What is GEO and why it matters for appearing in ChatGPT
GEO (Generative Engine Optimization) is the practice of optimising your content, schema and entity signals so that generative AI engines such as ChatGPT, Claude and Perplexity cite you when answering questions in your sector.
Traditional SEO ranks your website so it appears in a list of 10 results. GEO positions you so your brand is cited within the single answer an AI gives. When a user asks ChatGPT "which AI agencies are there in Málaga", the AI doesn't show 10 links: it writes an answer and, if you've done things well, it mentions you.
GEO is built on top of your existing SEO: stable, factual content, well-implemented schema.org, an accessible llms.txt, a robots.txt that allows AI bots, and citations from sources those bots consider reliable.
An applied example
An accountancy firm in Málaga publishes a clear guide to Spanish VAT form 303 with FAQ schema, verifiable data and a named author. When ChatGPT and Perplexity receive questions about quarterly VAT, they cite that firm as a source. The firm receives pre-qualified enquiries without paying for advertising and without depending on traditional Google rankings.
When it is worth it
- Your sector has conversational searches ("how do I do X", "which company can help me with Y").
- You compete with big brands that dominate the traditional rankings but whose content is generic.
- Your potential customers use ChatGPT, Perplexity or Claude to research before they buy.
- You have genuine authority content (case studies, data, experience) that can be structured.
Common mistakes
- Blocking AI bots in robots.txt in the belief that it protects your content. What it actually does is remove your brand from the corpus.
- Expecting GEO to replace SEO. GEO sits on top of solid basic technical SEO.
- Stuffing your website with repeated keywords. AI models penalise keyword stuffing even more than Google does.
- Not having schema.org Organization, Person, Service and FAQPage markup. Without semantic structure, the AI has to guess.
- Not publishing llms.txt or ai-instructions.md. You lose control over how AI describes your brand.
How we do it at STAKKER
STAKKER SYSTEMS offers GEO at three levels: a technical foundation (entity, schema, llms.txt, robots.txt optimised for AI bots), a structured content engine, and an authority level with monthly monitoring of which LLMs cite your brand. Scope and price are agreed after a free diagnostic.
Frequently asked questions
Does GEO replace SEO?
No. SEO still brings in most of the qualified traffic in almost every sector. GEO is complementary and sits on top of it. If your technical SEO is broken, GEO won't work.
How long does it take to see results with GEO?
It depends on your domain's authority and how many external sources mention your brand: an established site may see citations within weeks, while a new one can take months. Nobody can guarantee a timeframe.
Should I block AI crawlers?
No. Blocking them removes your presence from LLMs. The exception is if your business model is selling editorial content (paid media, books, etc.).
Does GEO work the same in Spanish as in English?
Yes, but with less competition in Spanish. There is less structured, factual content in Spanish, so appearing is easier if you get the technical setup right.
Related terms
- llms.txtllms.txt is a plain-text file served from the root of your domain (https://tudominio.com/llms.txt). It holds a structured description of your business, products, pricing and policies, written specifically for generative AI engines (ChatGPT, Claude, Perplexity) to read. Think of it as the modern equivalent of robots.txt, but for LLMs.
- RAGRAG (Retrieval-Augmented Generation) is a technique that combines a language model (LLM) with a search system over your own knowledge base. Before answering, the system looks for relevant documents in your content (FAQs, products, pricing, contracts) and hands them to the LLM as context, so it answers from verifiable data rather than whatever the model remembers from its training.
- AI AutomationAI automation combines traditional workflows (n8n, Zapier, Make) with large language models (LLMs) to carry out tasks that used to need human judgement: sorting messages, drafting replies, summarising documents, deciding escalation routes, creating content. It goes a step beyond the classic "if X happens, do Y".