Why your B2B SaaS does not appear in ChatGPT

Schema.org is the vocabulary that describes, in machine-readable code, what each page is. Language models read schema before they read human text. Without schema, the site is literally less legible to the AI than it is to a human.

Most Portuguese B2B SaaS sites have minimal schema (a simple Organization, perhaps), but fail in three areas:

• Service schema for each service offered
• FAQPage schema on pages with questions and answers
• Article schema with author, datePublished and dateModified on every blog article

Action: audit the current schema at validator.schema.org. If only Organization shows up and nothing else, there is work to do.

llms.txt is a file at the root of the site, in Markdown, that describes the company in language optimised for models. It is still an emerging convention, but Anthropic, Mistral and several other large companies have adopted it.

Without llms.txt, AI crawlers have to guess your site's structure through HTML. With a well-made llms.txt, they get a curated summary, with a clear hierarchy of your most important pages.

Action: create /llms.txt at the root. Basic structure:

# Company name
> Description in one sentence

## Services
- [Service 1](URL)
- [Service 2](URL)

## Resources
- [Blog](URL)
- [Case studies](URL)

Language models prefer to cite content with specific characteristics: clear definitions in the first 100 words, structured lists, explicit FAQs, hierarchical headers.

Your current blog articles probably follow the human logic of classic SEO: emotional hook, build-up of context, main point halfway through. That structure is terrible for AI citation. The models extract badly and cite little.

Action: rewrite your 5 to 10 most relevant articles with this structure: citable summary, key takeaways, structured body, FAQ, sources.

The models do not cite only on the basis of your site's content, they also cite on the basis of how many credible external sources reference you. Wikipedia, credible software comparison sites (G2, Capterra), sector publications, academic papers: those are sources the models weigh heavily.

If your company is not on G2 with recent reviews, has no entry (or a poor entry) on Wikipedia, and is not mentioned in Portuguese and European sector publications, the external signal is missing.

Action: audit your presence on G2, Capterra and Wikipedia. Identify 3 to 5 relevant sector publications. Build a sustained editorial relationship, not a one-shot.

Counter-intuitive as it may seem, classic SEO still matters for GEO. Models with active web search (ChatGPT with browsing, Perplexity, Gemini with Google) go to Google's top 10 for sources to answer with. If you are not in the top 10 on the key queries, you will hardly be cited.

Action: identify the 20 queries that matter for your brand. Check your current position. If you are outside the top 10, there is classic SEO work to do before GEO bears fruit.