AI SEO · SEO For ChatGPT
SEO for ChatGPT,
for both ways it answers.
ChatGPT replies from two very different places. Some of what it says was absorbed while the model was trained. The rest it fetches from the live web while you wait. Optimising for each one is a different job, and we do both.
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The levers that decide what ChatGPT says about you
- Web Browsing
- Search Results
- Cited Sources
- GPTBot Access
- ChatGPT-User Fetches
- Entity Clarity
- Structured Facts
- Third-Party Mentions
Our ChatGPT strategy
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01
Baseline both answers
The same questions asked with browsing on and with it off, so we know which failure we are fixing.
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02
Decide the crawler policy
GPTBot and ChatGPT-User do different jobs, so each gets a deliberate allow or block with the reasoning written down.
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03
Make a live fetch easy
Pages a browsing request can retrieve and quote in one pass, with the facts stated where they can be found.
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04
Corroborate off your domain
Independent sources repeating the same facts, because a model weighs what it can cross-check.
SEO for ChatGPT is the work of making OpenAI’s assistant describe your business correctly and cite your pages, across both the knowledge the model carries from training and the pages it fetches live when a conversation triggers browsing. It sits on top of the same crawlable, fast, well-linked foundation that organic SEO builds.
One assistant, two sources of truth
Most teams treat ChatGPT as a single black box. It behaves as two systems wearing one interface, and the fix for a bad answer depends entirely on which of them produced it.
What the model already absorbed
Training-era knowledge is broad, cheap to reach and slow to correct. It answers instantly, with no source list, and it keeps repeating whatever it learned until a later training pass sees something different.
What it fetches while you wait
When a question needs current information, ChatGPT browses. That path responds to on-page structure within a normal crawl cycle, and it is the one that produces a visible citation you can click.
The cost of being wrong is higher here
ChatGPT is the assistant most buyers reach for first. A missing or outdated answer therefore reaches more of your market than the same problem would on a smaller engine, and it reaches them before they ever open a browser tab.
Answered from training, or answered from live browsing
Before anyone writes a word of copy, work out which column you are in. The two columns have different clocks, different inputs and different repair paths.
| Answered from training | Answered from live browsing | |
|---|---|---|
| How fast it updates | Slowly, on OpenAI’s own schedule for gathering and training | Within a normal crawl and fetch cycle, so weeks rather than model generations |
| What influences it | How widely and consistently your facts appear across the open web | Whether the fetched page states the fact plainly and can be parsed in one pass |
| Which crawler matters | GPTBot, which gathers text that may feed future training | ChatGPT-User, which fetches a page on behalf of the person in the conversation |
| How you fix a wrong answer | Change what future crawls find, then get the correction repeated by independent sources | Restructure the page so the current fact is the one a fetch lands on and can quote |
| How you measure it | Ask with browsing turned off and record what the model asserts unaided | Ask with browsing on and record whether your domain appears in the source list |
| Typical failure | Confident, dated statements about pricing, staff or services you retired | A competitor page is easier to fetch and quote, so it gets the citation |
Who this is for
The work pays back fastest where a buyer forms an opinion inside a chat window before anyone at your company hears about it.
Businesses ChatGPT describes with old facts
The model states a price you stopped charging, names someone who left, or lists a service you closed. This is the characteristic failure of training-era knowledge, and correcting it means changing what future crawls see and getting the new version corroborated elsewhere.
Considered purchases researched in a chat
Software, professional services and B2B suppliers get shortlisted in conversation long before a form is filled in. If the assistant does not surface you at that moment, you never enter the comparison at all.
Sites that blocked the crawlers by accident
A robots.txt copied from a template, a firewall rule, or a bot filter added during a traffic scare. Plenty of sites have quietly shut out GPTBot or ChatGPT-User without anyone deciding to, and the first step is simply reading the logs.
Categories where a rival owns the answer
One name keeps coming back when buyers ask which supplier to use. Closing that gap is a question of evidence and repetition across sources the model reads, and it takes longer the further ahead the rival gets.
How our ChatGPT process works
Six steps, run in order. Every one of them produces something you can open and check for yourself.
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1
Baseline both modes
We put your real buyer questions to ChatGPT twice, once with browsing disabled and once with it enabled, then record what changes between the two. That difference tells us whether the problem lives in the model’s memory or in what a fetch can find today.
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2
Crawler access review
We check your robots.txt, your edge rules and your server logs for GPTBot and ChatGPT-User separately, because allowing or blocking each carries a different consequence. You get a recommendation for both, with the trade-off written down rather than assumed.
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3
Make live retrieval easy
Pages restructured so a fetch lands on the answer: headings that match the question, the current fact in the first passage rather than the fourth, and content that renders without waiting on client-side scripts.
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4
Entity clarity and structured facts
One canonical description of who you are, repeated consistently, backed by schema that states your details in a form a machine reads rather than infers. This is the layer Answer Engine Optimization depends on across every engine, and ChatGPT is no exception.
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5
Third-party corroboration
Your own site is one source. The model weighs what it can cross-check, so we work on the profiles, directories, editorial mentions and industry listings that repeat the same facts in someone else’s words.
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6
Re-run and track
The same prompt set goes back through ChatGPT every month in both modes. You see which answers moved, which citations appeared, and which change we shipped is the plausible cause. The method carries over to the wider LLM SEO programme if you run one.
What you actually receive
Artifacts your team keeps and can act on without us, handed over as we go rather than summarised at the end.
The ChatGPT baseline
- Your buyer questions written out as a fixed prompt set
- The answer with browsing off and the answer with browsing on
- The exact wording ChatGPT uses about your brand
- Which questions name a competitor instead
The crawler access report
- Current robots.txt directives for GPTBot and ChatGPT-User
- Log evidence of what each one actually reached
- Edge rules or bot filters blocking either agent
- A recommendation for each, with the consequence stated
Retrieval-ready pages
- Question-shaped headings on the pages that matter
- Current facts placed where a fetch will find them
- Schema and structured data deployed and validated
- Server-rendered content for anything a bot must read
Corroboration and monthly tracking
- Profiles and listings corrected to one canonical description
- Earned mentions that repeat your facts off your domain
- Month-on-month movement in answers and citations
- What we are doing next, and the reasoning behind it
“We started with a free strategy that showed us specific gaps in our campaigns. Today, LineUp is our regular partner, delivering a measurable return on every invested zloty.”
What clients say on Google
Unedited screenshots from our Google Business Profile. Swipe, or use the arrows, to read them all.
Read these reviews on Google. Reviews written in Polish or Turkish are shown in Google’s own translation.
Questions we get asked
What is SEO for ChatGPT?
SEO for ChatGPT is the work of making OpenAI’s assistant describe your business correctly and cite your pages. It covers two separate surfaces: the knowledge the model absorbed during training, and the pages it fetches live when a conversation triggers browsing.
Should we allow GPTBot?
That depends on what you sell. GPTBot gathers text that may be used for future training, so allowing it is how your own facts reach the model’s memory. Blocking it protects proprietary content but leaves the model relying on whatever other sites say about you.
What is the difference between GPTBot and ChatGPT-User?
GPTBot collects pages that may be used to train future models, so its effect is slow and broad. ChatGPT-User fetches a specific page during a live conversation because someone asked something that needed it. They are declared separately in robots.txt and can be handled differently.
ChatGPT quotes pricing we retired. How do we fix that?
You change what the next crawl finds. Publish the current figure on a page that states it plainly, remove the retired one from your own site, then get the same figure repeated on profiles and listings the model reads. Arguing inside the chat window changes nothing.
Can you guarantee ChatGPT will recommend us?
No. Model outputs are probabilistic, they change between versions, and nobody outside OpenAI controls them. What we commit to is making your facts easy for the assistant to retrieve and corroborated by sources beyond your own domain, then reporting honestly on what it says month to month.
How is this different from your other AI SEO work?
This page is the ChatGPT-specific version of work we also run across other assistants. Answer Engine Optimization targets the direct answer on any engine, LLM SEO covers language models generally, and this focuses on OpenAI’s crawlers and retrieval behaviour.
Find out what ChatGPT says about you today.
We will run your real questions through ChatGPT with browsing on and off, check whether GPTBot and ChatGPT-User can reach your site, and send you the baseline with the gaps ranked.
Last reviewed 28 July 2026.