Concept
GEO vs SEO: differences, overlaps, and what to prioritise
SEO and GEO are not the same discipline with different names. They share techniques, but optimize for different results - and confusing the two is the reason why many brands well positioned on Google remain invisible on ChatGPT.
What changes between SEO and GEO
SEO optimizes to appear on a search engine results page (SERP) - a list of links that the user must click to get the answer. GEO optimizes to be cited within an AI-generated response - the user already receives the information, and the only question is whether your brand is part of that response.
This difference changes everything that follows: how you measure success, what you optimize, and how predictable the outcome is.
Direct comparison
| Dimension | SEO | GEO |
|---|---|---|
| Where you appear | Search results pages (SERPs) | AI-generated answers |
| How you are evaluated | Ranking by position (1st, 2nd, 3rd...) | Mentioned or not mentioned |
| What the user sees | List of links to click | Direct answer, with or without your brand |
| How it is measured | Rank tracking tools (actual position) | Systematic prompts and output analysis |
| Determinism | High - ranking is consistent | Low - LLMs are not deterministic |
| What do you optimize | Backlinks, on-page, speed | Entity clarity, authority, structure for RAG |
| Result horizon | Weeks to months | Months (model retraining cycles) |
Where SEO and GEO overlap
Not everything is different. A set of technical fundamentals serves both disciplines at the same time, and this is usually where it makes sense to start:
- Clear heading structure (H1–H3) - helps both Google and AI crawlers map content.
- Content that directly answers questions - good for featured snippets and good for citation in LLMs.
- Structured data (Schema.org) - used by both to understand entities, services, and context.
- Speed and technical accessibility of the site - prerequisite for any form of indexing.
- External authority (mentions, quality backlinks) - signal of trust shared by both systems.
The non-overlapping part is where most strategies fail: optimizing for traditional SEO alone leaves LLMs' organic knowledge layer - what the model "knows" about your brand without research - completely unworked.
What to prioritize first
If your brand already has reasonable technical SEO, the next step isn't abandoning SEO - it's adding the layers that traditional SEO doesn't cover:
- Entity clarity - can the LLM unambiguously identify what the brand does and for whom, without ambiguity?
- Ficheiros de instrução para IA (
llms.txt,ai.json) - orientam diretamente os crawlers de modelos de linguagem. - Content that resists being summarized - if an LLM can quote you accurately from a single paragraph, that paragraph is well written for GEO.
- Data consistency across platforms - identical name, address, description everywhere prevents conflict in how models represent you.
If you don't already have solid technical SEO, start there - the overlapping foundations (structure, schema, speed) support both disciplines at the same time, so there's no wasted work.