There is no switch, schema property or submission form that guarantees a ChatGPT recommendation. The practical goal is to make your site eligible for discovery, easy to understand, useful for the exact question and credible enough to cite. That requires technical access, answer-ready pages, clear brand facts and evidence beyond your own marketing copy.

This is often called GEO, AEO, LLM optimization or ChatGPT SEO. The label matters less than the work. A site that blocks the relevant crawler, hides its best facts inside scripts or publishes generic claims is difficult to use as a source. A site with accessible pages, specific answers, transparent evidence and independent validation gives an answer engine something it can confidently reference.

Key takeaways

  • Allow OAI-SearchBot if you want pages to be eligible for ChatGPT search discovery.
  • GPTBot controls possible model-training use separately; it does not have to be allowed for ChatGPT search eligibility.
  • Build pages for real recommendation questions, not only short product keywords.
  • Put the direct answer, qualifications and evidence in crawlable text.
  • Make your company, product, authors, pricing and use cases consistent across the web.
  • Earn authentic third-party proof. Your own claim that you are “the best” is not independent evidence.
  • Measure citations, mentions, referral visits and conversions with a repeatable prompt set.
  • Treat AI visibility as an extension of sound SEO and brand building, not a shortcut around them.

Table of contents

Teams often combine four different outcomes under one phrase:

  1. A citation: ChatGPT search links to one of your pages as a source.
  2. A brand mention: your company appears in an answer, with or without a link.
  3. A category recommendation: your product is included when someone asks for the best tools for a use case.
  4. A navigational answer: a user asks specifically for your brand, pricing or documentation and receives a link.

These outcomes do not have a public, fixed ranking formula. Results can also change with the wording of the prompt, freshness of the underlying sources, location and product experience. Anyone selling a guaranteed “number-one ChatGPT position” is promising control they do not have.

The controllable work sits in three layers:

LayerQuestionWhat you can improve
EligibilityCan the search system access and use the page?crawler rules, status codes, rendering, canonicals
RelevanceDoes the page directly answer the prompt?page type, headings, entities, comparisons, examples
ConfidenceIs the answer supported and corroborated?sources, first-party proof, authorship, independent mentions

1. Allow the right OpenAI crawler

OpenAI documents separate user agents for separate purposes. The distinction is important.

  • OAI-SearchBot is used to surface websites in ChatGPT search results. OpenAI says sites that opt out will not be shown in ChatGPT search answers, although a navigational answer may still show a link.
  • GPTBot is used for content that may help improve generative AI foundation models. It can be allowed or disallowed independently.
  • ChatGPT-User is used when a person asks ChatGPT to visit a page. It is not an automatic crawler and does not determine whether a page is included in search.

If your policy is to permit search discovery but decline training access, the rules can be separated:

User-agent: OAI-SearchBot
Allow: /

User-agent: GPTBot
Disallow: /

Do not paste this blindly into production. A later wildcard rule, CDN bot policy or web application firewall may still block access. Test the final file with Bora's robots.txt tester, check the live response and review server logs. OpenAI notes that a robots.txt change can take about 24 hours to be reflected.

Crawler access is only eligibility. It does not guarantee selection or citation.

2. Make the useful answer technically retrievable

An elegant interface is not enough if the underlying information is hard to fetch. Give each important topic a stable, canonical URL that returns a normal 200 response and exposes its main content as text.

Check the basics:

  • the page is not blocked by robots.txt;
  • a noindex directive is not present by accident;
  • the canonical points to the intended URL;
  • essential copy is available without a login, form submission or complex interaction;
  • headings and links exist in the rendered HTML;
  • internal links connect the page to its category, product and supporting evidence;
  • the XML sitemap contains canonical, indexable URLs;
  • security tooling does not challenge legitimate crawlers indefinitely.

JavaScript is not automatically a problem, but relying on client-side actions for every meaningful sentence creates unnecessary failure points. Server-rendered or statically rendered key content is the safer default.

Use the SEO checker for an initial page review and the sitemap checker to catch discovery problems. Then verify with real server logs rather than assuming a green tool result proves that every crawler was served correctly.

3. Create pages for recommendation-shaped questions

Traditional keyword plans often stop at category terms such as “SEO automation software”. AI users ask longer, more conditional questions:

  • What is the best SEO automation tool for a two-person SaaS team?
  • Which platform can publish to WordPress without manual formatting?
  • What is a Soro alternative for multilingual sites?
  • Should I automate an existing blog or create a new one?
  • Which tool includes images, internal links and schema in one workflow?

One generic homepage cannot answer all of these well. Build a deliberate set of page types:

  • use-case pages for a defined audience and job;
  • integration pages such as Bora for WordPress;
  • transparent comparison and alternatives pages such as Bora vs Soro;
  • pricing and plan explanations;
  • implementation guides;
  • troubleshooting and limitation pages;
  • original case studies and benchmarks.

Each page should resolve a distinct decision. Avoid producing dozens of doorway pages where only the industry or city name changes. A smaller page set with genuine differences is more useful and easier to maintain.

4. Write answer-first, evidence-rich sections

AI answers often need a compact passage that can stand on its own. This does not mean writing unnatural fragments for machines. It means respecting the reader's time.

A strong section usually follows this sequence:

  1. State the answer in one or two sentences.
  2. Define when it applies.
  3. Provide evidence, a method or an example.
  4. Explain the limitation or trade-off.
  5. Link to the deeper proof.

Compare these two claims:

Bora is the best SEO automation platform.

That is promotional and unsupported.

Bora is designed for teams that want keyword research, drafting, images, internal links, schema and CMS publishing in one workflow. It supports more than 40 languages; teams that need a manual editorial marketplace may prefer a different category of product.

The second passage identifies a use case, lists verifiable capabilities and acknowledges a boundary. It is more useful to a buyer and easier for another system to summarize accurately.

Use descriptive H2s, short definitions, comparison tables and numbered processes when they improve understanding. Do not manufacture “quotable” statistics. If you make a numerical claim, show the source, sample, date and method.

5. Establish a clear brand and product entity

Recommendation systems need to distinguish your company from similarly named products and understand what it does. Keep core facts consistent across the homepage, pricing, documentation, author profiles, social profiles and reputable third-party listings.

At minimum, make the following explicit:

  • official company and product name;
  • one-sentence category and value proposition;
  • primary website and contact route;
  • supported platforms, languages and regions;
  • current pricing date and plan boundaries;
  • named founders, authors or reviewers where appropriate;
  • relationships between the organization, software product and published articles.

Relevant structured data can reinforce those visible facts. Organization, SoftwareApplication, Person and BlogPosting may be appropriate when their required information is present. Schema does not force ChatGPT to cite a page, and markup must match what users can see.

Run candidate markup through Bora's schema generator, then validate it before deployment.

6. Earn corroboration beyond your own domain

A recommendation is stronger when product claims are confirmed by sources that are not controlled by the vendor. Useful signals can include:

  • detailed customer case studies with permission;
  • independent reviews that describe an actual workflow;
  • expert roundups with a disclosed evaluation method;
  • partner and integration directories;
  • podcasts, conference notes or interviews;
  • public product documentation and changelogs;
  • original research cited by other publishers.

The goal is not to seed identical promotional language everywhere. It is to build a real record of use and expertise. Do not fabricate reviews, manipulate community threads or add yourself to Wikipedia without meeting its policies. Those tactics create reputation risk and weak evidence.

For Bora, a credible proof asset could show the publishing pipeline used, sample period, pages published, indexation pattern and conversion outcome. It should also disclose limitations such as domain age, promotion and editorial review.

7. Publish information competitors cannot cheaply copy

Generic summaries have little defensive value. The most useful source is often the page with evidence closest to the event.

Strong assets include:

  • an anonymized analysis of failed automated publishes;
  • an original comparison of CMS API limitations;
  • a benchmark with a reproducible method;
  • before-and-after screenshots with dates;
  • a checklist created from real support issues;
  • a pricing model with explicit assumptions;
  • an honest explanation of when the product is not a fit.

Bora already has this direction in what breaks when AI publishes daily and its article-cost analysis. Turn those first-hand observations into connected topic clusters rather than isolated posts.

8. Keep source facts fresh

Outdated pricing, integrations and product descriptions can lead to inaccurate answers. Assign an owner and review interval to every commercial page.

A practical process is:

  1. Record the claim, source and last verification date.
  2. Review fast-changing pages monthly or quarterly.
  3. Update the visible “last reviewed” date only after a real check.
  4. Redirect retired URLs to the closest useful replacement.
  5. Preserve a changelog for important product facts.

Automation can flag drift, broken links and stale dates. A person should review consequential claims and competitor comparisons.

9. Measure AI visibility with a repeatable prompt set

Do not judge progress from one impressive screenshot. Create a fixed set of prompts across four groups:

  • category discovery;
  • use-case recommendations;
  • competitor alternatives;
  • branded product questions.

Record the model or surface, date, prompt, whether Bora appeared, whether it was linked, the cited source URL, the position or prominence within the answer and whether the description was accurate. Repeat the test on a stable schedule. Results remain directional because answers can vary.

Then connect visibility to business outcomes:

  • referral sessions from ChatGPT or related sources;
  • landing pages reached;
  • signup and demo conversion rates;
  • assisted conversions;
  • branded search growth;
  • citations earned by original research pages.

The detailed framework in how to measure AI search visibility turns these signals into a usable dashboard.

What Bora can automate—and what it cannot

Bora can help build the on-site publishing system: keyword research, briefs, drafts, images, internal links, schema, multilingual content, CMS delivery and ongoing reporting. That removes repetitive work and makes topic coverage consistent. See how Bora works and the full feature overview.

It cannot manufacture genuine customer experience, independent reputation or a guaranteed recommendation. Those require a useful product, real users, credible experts and honest promotion. The best operating model combines automation for repeatable production with human ownership of evidence, positioning and review.

A 30-day ChatGPT visibility action plan

Week 1: establish eligibility

  • Inspect robots.txt for OAI-SearchBot and GPTBot rules.
  • Check CDN/WAF logs and allowlists.
  • audit canonicals, status codes, sitemaps and rendered content.
  • Create a baseline of current citations and referrals.

Week 2: repair entity clarity

  • Standardize product and organization facts.
  • Add real author/reviewer profiles.
  • Align visible content and structured data.
  • Correct outdated pricing and integration claims.

Week 3: publish recommendation assets

  • Build one use-case guide.
  • Build one transparent comparison page.
  • Publish one original evidence asset.
  • Link all three to the relevant product and documentation pages.

Week 4: distribute and measure

  • Share the evidence with relevant partners and customers.
  • Request genuine feedback, not scripted praise.
  • Re-run the fixed prompt set.
  • Review referrals, conversions and source-page performance.

Frequently asked questions

Can I submit my website directly to ChatGPT?

There is no public submission that guarantees inclusion or a recommendation. Make the site accessible to OAI-SearchBot, publish useful pages and earn credible references.

Should I allow GPTBot?

That is a separate policy decision about possible model-training use. OpenAI documents GPTBot and OAI-SearchBot independently, so a site can allow search discovery while disallowing GPTBot.

Does schema make ChatGPT recommend a product?

No. Accurate structured data can clarify entities and page meaning, but it is not a recommendation switch.

How long does ChatGPT SEO take?

There is no fixed timeline. Technical eligibility can be corrected quickly, while reputation, original evidence and third-party corroboration normally take sustained work.

Final checklist

  • [ ] OAI-SearchBot is not unintentionally blocked.
  • [ ] CDN and WAF rules permit legitimate requests.
  • [ ] Important answers exist as crawlable text on canonical URLs.
  • [ ] Use-case, comparison, pricing and documentation pages answer distinct questions.
  • [ ] Every important claim has evidence, a source or a clear limitation.
  • [ ] Product, company and author entities are consistent.
  • [ ] Independent mentions are authentic.
  • [ ] A fixed prompt set and conversion measurement process are active.

AI recommendation visibility is not won by adding more hype. It is earned by becoming a source that is accessible, relevant, specific and trustworthy. If maintaining that system manually is slowing the team down, compare Bora plans and automate the repeatable parts while keeping human judgment where it matters.

Sources and freshness notes

  • OpenAI crawler documentation — crawler purpose, robots.txt controls and IP guidance; reviewed 4 September 2026.
  • Recheck crawler names and policy language before publication because platform documentation can change.

Editorial implementation notes

  • Replace the suggested author with a real person and link to a verifiable author page.
  • Add a screenshot of the current robots.txt test and a dated crawler-log example if available.
  • Verify every product capability and pricing statement on publication day.
  • Use BlogPosting JSON-LD; do not add unsupported FAQ markup solely for rich results.