How to Rank on ChatGPT in 2026: Get Your Business Recommended by AI (8-Step GEO Tutorial)
Summary
Noxen Digital, an SEO, GEO and web design agency based in Istanbul, published a YouTube tutorial on getting a business mentioned by ChatGPT, Gemini, Perplexity and Google AI Overviews. It sets out an 8-step checklist. The steps are: let AI crawlers through robots.txt and CDN or firewall settings, get indexed in Google Search Console and Bing Webmaster Tools with IndexNow turned on, state plainly what the business does and who it serves, back pages with facts and sources, add Organization or LocalBusiness schema with sameAs, earn third-party mentions and reviews, and check results each month with a prompt sheet and GA4 referrals from chatgpt.com.
The item's canonical reference is OpenAI's first-party crawler documentation. That documentation is the primary source for the OpenAI crawler names the tutorial tells site owners to allow. The rest of the checklist is the agency's own recommended practice.
Demonstration by Noxen Digital, embedded from YouTube. AIOTruth did not reproduce the test.
Why it matters
Most of the checklist is advice. The crawler step is a hard gate. A site that blocks OAI-SearchBot or GPTBot in robots.txt, or whose CDN or firewall rejects them at the bot layer, can be left out of what ChatGPT retrieves, however good its content is. Many owners have never checked those settings, because firewall rules are often set by a hosting or security vendor and never reviewed for AI access. The tutorial also frames measurement as prompts plus referral traffic from chatgpt.com. That gives a business a way to see whether AI systems send visitors at all, instead of assuming its search rankings carry over.
Source
- developers.openai.com/api/docs/bots the item itself, published by Noxen Digital, created by Noxen Digital
- github.com/openai/openai-cookbook Public source code or repository
- noxendigital.com/blog/geo/what-is-schema-markup-structured-data-seo-geo-guide Reputable reporting
- noxendigital.com/blog/geo/google-ai-overviews-how-to-get-cited-in-ai-generated-answers Reputable reporting
- youtube.com/watch?v=cHChYp5BUkMwhere AIOTruth found it
What was checked
- canonical URL taken from the page itself
- read the item page (200)
- https://github.com/openai/openai-cookbook: supports the item, tier 6 (Public source code or repository)
- https://noxendigital.com/blog/geo/what-is-schema-markup-structured-data-seo-geo-guide: supports the item, tier 9 (Reputable reporting)
- https://noxendigital.com/blog/geo/google-ai-overviews-how-to-get-cited-in-ai-generated-answers: supports the item, tier 9 (Reputable reporting)
- https://developers.openai.com/api/docs/bots: supports the item, tier 1 (Official platform documentation)
- https://developers.openai.com/api/docs/bots: supports the item, tier 1 (Official platform documentation)
- https://noxendigital.com/contact: does not mention the item, tier 9 (Reputable reporting)
Limitations
- The demonstration was not independently reproduced by AIOTruth.
AIOTruth judgment
The item scores high on relevance and evidence. Its core technical claim, which crawlers OpenAI runs and how site owners control them, rests on OpenAI's own documentation, and that supports the Confirmed evidence status. Usefulness is strong because every step can be acted on and checked by a site owner. Originality is lower because most of the checklist repeats established search and structured data practice under a GEO label. Two sources are the publisher's own blog posts, and the video is also a marketing asset for the agency's services. AIOTruth did not reproduce the demonstration, so the claims about how each AI system picks which businesses to mention are the publisher's account.
How this score was calculated
| Dimension | Weight | Score | What produced it |
|---|---|---|---|
| AIO relevance | 30% | 10 | geo, ai visibility, ai search, generative engine optimization, ai overviews; 5 scope question(s) matched |
| Usefulness | 30% | 8 | 4 artifact(s), 6 actionable marker(s), 0 measured figure(s) |
| Evidence | 25% | 10 | Official platform documentation; 4 verified source(s) across 3 domain(s) |
| Originality | 15% | 7 | no original testing found; closest archive match 0 |
aioRelevance x 0.30 + usefulness x 0.30 + evidence x 0.25 + originality x 0.15. The rubric is published in full on the Editorial Method page. Scoring is deterministic: the same item scores the same on every run.
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