GEO and AEO are the work of preparing your site and external mentions so that ChatGPT, Perplexity, Google AI Overviews and other assistants can take an accurate fact about you and name the company in their answer.
A share of buyers now gets an answer without opening a single website: they ask an assistant, they read an AI summary at the top of the results. In that situation your ranking matters less than whether you made it into the answer and what was said about you. It works differently from classic SEO: the assistant assembles a reply from several sources — your site, business listings, reviews, articles, niche aggregators — and retells them in its own words. So the work runs on two fronts: a site an assistant can quote accurately (direct answers, tables of terms, schema markup, the same figure in every section, crawlers not blocked) and the external mentions it leans on. Being cited cannot be guaranteed — the answer is generated anew each time. What can be done is honest measurement: a fixed prompt set, a regular re-run, and the share of answers that name your brand.
Prospects ask ChatGPT for recommendations — it lists your competitors. You lose deals that never showed up in Google Analytics.
People get a complete answer in the results or from an assistant and never open a site. If that answer doesn't mention you, you aren't part of the decision.
Millions use AI search daily. These systems cite structured sources — your content doesn't fit that mold.
LLMs prefer clear definitions, numbered lists, factual precision. Marketing copy without structure gets ignored.
Without Wikidata, Wikipedia, or verified Google Knowledge Panel — LLMs can't identify you as an authoritative source.
How often does ChatGPT mention you? For which queries? What context? Without measurement, you're flying blind.
Benchmark your brand across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overview on 50-200 queries. Full competitive comparison.
Definitions, numbered lists, FAQs, factual precision. Format LLMs love to cite.
Wikidata entries, Wikipedia articles, Google Knowledge Panel, industry directories, Schema.org authoritative markup.
Featured expert commentary in Forbes, TechCrunch, industry publications. LLMs weigh authoritative citations heavily.
Optimize for natural-language queries: 'how', 'why', 'what's the best', 'compare X vs Y'.
Which prompts mention your brand, in what context, at what position. Trend tracking across all 5 major LLMs.
We don't sell AI search as a separate package: preparing a site to be quoted by assistants is part of the SEO retainer. We take it standalone in one case only — when another vendor runs your SEO and you need the AI part.
For reference: the 2026 market prices an AI-visibility audit at $1,000–$3,000 and ongoing GEO work at $2,000–$7,000 a month. Standalone AI adaptation on our pricing page starts at $1,000/mo.
Being cited cannot be guaranteed: the answer is generated anew every time and depends on how the question is phrased.
A fixed prompt set, a regular re-run across assistants, and the raw numbers — including the cases where your niche leans on aggregators and nobody gets named.
Every recommendation backed by LLM query testing. We know what formats get cited — you don't guess.
Monthly reports show exactly which prompts cite your brand and how you rank vs competitors. No black box.
Most industries have low GEO competition today. First-movers lock in LLM authority for years.
Benchmark LLM visibility across 50-200 queries and 5+ LLMs. Competitor analysis. 6-month strategy.
GEO-content templates: definitions, FAQs, structured lists, factual density. Adapted to your niche.
Schema.org Organization/Brand/Person. Wikidata entries. Industry directory listings. Google Knowledge Panel prep.
8-15 expert pieces monthly. Each structured for LLM citation.
Expert commentary in Forbes, TechCrunch, industry publications. LLMs weight authoritative citations.
Monthly LLM visibility reports. Adjust strategy based on data — what's cited, what's not, why.
The biggest problem with this service on the market is that it gets sold without explaining how results are counted. Here is what we measure and where each metric stops being reliable.
| Metric | How we measure it | Where it breaks down |
|---|---|---|
| Share of answers mentioning the brand | A fixed prompt set for your niche, re-run on a schedule across assistants | Answers are unstable: the same question phrased differently returns different sources |
| A link to your site in the answer | Same prompt set, sources recorded each run | Not every assistant shows links, and the source mix changes |
| Referrals from assistants | A separate segment in analytics by referrer | Part of the traffic goes untagged — the real number is usually higher |
| Branded demand | Search volume for your company name | Moves slowly and not only because of AI |
| Presence in Google AI Overviews | Manual checks across a query group | Whether an AI answer shows at all depends on the query and the device |
The answer is assembled from several sources, not only your website — which is why working on the site alone delivers half the result.
Two or three sentences that answer the question completely and read on their own. Those are the fragments that end up quoted.
Prices, terms, timelines, limitations. Structured data is extracted far more reliably than a paragraph of reasoning.
FAQPage, Product, LocalBusiness, Organization — unambiguous machine-readable answers to who you are and what you sell.
A price, a lead time or a condition lives in one place and flows everywhere from there. Conflicting numbers across pages are why assistants quote outdated terms.
We check that GPTBot, PerplexityBot, Google-Extended and search crawlers aren't blocked in robots.txt. They get blocked by accident more often than you'd think.
A visible update date and maintained facts: an outdated price inside an AI answer hurts more than no mention at all.
Citation cannot be guaranteed. The answer is generated from scratch on every request and depends on phrasing, conversation history and the model version. Anyone selling a guaranteed placement in ChatGPT is selling something they don't control. What can be promised is the preparation: a site that is easy to quote accurately, consistent facts in one place, schema markup, open crawler access and external mentions. From there it either works, or it shows that in your niche the assistants lean on aggregators — and we say so plainly instead of dressing up a report.
LLMs love clear lists, definitions, FAQs. 'Beautiful' unstructured content gets ignored by algorithms.
LLMs penalize sources with errors. Every stat, date, quote verified — expertise matters.
Content by credentialed experts with LinkedIn profiles, credentials, industry recognition. Signals E-E-A-T.
LLMs analyze outbound links. Cite peer-reviewed sources, official documents, primary research.
The goal differs. In SEO we work so a person sees a link and clicks it. Here we work so an assistant takes a fact from your site and names the company in its answer, even when no click follows. Much of the technical groundwork overlaps: a healthy site, a clear structure, honest facts. The differences are direct answers at the top of sections, facts in tables, schema markup, consistent figures across the site, and open access for assistant crawlers.
No. The answer is generated from scratch on every request and depends on the phrasing, the conversation history and the model version: the same question asked two ways returns different sources. Anyone selling a guaranteed placement in ChatGPT is selling something they don't control. What can be guaranteed is the preparation and the measurement, not the output of a generative model.
We fix a prompt set for your niche — usually several dozen questions, phrased the way your buyers phrase them — and run it across assistants on a schedule. We record whether the brand is mentioned, whether a link appears, what exactly is said and whether any facts are out of date. Separately we track referrals from assistants in analytics. We report the numbers as they are, including the cases where assistants in your niche rely on aggregators and don't name vendors at all.
On its own only when another vendor runs your SEO — then we scope the work for your niche. Otherwise it's part of the retainer that starts at $1,500 a month. For reference: the market in 2026 prices an AI-visibility audit at $1,000–$3,000 and ongoing GEO work at $2,000–$7,000 a month, so this is a saving rather than an add-on.
Referrals from assistants are still modest, and promising a flood of them would be dishonest. The value sits elsewhere: your name appears at the moment of choosing, and the person who does arrive already understands your terms, so the conversation doesn't start from zero. Part of that traffic also goes untagged in analytics, so the real contribution is usually larger than what you can see.
Accurate facts: current prices and terms, limitations, the cases you don't take. An assistant retells outdated data as confidently as correct data, and a stale price inside an answer does more harm than no mention at all. We also need agreement to consolidate figures across the site: one price in one place rather than five versions in five sections.
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