Editorial guide · GEO and SEO · Updated September 2026
What is GEO: getting cited in the answer, not just listed.
GEO is the work of getting your company cited when someone asks ChatGPT, Gemini, Claude, Perplexity or Copilot. This guide covers how those models choose their sources, what to do on each front, how to measure citations and where companies get it wrong.
We work in English, Portuguese and Spanish. Headquarters in Belo Horizonte, Brazil.
01Overview
What is GEO
GEO (Generative Engine Optimization) is the work of getting a brand, a product or a piece of content cited inside answers generated by artificial intelligence. If you want to know what is GEO in one line: it is SEO applied to a place where there is no list of ten blue links, only a single answer that picks a handful of sources to stand behind what it says.
Buyer behaviour is what makes this urgent. The same person who used to type three words into Google now writes a full paragraph into an assistant, with context, budget and constraints, and gets a shortlist back. When the model names which vendors to consider, being on that list is worth more than any organic position, because the decision arrives pre-filtered.
Netlinks has run GEO inside the same SEO contract since before the acronym became a market topic, with citation monitoring across dozens of AI models running in the App for clients. Everything in this guide comes from live client work: more than 200 companies served since 2017, executed in English, Portuguese and Spanish.
- 200+
- companies served since 2017
- Dozens
- of AI models monitored in the Netlinks App
- 24h
- of live citation tracking
- 3
- languages we plan and execute in
02Contents
What this guide covers
Twelve blocks, from the concept to measurement. If you already know what the acronym means, start with the criteria.
- What is GEO: the definition in two sentences
- GEO, SEO and AEO: the difference in one table
- How AI models build an answer
- The six criteria that decide who gets cited
- What is GEO in practice: the checklist
- Citable content: the format models lift
- Structured data: removing the ambiguity
- Authority and consensus: the model checks you elsewhere
- How to measure GEO: AI monitoring
- What is GEO in your sector: six examples
- Six common GEO mistakes
- Where to start
03Definition
What is GEO: the definition in two sentences
GEO, short for Generative Engine Optimization, is the discipline of preparing a company's content, authority and data so that language models use it as a source when answering questions. The outcome is not a position in a list: it is your brand named, with a link, inside an answer the machine wrote.
The name describes what changed about where answers live. A classic search engine returns ten links and leaves the choice to the person. A generative engine reads several pages, summarizes, decides and hands over a recommendation, crediting a few sources. Anyone not among them simply does not exist in that conversation.
Three practical consequences:
- The field narrows. Where ten results used to fit, three or four cited sources now do. The prize for being one of them is larger, and so is the cost of missing out.
- The click changes character. Someone clicking a cited source has already read the summary and wants depth or wants to buy. It is a visit with formed intent.
- Your brand becomes data. The model needs to know your company exists, what it does, for whom and where. Inconsistent information across the web turns into absence from the answer.
GEO does not replace SEO, and that confusion is the most expensive one going around. Almost everything that gets a page cited by an AI is what gets it ranked by Google: deep content, authority, structured data and speed. The foundation is covered in what is SEO.
04Comparison
GEO, SEO and AEO: the difference in one table
The three acronyms coexist and plenty of vendors use them interchangeably. This table separates what each one optimizes, where the result shows up and how it is measured.
| SEO | AEO | GEO | |
|---|---|---|---|
| What it optimizes | Pages for the results list | Passages that answer one direct question | Content and brand to be cited by AI models |
| Where it shows | Organic results in Google and Bing | Featured snippets, People Also Ask, voice assistants | ChatGPT, Gemini, Claude, Perplexity, Copilot and AI Overviews |
| Unit of success | Position and click | Owning the answer box | Brand citation inside the answer |
| Metric | Average position, traffic, conversion | Snippet presence, click-through rate | Citation frequency, share of voice, sentiment |
| Winning format | A complete page on the topic | A 40 to 60 word direct answer | A self-contained passage with data, source and context |
| What they share | Good content, authority, structured data, speed | Same | Same |
05Mechanics
How AI models build an answer
Every model implements this differently, and they all change month to month. The general path, when the answer uses the live web, looks like this. Understanding the path is what separates GEO from guesswork.
- 01
Interpretation
The model reads the question and works out what the person actually wants: to compare, to decide, to understand, to find a supplier nearby.
- 02
Query rewriting
The question becomes several different searches, with synonyms and angles. That is why optimizing for one exact phrase pays so little in GEO.
- 03
Retrieval
The model searches its own indexes and partner search engines and pulls back dozens of candidate pages. Not being indexed means being eliminated here.
- 04
Reading and selection
Candidates are read in passages. The passage that answers on its own, with data and context, and without depending on the rest of the page, wins the space.
- 05
Cross-checking
The model verifies the claim against more than one source before asserting it. A figure that appears in a single place tends to be dropped.
- 06
Synthesis and citation
The answer is written and a few sources are credited with a link. Being one of them is what GEO chases and what monitoring measures.
06Criteria
The six criteria that decide who gets cited
There is no published formula, and anyone promising one is selling something. What exists is an observable pattern across thousands of monitored answers, and it keeps landing on these six points.
Citability
The passage answers the question on its own, in a few lines, with a number, a timeframe or a clean definition. Text that reaches the point in paragraph six rarely becomes a citation.
Consensus
The same information appears in several independent sources. Models avoid asserting what only one site claims, because being wrong is expensive for them.
Structured data
Markup that says what is a price, a rating, an address, an author, a service and a coverage area. It removes the ambiguity that would otherwise get the page dropped.
Authority
A domain recognized on the topic, editorial links, press mentions and a consistent publishing record. It weighs heaviest in sensitive fields such as health, law and finance.
Freshness
A visible date, reviewed information and content that reflects the current year. In fast-moving topics, a stale page is filtered out before it is even read.
Technical access
Indexed, fast, no blanket block on AI crawlers, and the content present in the HTML. Text that only appears after a click is often never read.
07Execution
What is GEO in practice: the checklist
This is the checklist we run in a GEO diagnosis. Every line pairs a concrete action with a way to know it worked, because a workstream without measurement turns into opinion by month three.
| Workstream | What to do | How you know it worked |
|---|---|---|
| Content format | Open every page with a two-sentence definition and answer each subtopic in self-contained blocks | Passages from your page start appearing paraphrased in answers |
| Structured data | Mark up Organization, Service, Product, FAQPage, Article and LocalBusiness, and validate before publishing | Rich results in Google and fewer answers carrying wrong facts about you |
| Brand entity | Standardize name, address, phone, leadership and description across site, Google Business Profile, LinkedIn and press | Models describe your company accurately when asked about it directly |
| Authority | Editorial links and press angles in sector publications, with original data wherever possible | Growth in citations on comparison questions, not just branded ones |
| Question coverage | Map the real questions in your funnel and give each one a page that answers it in depth | The number of distinct questions where you appear keeps rising |
| Technical access | Content in the HTML, fast pages, clean indexing and a deliberate robots.txt decision per AI agent | Pages read and cited with a direct link, instead of a third party standing in for you |
| Proof and numbers | Publish original data, research, price ranges, timelines and verifiable comparisons | Your figures appear in answers, credited to your brand |
| Monitoring | Run your funnel questions across dozens of models on a fixed cadence and log who gets cited | A historical series of citations by model, by question and by competitor |
08Content
Citable content: the format models lift
The difference between a text that ranks and a text that gets cited lies in the internal architecture of the text. Models do not copy pages, they copy blocks. The more a block stands on its own, the higher the chance it becomes a sentence in the answer.
What we do on every client page that enters a GEO programme:
- Definition first. Two sentences answering the core question before any context or company history.
- One subheading per real question. Phrased the way a buyer asks it, not the way the industry talks internally.
- Short, complete blocks. Each section delivers a figure, a timeline, a price range or a criterion, without depending on the paragraph before it.
- Numbers with a source. An unsourced figure gets dropped. A figure with a stated origin gets reused.
- Tables and lists. Formats a model can read and reconstruct accurately.
- Visible dates and reviews. Content that states when it was updated wins preference in fast-moving topics.
One warning about volume: mass publishing thin text makes results worse, because it dilutes domain authority and increases the odds that a model finds your own site contradicting itself.
09Technical
Structured data: removing the ambiguity
Language models handle uncertainty badly. When a page does not make explicit what is a price, what is a rating, who wrote it and which areas are served, the machine has to infer, and risky inference usually ends in the page being dropped.
Structured data settles that at the source. The markup declares, in machine language, what each piece of information means. It is the most neglected layer in the market and the one paying best right now, because it serves Google and the AI models at the same time.
The markup that moves the needle most on a company website:
- Organization with the legal name, logo, profiles and identifiers, so the model knows who it is dealing with.
- Service and Product, with coverage area, availability and price range where one exists.
- FAQPage with the questions visible on the page, never hidden purely for the markup.
- Article with author, publication date and review date.
- LocalBusiness with address, hours and coordinates, for searches carrying geographic context.
Netlinks marks up the entire site, validates before shipping, watches for broken schema on every release and reviews it each cycle. The full service is at structured data, and the engineering behind it at technical SEO.
10Authority
Authority and consensus: the model checks you elsewhere
Before recommending a company, a model looks for confirmation. If the only source claiming you lead a category is your own website, the claim drops out of the answer. If trade press, industry associations, specialist portals and public profiles say the same thing, the claim gets treated as fact.
That reshapes the authority workstream inside a GEO programme:
- Press counts twice. It produces a link and it repeats your information in an independent source, which is exactly what cross-checking looks for.
- Original data travels. Studies, surveys and operating numbers are the material journalists publish and models reuse with credit.
- Entity consistency. Name, address, phone, leadership and description have to match everywhere. Divergence creates uncertainty, and uncertainty creates omission.
- Presence where the question is asked. Reddit, niche forums, YouTube and technical communities feed part of what these models read.
Execution sits in authority, with links at link building agency and press angles at digital PR.
11Measurement
How to measure GEO: AI monitoring
GEO has no average position to track. Measurement means running the real questions from your funnel through the models on a fixed cadence and recording what came back. That is robot work, not an intern opening ChatGPT every Monday.
It is what the Netlinks App does for clients: it fires a defined set of questions at dozens of AI models on a schedule and stores who appeared, in what context and next to which competitor. The numbers we track:
- Citation frequency. How many answers mention your brand, by model and by question.
- Share against competitors. Who splits the answer with you, and on which topics they win.
- Sentiment and accuracy. How your company is described, and whether the description is correct.
- Question coverage. How many distinct funnel questions now surface your brand.
- Crosswalk with organic. Google rankings and AI citations side by side, because each feeds the other.
All of it sits on the same screen as the SEO report, updated 24 hours a day, next to the delivery queue waiting for your approval. Details at AI monitoring and technology.
12Application
What is GEO in your sector: six examples
The question a model receives changes by sector, and so does the material it needs to find. Six cuts we see often across our portfolio.
Ecommerce
The question becomes a product comparison. The winner has complete specifications, real reviews, buying guides and correct Product schema, not a page with a photo and a price.
B2B and software
The question is about vendors and alternatives. The winner publishes honest comparisons, investment ranges, use cases by company size and public documentation.
Professional services
Accounting, legal and engineering run on trust. Named expert authorship, reviewed content and mentions in trade publications matter more here than anywhere else.
Healthcare
A sensitive category with a harder filter. Content with a named clinical reviewer, official sources cited and a dated review is the price of entry, not a differentiator.
Manufacturing
The question is about specifications and approved suppliers. A catalogue with complete technical data, standards met and a stated delivery area is what puts the brand on the list.
Local services
The question carries a city or a neighbourhood. Location pages, marked-up addresses, hours, reviews and genuinely local content decide who makes the recommendation.
13Pitfalls
Six common GEO mistakes
The errors we see most when a company chases AI citations without a plan.
Treating GEO as a separate project
Buying an isolated GEO workstream with no technical SEO and no authority behind it means paying twice for the same work and harvesting half.
Mass publishing with AI
Thin text at volume dilutes domain authority and creates internal contradictions. The model finds the contradiction before your competitor does.
Blocking everything in robots.txt
Shutting out every AI crawler without analysis removes your company from the answers. The decision has to be made agent by agent, with a rationale.
Hiding content behind a click
Accordions that only load text after interaction, or pages assembled entirely in the browser, tend to be read partially or not at all.
Measuring one model only
Each model picks sources differently. Testing in ChatGPT and concluding the work failed ignores the rest of the map.
Claiming without proof
Adjectives do not get cited. Sourced numbers, stated timelines and verifiable comparisons are what a machine can reuse.
14First step
Where to start
If your company has never looked at GEO, the first pass is cheap and fast. One afternoon is enough to know where you stand:
- List 20 real questions from your funnel, phrased the way customers phrase them, including the comparison questions that name competitors.
- Run all 20 in at least four models and log who was cited in each answer. The picture is usually uncomfortable, and it is the most useful data in the conversation.
- Check what AI says about your company. Ask directly who you are and what you do. Errors here point at an entity and structured data problem.
- Pick the three most valuable questions and build the best public answer on the internet for each one.
From there the work is continuous and looks a lot like good SEO: a clean technical base, deep content, correct markup, earned authority and weekly measurement. That is how we run it in GEO for AI search, inside the same SEO consulting engagement and the Response Marketing Method.
15The deliverable
What you receive
Finished work, approved by you in the App and shipped. Not a report that only describes the problem.
Citation diagnosis
Your funnel questions run across dozens of models, with a picture of who is cited today, whether you are in it, and how you compare with competitors.
Question map
The real questions your buyers ask, grouped by funnel stage, with the page responsible for answering each one.
Content rewritten for citation
Definition first, self-contained blocks, sourced data and tables. Produced and reviewed by a senior specialist.
Full semantic markup
Structured data across the whole site, validated before shipping and monitored against breakage on every release.
Authority and consensus
Editorial links and press angles that get the same information repeated in independent sources.
Citation dashboard in the App
Frequency by model, by question and by competitor, with a historical series and a crosswalk to your Google rankings, 24 hours a day.
16How it works
From the audit to the page going live
The same path on every project, with an owner and a date on each step.
- 01
Diagnostic conversation
One meeting to understand the business, the sales cycle and the questions that decide a purchase in your market. No commitment.
- 02
Baseline picture
We run your funnel questions across the models and measure where you appear today, who splits the answer with you and what AI says about your brand.
- 03
Fixing the base
Indexing, speed, content in the HTML, structured data and entity consistency. Without this, none of the rest gets read.
- 04
Content and authority
The best public answers to the chosen questions, with editorial links and press supporting the consensus.
- 05
Approval in the App
You approve every deliverable before it ships and follow the full history of what was done.
- 06
Continuous measurement
Citations measured monthly, with the plan revised against what moved and what competitors gained.
FAQ
Frequently asked questions
What is GEO, in one sentence?
GEO (Generative Engine Optimization) is the work of getting a brand cited inside answers produced by AI assistants such as ChatGPT, Gemini, Claude, Perplexity and Copilot when someone asks about its market.
What is the difference between GEO and SEO?
SEO goes after a position in the search engine's results list. GEO goes after a citation inside an answer written by a language model. The technical foundation is nearly identical, deep content, authority, structured data and speed, and what changes is the shape of the text and the way you measure: citation frequency instead of average position.
Are GEO and AEO the same thing?
No. AEO (Answer Engine Optimization) was born for the search engine's own direct answer blocks, such as featured snippets and voice results, with short factual replies. GEO deals with answers synthesized by generative models, which read several pages, compare sources and cite a few. AEO work helps GEO, but it does not cover consensus, entity data or monitoring.
How do AI models decide which sources to cite?
From what large-scale monitoring shows, six factors carry weight: how citable the passage is, consensus across independent sources, structured data, domain authority, freshness of the content and technical access to the page. No model publishes its formula, and it changes frequently.
Should I block or allow AI crawlers in robots.txt?
It depends on your business, and the decision is per agent. Companies selling a product or a service usually gain by allowing the agents that cite sources with a link and assessing case by case the ones that only train models. Blocking everything as a precaution removes your brand from the answers, which is the opposite of the goal.
How long does it take to appear in AI answers?
Base fixes and rewritten content usually change the picture within 4 to 12 weeks. Comparison questions, which are more contested, take 4 to 6 months, because they depend on authority and consensus that build slowly.
Can GEO be measured without a tool?
You can take a manual snapshot: run your funnel questions through the models and log who was cited. What you cannot do manually is track evolution, because answers vary on every run and the historical series is what reveals a trend. In the Netlinks App this runs automatically across dozens of AI models.
Does GEO work for a small company?
It does, and it often pays better in a specific niche, where competition for space inside the answer is still light. A well described regional company with correct structured data and content answering the local question gets into recommendations that generic global brands never reach.
Does publishing lots of AI-written content help GEO?
It hurts in most cases. Thin text at volume dilutes domain authority and creates internal contradictions that models find. What works is depth, sourced data and human expert review.
Do you sell GEO separately from SEO?
No. GEO sits inside the same contract, the same plan and the same report as SEO, because the two share almost all of the technical execution. See how the service is designed at GEO for AI search and the foundation at what is SEO.
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