT-User, OAI-SearchBot, PerplexityBot and ClaudeBot was zero. Only bingbot and YandexBot ever fetched the file. Publishing one is harmless; charging for it as a mechanism is not honest, and I removed that claim from this site when the logs contradicted it.
Pages built to match the shape of a query
Thirty pages of the "where to buy X in [city]" pattern earned zero citations in eleven days on a site that was being cited elsewhere in the same period. It is a dead layer for purchase questions. Guides that answer how to choose between products do get cited — the distinction is measurable and it is not the one most playbooks make.
Price
Four ways in
| What | Scope | Price |
|---|---|---|
| Category check | Four of your buyers' questions in ChatGPT and Perplexity. The answers verbatim, every source listed under its answer. No scoring. Two working days. | Free |
| AI traffic check | Fourteen days of your server logs: which pages ChatGPT and Perplexity actually read, whether a ChatGPT drop is lost tracking or lost visits, and what your structured data claims that your pages do not. No prompts. Three working days. | $400 |
| Category source map | Ten buyer questions, three runs each, two engines. The two to four third-party sites that decide answers in your category, whether you are on them, what each requires, and which popular tactics do not work in your category. Five working days. | $600 |
| Placement program | Getting onto those sites, fixing what the logs showed, monthly re-measurement and ChatGPT fetcher monitoring. Guaranteed: the work and the measurement. Not a citation. Three months minimum. | from $1,500/mo |
Questions
Frequently asked
What is AI search optimization?
The work of making a brand eligible to be named inside the answers AI engines generate for buying questions, rather than ranked in a list of links. Nobody controls whether it is picked. In practice it means publishing checkable facts where the engines actually retrieve them, making the site machine-readable, and — where the category requires it — appearing in the third-party sources the engines quote.
Is AI search optimization different from SEO?
The technical foundations overlap almost completely, and anyone claiming otherwise is selling novelty. What differs is the target and the measurement: a citation inside an answer instead of a position on a page, measured as a share of repeated runs instead of a rank.
Which engines are worth optimising for?
It depends on what you sell. For a product business ChatGPT carried the great majority of measured arrivals. For a service business it is the opposite: ChatGPT returns a vendor list on only a couple of phrasings, while Perplexity names providers freely on nearly all of them. That is measured, not assumed, and it is the first thing the baseline settles.
How long before anything changes?
Weeks, not days. Between publishing a change and seeing it in answers sits crawl, index and retrieval. On the reference deployment a measurement taken eleven days after a large publication showed nothing from that layer, while other work from the same period was already being cited. That is why the program runs at least three months and re-measures every month.
Do you work with agencies?
Yes, on a white-label basis. The deliverable is a written work order your developers execute and I verify from outside — no access to your systems is required for the technical layer.
What if nothing moves?
Then the report says so, with the evidence. Whether an answer engine picks you is decided inside the engine, and no consultant controls it. What is guaranteed is the measurement: if it cannot be run to the protocol, you do not pay.
Find out whether your category is winnable
Send your site and three or four questions your buyers actually ask. The free check comes back in two working days with the eight runs, the names that appeared instead of yours, and the domains the engines cited.
alex@citedlayer.com