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chatgpt recommends competitors, not you
Generative engine optimization services (GEO)
from $250Generative engine optimization services that get your site read, quoted and recommended by AI Overviews, ChatGPT, Perplexity and Gemini. Measured, not claimed.
What's included
- AI crawler access audit across GPTBot, ClaudeBot, PerplexityBot, and Google-Extended
- robots.txt reviewed so you are not blocking the engines you want to be cited by
- llms.txt written and kept in sync with the site
- Pages restructured so answers are extractable, not buried in preamble
- Entity and author signals so the engines know who is talking
- Structured data that supports citation, not just rich results
- A baseline of where you are mentioned now, so the change is measurable
Price
Includes the crawler access audit, the structural work, and a mention baseline you can measure against later. Ongoing monitoring is quoted on top.
There is a second index now. When somebody asks ChatGPT which tool to use, or Google answers in an AI Overview without a click, a set of sources gets picked and yours is either in it or it is not. Most sites have never checked which.
It starts where technical SEO starts
The work is less exotic than the label suggests. Answer engines still need to fetch the page, still need to parse it, and still need a reason to quote you rather than the site next to you. So the first questions are the old ones: is the crawler allowed in, does the page render without JavaScript doing the work, is the answer near the top or three scrolls down.
This is where most of the cheap wins are. Sites block GPTBot, ClaudeBot or PerplexityBot without knowing it, because a security plugin default or a bot-protection rule did it for them, and then wonder why they are never cited. That is an access problem wearing the costume of a visibility problem, and it is fixable in an afternoon.
Where it genuinely differs
Extraction. A search engine ranks a page. An answer engine lifts a passage and attributes it. That changes how a page should be written: questions as headings, the answer in the first two sentences under each one, one idea per paragraph, claims specific enough to be worth repeating, and sourcing that makes you safe to cite.
The useful part is that none of this trades against normal SEO or against readability. A page built to be quoted is the same page a reader in a hurry wanted. There is no version of this work that makes your site worse for humans, which is not something you can say about every tactic sold under this heading.
What it will not do
It will not manufacture authority you do not have. Engines quote sources that say something specific, and a page of general advice about your industry is exactly what a model can already produce without you. The sites that get cited are the ones with a number, a method, a constraint or a result that had to come from doing the work.
So if the honest state of the site is that it has nothing distinctive on it, this is content work before it is optimization work, and I will say so rather than sell the smaller job.
Run in public, on my own site
I am running this method on this site, out loud. It started at zero mentions across every engine, which is where most sites start, and what I do about that gets written up in the AI search posts as it happens, including the parts that do not work.
If you are comparing quotes, what generative engine optimization services actually do is the buying guide, including the questions worth asking me. If you want the method rather than the service, AI search visibility defines what is being measured, gives the baseline procedure, and says what moves the number and what does not. How to track brand mentions in AI search is the measurement half on its own. Read them and run it yourself if you would rather not hire anyone.
This pairs with technical SEO, because a page an AI crawler cannot fetch is not an optimization problem, it is an access problem.
Tell me your market and I will run the baseline before quoting anything.
- step 1 · baselineI check what the engines say about you today, across AI Overviews, AI Mode, ChatGPT, Perplexity, and Gemini, and record it. Most sites start at zero mentions, which is the number worth knowing before you spend anything.
- step 2 · fix accessThe cheapest wins are usually blocking faults. Sites regularly block the crawlers behind the assistants they want to appear in, without knowing it. That gets audited and fixed first.
- step 3 · make pages quotableAnswer engines lift passages, not pages. Headings become real questions, answers move to the top, claims get sourced, and the structure stops burying the thing you want quoted.
- step 4 · re-measureThe same queries get run again later against the same baseline. The measurement is the point: this field is full of confident claims and short of evidence.
before you ask
Common questions.
Is this different from normal SEO?
It overlaps at the crawl layer and diverges after. Both need the page reachable and readable. But an answer engine lifts a passage and cites a source, where a search engine ranks a page, so structure, sourcing, and how directly you answer the question matter more than they do in classic SEO.
Can you guarantee ChatGPT will recommend my site?
No, and treat anyone who does as a warning. Nobody controls an answer engine's output. What can be controlled is whether your site is reachable, readable, structured for extraction, and specific enough to be worth quoting. That is the work. The measurement afterwards is honest about what moved.
Should I block AI crawlers instead?
That is a real choice and it depends on your business. A publisher losing traffic to a summary has a case for blocking. A service business that wants to be recommended does not. The mistake worth avoiding is blocking by accident, which is common, because a plugin default or a security rule quietly did it for you.
What is llms.txt and does it actually do anything?
It is a plain text file listing your important pages for language models, the way robots.txt lists rules for crawlers. No engine is obliged to read it, so treat it as cheap and low risk rather than as a lever. It costs an hour and it cannot hurt you. Access, structure, and specificity are what carry the weight.
How do you measure whether any of this worked?
A fixed set of buying questions from your market, run against each engine before the work and again after, with the answers recorded rather than summarised. What gets counted is whether you were named and whether a page of yours was cited, which are two different outcomes and worth separating. It is a small sample and it is not a rank tracker, so it is reported as what it is: repeated observation, with the queries listed so you can run them yourself and get the same answer.
Is it too early to spend money on this?
For the access half, no, because that half is nearly free and the downside of being blocked is total. Checking whether your robots.txt is turning away the crawlers behind the assistants takes minutes and occasionally turns out to be the entire problem. For the rest, it depends on whether your buyers ask assistants before they buy. In some markets they clearly do and in others nobody has started, so the baseline in step one exists partly to tell you whether to keep going.
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