Initial GEO Audit
Mapping of your domain's current citations across the four main AI engines, on a set of 30-50 queries relevant to your industry. Output: a document with a measurable baseline and intervention priorities.
GEO Consulting: Optimization for ChatGPT, Gemini, and AI Engines
SEO gets you on the first page. GEO gets you inside the answer. They are two different things, and today you need to do both — because in 2025, traffic generated by AI assistants to websites grew by 527% year-over-year, and none of your competitors are doing anything to intercept it.
Generative Engine Optimization (GEO) is the discipline of optimizing website content to be cited by AI search engines — ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot. It differs from traditional SEO because it does not aim for the click on the SERP, but for the citation inside the answer generated by the model. The main techniques are: comprehensive schema markup (Organization, Service, FAQPage, HowTo, Article), answer-first structured content in the first 60-100 characters, an llms.txt file in the root of the site, robots.txt explicitly open to AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended), well-defined entities, and high fact density.
+527%
YoY growth in traffic from AI assistants to websites in 2025
~70%
Global market share of ChatGPT among AI search platforms
3-5
Average number of sources an AI engine cites for each response
2 / 10
Companies with a structured GEO strategy today
Understand the mechanism before optimizing it.
An AI engine is not a search engine. It is a hybrid system that combines language generation with web source retrieval. When a user asks a question, the model performs three operations in sequence.
Query understanding
The model internally reformulates the user's question to understand the real intent. Example: "best CRM software for SMEs" internally becomes multiple queries like "cloud CRM for SMEs 2026", "affordable HubSpot alternatives", "CRM with local support".
Source retrieval
The engine queries its index (for ChatGPT, it is based on Bing + proprietary crawling) and selects 5-15 relevant candidate sources. Classic SEO and the presence of structured data interpretable by the model play a major role here.
Synthesis and citation
The model reads the sources, extracts the most relevant information, and combines it into a single response, citing 3-5 links. Pages with answer-first content and high fact density are much more likely to be cited.
Output to the user
The user sees a concise response with footnotes containing citations. If your site is among those cited, you receive a highly qualified click (high intent) or, even better, brand exposure without a click — a phenomenon known as a "zero-click impression."
Eight levers of intervention, integrated into an operational plan.
Comprehensive Schema Markup
Implementation of all relevant schemas for your industry: Organization, Service, ProfessionalService, FAQPage, HowTo, Article, BreadcrumbList, ItemList, Product, Recipe, Event. Every page of the site is structured.
Answer-First Rewriting
We rewrite key content according to the structure most "readable" by LLMs: a concise answer in the first 60-100 characters, backed by verifiable facts, statistics, and citations from authoritative sources.
llms.txt File
Implementation and maintenance of the llms.txt file in the domain root. An emerging standard that describes the site in Markdown format to LLMs. Faster to read than an XML sitemap.
AI Crawler Configuration
Explicitly opening robots.txt to all major AI bots: GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended, anthropic-ai. Configuring headers and CDN to ensure efficient crawling.
Entity Definition & E-E-A-T
Building brand entities on knowledge graphs (Google Knowledge Panel, Wikidata, Wikipedia where applicable), author pages with solid E-E-A-T, and verifiable external citations.
Endpoints for AI Agents
Creation of static, machine-readable (JSON) endpoints with structured information about services, contacts, and hours. This prepares the site to be programmatically queried by AI agents — the next step after AI searches.
AI Citation Monitoring
Monthly tracking of citations across the four AI engines, with benchmarking against direct competitors. Tools used: Otterly, Profound, BrandRank.AI, or equivalents, depending on the project.
The Core Differences Between the Two Disciplines.
They are complementary, not alternatives. However, they follow profoundly different logics.
| Traditional SEO | GEO (AI Search) | |
|---|---|---|
| Objective | Positioning in SERPs | Citation within the AI response |
| Primary metric | Click-through rate, organic traffic | AI citations, brand mentions, AI referral traffic |
| Content unit | Keyword-optimized page | Extractable, concise answer |
| Ideal structure | H1, argumentative paragraphs, keyword density | Answer-first, verifiable facts, structured schema |
| Schema markup | Useful for rich snippets | Critical for fact extraction |
| Key files | sitemap.xml, robots.txt | llms.txt, robots.txt open to AI bots |
| Time to results | 3-6 months | 2-4 months |
| Market status | Saturated, high competition | Embryonic, window of opportunity open |
Who this service is for
GEO makes sense right now if you recognize yourself in these situations.
- You have a B2B brand that wants to dominate buying committee searches
- You sell products or services that users compare via ChatGPT
- You are in an industry where your customers ask "which is the best?"
- You have quality content but it is poorly structured for LLMs
- You want to get ahead of competitors on a channel that is still untapped
- You are seeing a decline in organic click-through rates
- You have invested heavily in content marketing without monitoring AI
- You are building brand authority in a technical sector
About GEO and AI Search.
What is GEO (Generative Engine Optimization)??
GEO is the discipline that optimizes web content to be cited by generative search engines: ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot. It differs from traditional SEO because it does not aim for a click on the SERP, but for a citation within the response generated by the AI. The term was proposed in 2023 by researchers from Princeton, Georgia Tech, and the Allen Institute.
What are the main AI search engines in 2026?
The four main AI engines are: ChatGPT (OpenAI, around 70% of global market share among AI search platforms), Google Gemini with AI Overviews (present directly in Google results), Perplexity (search-first AI rapidly growing among technical users and SMEs), and Microsoft Copilot (based on GPT-4, integrated into Bing, Edge, and Microsoft 365). All cite web sources and all are optimizable.
How do AI engines choose which sources to cite?
AI engines select sources by combining several signals: classic SEO ranking (already authoritative pages), presence of Schema.org structured data (for fact extraction), answer-first content structure, fact density (verifiable statistics and data), well-defined entities, presence in authoritative sources like Wikipedia, domain authority, and content freshness. GEO optimizes all these factors simultaneously.
Does GEO replace SEO?
No. GEO complements SEO. To be cited by AI engines, you first need to be ranked organically: content that ranks in Google's top 20 results is the primary pool from which LLMs draw. SEO is the necessary condition; GEO makes it sufficient to obtain AI citations. Anyone starting today without a solid SEO foundation is building on sand.
How much does a GEO service cost?
The standalone GEO service starts at €1,200/month and can be combined with SEO consulting for an integrated fee starting at €1,500/month total. The initial GEO audit is free and includes a mapping of current citations on the main AI engines, based on a set of 30-50 queries relevant to your industry.
How long does it take to see GEO results?
The first technical improvements (schema markup, llms.txt, answer-first content) can be implemented within 30-45 days. The first stable citations on AI engines typically arrive in 60-120 days: language models update their indexes in slower cycles compared to Google. Perplexity and AI Overviews are the most responsive (4-8 weeks); ChatGPT is the slowest to update its knowledge base (often 3-4 months).
What is the llms.txt file?
The llms.txt file is an emerging standard, proposed in 2024 by Jeremy Howard, that acts as a sitemap dedicated to LLMs: it describes the site structure, key content, and crawling policies in Markdown format. It is placed in the domain root (https://yoursite.com/llms.txt) and helps AI engines understand the site structure without having to crawl every single HTML page. It is a GEO best practice that we adopt by default on our clients' sites.
How are AI citations measured?
AI citations are monitored with dedicated tools that periodically test sets of relevant queries on the four main AI engines and record if and how the domain is cited. The most common tools are Otterly, Profound, BrandRank.AI, and AthenaHQ. In addition, Google Analytics 4 shows referral traffic coming from AI assistants (chat.openai.com, perplexity.ai, copilot.microsoft.com), a figure that has doubled over the last 12 months.
Is your site ready to be cited by AI?
Take our self-diagnostic test to calculate your GEO Readiness score, or book a free customized audit.