What is GEO? Understanding Generative Engine Optimisation

GEO — Generative Engine Optimisation — is the set of practices that allow a site, brand, or piece of content to appear and be cited in responses generated by artificial intelligence engines: ChatGPT, Perplexity, Google AI Overview, Claude, Bing Copilot, and their successors.

If SEO aims to rank in classic search results, GEO aims to be the source that AI cites when someone asks a question. That's a fundamental difference — and a brand-new discipline in its own right.

Why Has GEO Become Essential?

In 2023-2024, several shifts changed the online search landscape:

• Google deployed AI Overviews (formerly Search Generative Experience) in its results. For tens of millions of queries, an AI-generated answer now appears before any organic result.
• ChatGPT launched web search (ChatGPT Search), letting users search and get answers citing real sources.
• Perplexity AI established itself as an AI search engine with citations, surpassing 100 million active users in 2024.
• Claude, Mistral, Gemini and other LLMs increasingly incorporate web search into their responses.

Result: a growing share of informational searches — "how to do X?", "what is Y?", "what's the best Z?" — is now resolved directly by AI, without a click to any site.

For content creators and businesses, this raises an existential question: if AIs answer instead of sites, how do you stay visible?

How Do AI Engines Choose Their Sources?

Understanding this mechanism is the key to GEO. Unlike SEO (where the algorithm is partially known and documented), LLM functioning is more opaque. But we can identify general principles:

Training Data

LLMs like ChatGPT or Claude were trained on vast text corpora — books, articles, web pages. Content that existed before the training cutoff date is potentially integrated into the model's knowledge.

This means: high-quality, well-structured content, frequently cited in other texts, has a higher chance of being incorporated — and being "recalled" in responses.

Real-Time Web Search

When an LLM performs a web search (Perplexity does this systematically, ChatGPT Search too), it selects sources from search results. SEO therefore remains the foundation: if you're not crawlable and indexed, LLMs won't find you.

But among indexed sources, the AI performs an additional qualitative selection: it prefers content that is clear, structured, factual, and sourced.

Perceived Reliability

LLMs place more trust in sources that appear authoritative: institutions, recognised researchers, sites with a strong editorial identity. This is the AI equivalent of E-E-A-T.

The 6 Levers of GEO

Here's what GEO experts do to optimise their presence in AI responses:

1. Factual and Verifiable Content

LLMs prefer content with precise data, dates, and sourced statistics. "Voice search accounts for 27% of global mobile queries (source: Statista, 2024)" — this type of formulation is more citable than a vague assertion.

2. Clear Structures and Direct Answers

AI engines look for direct answers to questions. Text organised with H2/H3 headings and a short answer at the start of each section (what we call the "Featured Snippet position") is more easily extracted and cited.

3. Entities and E-E-A-T

Clearly associating content with a real person, with verifiable expertise, strengthens credibility. A well-filled author page, a Wikipedia presence, mentions in recognised publications — all of this builds your "entity" in LLMs' eyes.

4. Schema.org Markup

Even if LLMs don't directly read schema.org like Google does, a well-marked-up page will be better understood by the search engine crawlers that feed LLMs. FAQPage, Article, Person, Organization — these tags aid semantic clarity.

5. Being Cited by Others

LLMs often rely on consensus: if several independent sources say the same thing and cite each other, the probability of inclusion in a response increases. Quality backlinks remain useful — not only for SEO but also for building this citation network.

6. Presence in Forums and Discussions

Perplexity and other LLMs crawl Reddit, Quora, and specialist forums. An active and documented presence in discussion spaces of your niche can generate direct citations in AI responses.

GEO vs SEO: Do They Need to Coexist?

The answer is yes — and in fact, they reinforce each other. Here's how:

Dimension	Classic SEO	GEO
Target	Google algorithm	LLMs (ChatGPT, Perplexity, AI Overview)
Result	Position in SERP	Citation in AI response
Common foundation	Quality content, indexation, authority	Quality content, indexation, authority
Key difference	Technical optimisation, backlinks	Semantic clarity, factuality, entities

Good SEO practices (deep, structured, well-marked-up content with quality backlinks) are the necessary condition for GEO. You can't succeed at GEO with a poorly-ranked site. But succeeding at SEO no longer guarantees being cited by AIs.

How to Measure Your GEO Presence?

This is still a developing field. Dedicated GEO tracking tools are recent and imperfect. Some approaches:

• Directly interrogate LLMs: ask ChatGPT, Perplexity, Claude questions about your sector and see if you're mentioned
• Semrush AI Tracking: a tool in development for measuring AI citations
• Brandwatch / Mention: to detect mentions of your brand, including in screenshots of AI responses shared on social media

Next Steps: Deepening Your GEO Understanding

If this approach interests you, explore our complete guide to AI search and GEO as well as our comparison of SEO vs GEO to understand how to coordinate both strategies.

And if you want an expert to evaluate your current visibility in AI engines and propose an optimisation plan, get in touch — it's one of my specialties at iZZi.

Also practise navigating between SEO and GEO decisions in our SEO strategy simulator.

---

Article written by Alexandre De Sousa, SEO & GEO consultant, founder of iZZi. Last updated: May 2026.