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What is GEO (Generative Engine Optimization), and why is it changing SEO?

Summarize this article with:

GEO, or Generative Engine Optimization, is the discipline of optimizing your site so it appears in AI-generated answers from tools like ChatGPT, Perplexity, Gemini, and Claude. Sandro, co-founder of the agency Gemeos, walks you through this complete guide to how GEO works, how it differs from classic SEO, and how to apply it in practice starting today.

What exactly is GEO?

Traditional search engines like Google and Bing show a list of links. AI engines like ChatGPT, Perplexity, and Gemini generate a synthesized answer directly, sometimes citing sources. GEO is the set of techniques that increase the likelihood your content will be used as a source in those generated answers.

Unlike SEO, which optimizes for clicks, GEO optimizes for citations. The goal is no longer to rank #1 on Google, but to be the source the model chooses to cite when someone asks a question in an AI chat.

  • SEO: you want the user to click your link in the results
  • GEO: you want the AI model to include your content in its answer
  • The two aren’t opposites: strong SEO content is often a great starting point for GEO

good to know

GEO doesn’t replace SEO. It complements it. In 2026, both disciplines coexist: Google still dominates direct traffic, but the share of searches resolved inside AI interfaces keeps growing every quarter. Ignoring GEO means missing a growing share of visibility.

How LLMs choose their sources

To optimize your content, you first need to understand how large language models (LLMs) select the information they use.

LLMs are trained on massive corpora of web text. They don’t index pages in real time like Google: they learn language patterns and store associations between concepts. But some tools like Perplexity or ChatGPT Search also run real-time web searches before generating their answer.

In both cases, several criteria influence the likelihood of being cited:

  • The clarity and information density of the content: LLMs favor pages that answer a specific question directly
  • The semantic structure: clear headings, lists, definitions, and tables make information easier to extract
  • Domain authority and how often other sources cite you
  • The presence of numerical data, verifiable facts, and precise definitions
  • Consistency between the page content and metadata (Schema.org, meta tags)
Criteria Classic SEO impact GEO impact
Inbound backlinks Very strong Moderate
Clear semantic structure Strong Very strong
Numerical data and precise facts Moderate Very strong
Explicit definitions Moderate Strong
Structured Schema.org markup Strong Strong
Load speed Very strong Low
Conversational content (Q&A) Moderate Very strong
Domain authority Very strong Strong

{usecases}

The 6 pillars of a GEO strategy

Here are the concrete levers to pull to improve your visibility in AI answers.

1. Structure content as direct answers

LLMs look for answers, not articles. Structure each page around one clearly stated main question, and answer it in the first few lines. Use H2 and H3 headings that are themselves questions or precise statements ("What is X," "How to do Y," "Why Z matters").

Use the "definition + explanation + example" format for each key concept. That’s exactly what an LLM extracts and rewrites in its response.

2. Add numerical data and verifiable facts

LLMs strongly prefer content that includes statistics, percentages, dates, and sourced claims. These elements increase the model’s "confidence" in your content.

Explicitly cite your sources in the text ("According to a study by [source], X% of..."). Even if you can’t source everything, add concrete data instead of vague phrasing.

3. Implement Schema.org structured data

Schema.org markup remains a strong signal for both Google and AI engine crawlers. The most useful types for GEO are:

  • FAQPage: for Q&A pages, the ideal format for AI answers
  • Article / BlogPosting: for your blog posts and guides
  • HowTo: for step-by-step tutorials
  • Organization: for your About page and company information
  • Product / Service: for your service pages

4. Create an llms.txt file

The llms.txt file is the equivalent of robots.txt for LLMs. It tells AI crawlers which pages on your site are most relevant to index, and in what order. Adoption is still emerging, but the main crawlers (Anthropic, OpenAI, Perplexity) are starting to read it.

See the dedicated guide: How to add an llms.txt file to your Webflow site.

5. Optimize strategic pages for LLMs

Some pages have more GEO impact than others. In order of priority:

  • About page: LLMs use it to understand who you are and what you do. It should be factual, precise, and backed by concrete data (founding date, number of clients, areas of expertise, location)
  • Service pages: each service should be described with a clear definition, a typical use case, and measurable results
  • FAQ pages: the ideal format for GEO. Each question is a potential citation vector
  • Blog posts and guides: long-form content that covers a topic in depth

6. Measure your visibility in AI engines

Unlike SEO, where Google Search Console gives you your rankings, there still isn’t a standardized tool to measure your GEO visibility precisely. Manual testing is still the most reliable method: regularly test target queries in ChatGPT, Perplexity, and Gemini, and note whether your site is cited.

A few emerging tools can automate this tracking: Profound, Otterly.ai, AI Rank Tracker. None are as mature as traditional SEO tools yet.

good to know

AI engines don’t all use the same sources. Perplexity runs real-time web searches and cites its sources explicitly. ChatGPT (without a plugin) relies on its training data. Gemini combines both. Your GEO strategy therefore needs to cover both training (indexable content, authority) and real-time search (fresh content, clear markup).

SEO vs GEO: the concrete differences in your workflow

Here’s how the two disciplines compare in day-to-day practice:

ActionSEO priorityGEO priority
Keyword researchYes, search volumeYes, conversational intent
H1 title optimizationExact keyword at the startClear question or direct statement
Content lengthDepends on competitionDense and complete, no padding
Inbound link buildingAbsolute priorityImportant but secondary
Structured dataRecommendedEssential
FAQ formatUseful for featured snippetsEssential
About pageLittle direct impactMajor strategic page
Load speedRanking factorNegligible impact

Where to start, practically

If you’re starting from zero on GEO, here’s a logical priority order:

  1. Audit your strategic pages: About, Services, FAQ. Are they written in a factual, structured way?
  2. Add or complete your Schema.org markup: start with Organization on your homepage, then FAQPage on your FAQ pages
  3. Create an llms.txt file that lists your most important pages
  4. Rewrite your H2 and H3 headings as questions or precise statements
  5. Add numerical data and explicit definitions to your content
  6. Set up monthly tracking: test 5 to 10 target queries in Perplexity and ChatGPT

good to know

GEO is evolving fast. The practices described here are the ones delivering the best results in 2025-2026, but LLM algorithms change frequently. Stay current by regularly testing your target queries across different AI engines.

Conclusion

GEO isn’t a trend: it’s a structural response to how search behavior is evolving. AI interfaces are capturing a growing share of queries, and the sites that adapt now will pull ahead of those that wait.

Applying GEO doesn’t mean starting from scratch. It means sharpening what you already do in SEO: better structure, denser content, more precise markup. The gains compound.

  • Use case 1: a SaaS startup that wants to be cited when a prospect asks "which tool should I use for X" in ChatGPT
  • Use case 2: an agency that wants to appear in Perplexity answers when someone searches "Webflow agency France"
  • Use case 3: a consulting firm that wants its service pages to become the cited reference for LLMs in its market

Good to know

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