AI Search Optimization
AI search optimization: get cited by ChatGPT, Gemini and AI Overviews
AI search optimization, or GEO (Generative Engine Optimization), is the work of getting a company cited in answers from ChatGPT, Perplexity, Gemini and Google AI Overviews. It differs from traditional SEO because these systems do not show ten blue links: they pick a handful of sources and write a single answer. Fluxo Ads audits whether your brand appears in those answers today, restructures your site content into the format models can actually extract, and tracks citations month over month.
- ChatGPT
- Perplexity
- Google AI Overview
- Gemini
- Claude
- Copilot
- llms.txt
- Structured data
- Extractable content
What is included
What you receive
- 01
Citation audit
We run the questions your customers actually ask across each assistant and record who gets cited today. You find out whether the answer names you, names a competitor, or names nobody in your category.
- 02
Content restructuring
A direct answer under every heading, tables instead of prose, marked-up FAQs, and facts spelled out in full. That is the format models extract faithfully.
- 03
Complete structured data
Schema.org for organization, service, article, FAQ and navigation. This is the layer that states unambiguously what you do, where you operate and how to reach you.
- 04
llms.txt file
A plain-text business summary and site map in the format model crawlers already consume. A sitemap says which URLs exist; llms.txt says what each one answers.
- 05
Crawler accessibility
Model crawlers do not execute JavaScript and do not scroll. We audit what is left of your site with JavaScript disabled, which is usually far less than the owner expects.
- 06
Monthly citation tracking
A report repeating the same questions every month, showing gains and losses per assistant, plus traffic arriving from AI domains in your analytics.
Process
How we run it
- 1
Question mapping
We list 30 to 50 real questions across your funnel, from informational ("what is") to decision-stage ("best company for X").
- 2
Baseline
We run every question through each assistant and record the starting state. Without that measurement there is no way to prove a gain later.
- 3
Restructuring
We rewrite and re-mark up the priority pages into extractable format, and implement schema, llms.txt and the rendering fixes.
- 4
Re-measure and adjust
We repeat the question battery monthly. What gained citations becomes the template for the next pages; what did not goes back in the queue with a new hypothesis.
Why search changed
For twenty years a search result was a list of links, and SEO meant climbing that list. AI assistants broke the format: they read several sources and return a single answer, citing only a few. If you are not cited you do not appear at all — there is no second page to fall back on.
That changes the target of the work. Ranking is no longer enough: you have to be the source the model chooses to copy. And models choose by different criteria than the classic search algorithm.
What a model can actually read from your site
Language model crawlers have two limitations that decide almost everything: they do not execute JavaScript and they do not scroll. A React site that assembles its content in the browser serves that crawler a nearly blank page. The owner sees everything working and cannot understand why they are never cited.
The format models extract best
Not all text is equally quotable. Across projects, four formats proved consistently more extractable than prose:
| Format | Why it works | Where to apply it |
|---|---|---|
| Direct answer under the H1 | 2 to 3 sentences that answer the query on their own, independent of the rest of the page | Every page, before any CTA |
| Table | Explicit relationships between columns, no need to infer structure from prose | Comparisons, pricing, timelines |
| FAQ with schema markup | Question and answer arrive already paired and declared as such | End of every service page |
| Facts written out in full | No "click here to see": the data has to be in the text to be copied | Phone, timeline, coverage, price |
GEO and SEO are not competitors
Much of what makes a page quotable by AI also makes it rank on Google: clarity, structure, verifiable data and authority. GEO does not replace SEO consulting — it builds on it. What changes is the priority of certain techniques: structured data and JavaScript-free rendering move from "good practice" to requirement.
In practice we run both together on most projects. When the site has to be rebuilt to support it, that work is bundled with website development.
How we measure results
A citation inside an AI answer does not show up in Google Analytics the way a Search Console position does. We measure on two fronts:
- Direct citation: the same question battery run monthly across each assistant, recording who was cited and in what order.
- Referral traffic: sessions arriving from chatgpt.com, perplexity.ai, gemini.google.com and copilot.microsoft.com, isolated in analytics.
The second number tends to start small and grow fast. The first is what matters strategically: being the company the assistant names when someone asks who to hire.
Frequently asked questions
How long does it take to show up in AI answers?
Can you guarantee ChatGPT will cite my company?
Do I need to rebuild my entire website?
Does this work for a local business?
What is the difference between GEO, AEO and AI SEO?
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