What GEO Is & Why Your Business Needs It

An introductory guide to GEO: What it is, why it matters, and how to optimize your content for AI-powered search.
Aug. 13, 2026
15 min
Contents:

What GEO Is & How It Differs from SEO

Search used to work like this:
  1. Users enters a query.
  2. They see a list of search results.
  3. They click the first result.
  4. If the page doesn't answer their question, they go back and try another websites.
Today, the process often looks different:
  1. Users enters a query.
  2. They read an AI-generated overview.
  3. If the answer isn't sufficient, they click one of the sources cited by AI.
  4. If the answer is sufficient, they never click through to a website.
For website owners, this creates two possible scenarios:
  1. AI cites your content: You gain a citation, brand visibility, and potentially traffic.
  2. AI cites a competitor: Your website remains invisible, even if it ranks first in traditional search results.
To increase the chances of being cited by AI, marketers use GEO (also referred to as AEO).
GEO (Generative Engine Optimization) is the practice of optimizing content for generative search systems such as Google AI Overviews, ChatGPT Search, Perplexity, and Google Gemini. The goal is no longer to rank higher in search results, but to become part of the AI-generated answer.
GEO helps your business show up in AI-generated overviews and recommendations.
SEO
GEO
Goal
Rank at the top of search results
Be cited in AI-generated answers
Ranking unit
The entire page
A paragraph or section
Primary signals
Backlinks and user behavior
Content structure and unique information
Outcome
A click to the website
A direct answer, with or without a click-through
Key tools
Meta tags, backlinks, page speed
Answer Units, Schema.org, Entity-First
GEO doesn't replace SEO. In most cases, the websites cited by AI are the same ones that perform well in traditional search. However, SEO alone is no longer enough.

How AI Decides Which Websites to Recommend

Before updating your content, it's important to understand how AI search works. Otherwise, optimization efforts can quickly become random and ineffective. Most modern AI search systems rely on Retrieval-Augmented Generation (RAG). Here's a simplified overview of the process.

Step 1: Retrieving relevant passages

AI doesn't search for exact keyword matches the way Ctrl+F does. Instead, it understands meaning and context, even when there are no overlapping words. For example, a query like "How do I get a loan?" may surface a paragraph about "the loan application process" even if none of the exact keywords appear in the text.
Technically, both the user's query and every piece of content are converted into numerical representations. Similar numbers indicate similar meaning. To learn more about how AI works, see our article on artificial intelligence.
The system retrieves the 20-50 passages that are most relevant and passes them to the next stage.

Step 2: Reranking

A second filtering stage compares each selected passage against the original query and evaluates its actual relevance. AI tends to favor passages that include concrete facts, original insights, and data over vague or generic statements.
As a result, only the top 3-5 passages move forward.

Step 3: Generating the answer

AI composes an answer using the selected passages and cites the original sources.
If an AI includes a link to your website, the person may notice your logo and click through.
AI systems rank passages rather than entire web pages. The boundaries of a passage are determined automatically, but in practice, a passage usually consists of 1-3 paragraphs organized around a single idea under one H2 heading. The more precisely a section answers a specific question, the more likely AI is to extract it as a standalone answer.

Large, catch-all sections titled "General Information" are poor candidates for citation. Specific H2 headings framed as questions or clear statements perform much better. If a passage fails to make it through the initial retrieval stage, nothing later in the process can save it. The competition happens not between pages, but between thousands of passages from different websites.

How to Prepare Your Website for AI Indexing

Many website owners immediately start rewriting their content. This is a mistake. If a website has technical issues, AI crawlers may fail to access the content or interpret it incorrectly. A solid technical foundation should come first.

Configure robots.txt for AI search

Here are several important steps:
1
Don't block CSS or JavaScript files. Otherwise, AI systems may evaluate the page differently from how users see it, which can negatively affect Core Web Vitals assessment.
2
Review your robots.txt file after every major technical change, especially after website migrations, CMS changes, or CDN implementation. Accidental blocking issues often appear during these updates.
3
Avoid blocking all AI crawlers through a blanket Disallow rule for every user agent. This is a common mistake that can prevent AI systems from indexing your website. To avoid blocking the wrong crawler, it's important to understand which bots each AI platform uses. Most platforms operate several separate bots with different functions, and blocking one doesn't necessarily block the others.
Platform
Model training
Search indexing
User requests
OpenAI
GPTBot
OAI-SearchBot
ChatGPT-User
Anthropic
ClaudeBot
Claude-SearchBot
Claude-User
Google
Google-Extended
Googlebot
—
Perplexity
—
PerplexityBot
Perplexity-User

Keep URLs stable

AI systems and search engines such as Google accumulate behavioral signals and historical data for each document over time. When the same content is accessible through multiple URLs, those signals become fragmented, reducing the page's overall authority and search performance.
Common issues and how to fix them:
1
UTM parameters in URLs (?utm_source=email_campaign) are tracking parameters used for analytics. They can create duplicate pages in search indexes: The website is the same, but search engines may see dozens of different URLs.

Solution: Add a canonical tag to every page by specifying `<link rel="canonical" href="URL without UTM parameters">`. This tells Google that all parameterized versions refer to the same page, so only the canonical URL should be indexed.
2
Filter parameters in online catalogs (?color=red&size=M) — each filter combination generates a new URL. On large eCommerce websites, this can result in thousands of duplicate pages.

The solution depends on how your website handles filtering and URL parameters. For search engines such as Google, use a canonical tag pointing to the main version of the page or block parameterized URLs in the "robots.txt" file when appropriate.
3
Duplicate versions with and without "www" — website.com and www.website.com are technically different URLs.

Solution: Set up a 301 redirect from one version to the other and specify the preferred domain in Google Search Console. On Tilda, this can be configured in Site Settings.
The rule is simple: One URL = one address = one indexing history.

Content quality

AI systems evaluate not only the page you want to rank, but also the website as a whole. Hundreds of thin tag pages or duplicate pages weaken your website's topical signals. As a result, even high-quality pages can lose visibility.
Pages to remove, improve, or exclude from indexing:
  • Tag and category pages with little or no original content
  • Empty author profiles without photos, bios, or proof of expertise
  • Duplicate pages
  • Technical pages accidentally indexed, such as shopping carts or user account pages
Recommended tools: Screaming Frog (free for up to 500 pages) and Google Search Console → Coverage report.
If you're new to no-code solutions, use this exclusive promo code to get one month of the Tilda Personal Plan instead of the standard 2-week trial.
See instructions on how to activate it

Website speed

If a server responds slowly or frequently returns errors, Google reduces its crawl rate. On large websites, with tens of thousands of pages, this can become a serious issue, as some pages may never make it into the index. On smaller websites, server speed is rarely a major bottleneck.
AI crawlers are less transparent. There is no public documentation explaining how GPTBot or ClaudeBot adjust crawl frequency. Still, the underlying principle remains the same: A slow server creates friction at every stage of the crawling process.
Three key metrics to monitor (Core Web Vitals):
  • LCP (Largest Contentful Paint) under 2.5 seconds.
  • CLS (Cumulative Layout Shift) below 0.1.
  • INP (Interaction to Next Paint) under 200 ms.
Recommended tool: PageSpeed Insights.

JavaScript-generated content

Among major crawlers, only Googlebot and Gemini, which uses Google's infrastructure, can reliably render JavaScript. GPTBot, ClaudeBot, and PerplexityBot receive only the raw HTML, meaning they cannot see content loaded via JavaScript.
The practical takeaway is straightforward: If your website is built with React, Vue, or another JavaScript framework without server-side rendering (SSR) or static site generation (SSG), most AI crawlers will see an empty page instead of actual content.
One important clarification: Content hidden inside accordions or tabs is perfectly acceptable. Google has officially confirmed that any content present in the HTML when the page loads is fully considered for indexing. Problems arise only when content is loaded via AJAX after a user interaction. In that case, the content is missing from the initial HTML, and crawlers may never see it.

Audit your website in 5 minutes

Here are four quick checks you can run right now:
1
Open yoursite.com/robots.txt and make sure OAI-SearchBot, Claude-SearchBot, and PerplexityBot aren't blocked.
2
Run your website through PageSpeed Insights and look at the mobile results. Is your LCP below 2.5 seconds?
3
Go to Google Search Console → Coverage and see how many pages are marked as "Excluded." If more than 30% of pages are excluded, that's a sign of an issue.
4
Disable JavaScript in your browser and reload your Home Page. If the content disappears, GPTBot and ClaudeBot can't access it.

Schema.org: How to Add Structured Data Without a Developer (on Tilda)

Schema.org acts as a second language for your web pages, one that AI systems can read directly. While AI has to interpret regular text and may misunderstand it, JSON-LD explicitly tells it the author, publication date, and the content on the page.
In March 2025, Microsoft officially confirmed that its large language models use schema markup. t SMX Munich, the company said structured data helps AI systems understand content. Google consistently recommends using structured data in its official documentation, although it hasn't publicly confirmed its role in AI Overviews specifically.
Important: Incomplete or incorrect schema markup can be worse than having no schema at all. A 2026 study of 730 AI citations found that pages with incomplete schema were 18 percentage points less likely to appear in AI-generated answers than pages with no schema at all. If you implement schema, make sure to fill in all recommended properties.

3 priority schema types

Article — The primary schema type for any piece of content. Required properties include headline, author, dateModified, and publisher. The @id property acts as a persistent identifier for authors and organizations, allowing AI systems to accumulate reputation signals across multiple publications.
FAQPage — one of the most effective schema types for GEO. According to an academic study published on SSRN (April 2026), pages using detailed schema attributes were cited in AI responses in 61.7% of cases, compared to 41.6% for pages using only basic markup.
Organization — establishes your brand identity by defining your company name, website, description, and social media profiles. It helps AI systems consistently recognize your organization across different mentions and sources.

How to add JSON-LD to Tilda without a developer

  1. Add the "HTML" block (T123) anywhere on the page.
  2. Paste your JSON-LD script into the block.
  3. Validate the markup using Google Rich Results Test.
No-code schema generators such as Merkle Schema Generator and Schema App can generate ready-to-use code snippets for free.

Entity linking

The "about" and "mentions" properties in Article schema can help content become part of Google's Knowledge Graph. These properties explicitly identify the entities discussed in an article and the related topics it references. This is one of the most overlooked GEO techniques.
On the right is a list of sources that Google used to gather the information.

What "Unique Content" Means for AI & Why It Matters

AI systems already know the basic facts. A statement like "SEO is a set of practices used to optimize a website" appears on hundreds of thousands of pages. AI has no reason to cite your website specifically, it can simply use information from Wikipedia.
To be cited, you need to provide information that can't be found anywhere else.

5 types of content uniqueness (from strongest to weakest)

1
Proprietary data: Results of A/B tests, internal metrics, and original research. This is the strongest type of uniqueness because only you have access to this data.
2
Real-world case studies with specific numbers: "We tried X, and here's what happened." Include metrics, timelines, and brand or product names whenever possible.
3
Fresh data. While competitors cite data from 2023, you reference findings from 2026. AI systems use the dateModified field to evaluate how current the content is (a concept often referred to as Temporal E-E-A-T).
4
A new perspective. Everyone writes about "how to do SEO." You write about "why 80% of SEO advice doesn't work for websites with fewer than 100 pages."
5
An original framework. Your own methodology, model, or classification system that can't be found anywhere else.
A quick test: Open the top three results for your target query and list all the facts they contain. Does your page include at least 3 facts that don't appear in any of them? If not, AI has little reason to cite your content.

EEAT in practice

  • Create an author profile with a real bio, job title, and links to published work.
  • Cite primary sources directly in the text. Instead of writing "according to research," specify the source—for example, "According to Ahrefs (February 2026)."
  • Display the date the article was last updated and refresh content whenever new information becomes available.
  • Include personal experience and case studies. AI systems can distinguish expert-written content from rewritten summaries.

How to Increase Your Chances of Being Cited by AI

Answer units: The formula for an AI-friendly paragraph

An Answer Unit is the smallest piece of content AI can extract and use as a standalone answer. If a paragraph doesn't function as an Answer Unit, the model will likely ignore it.
Answer Unit consists of 4 elements:
1
Claim: A single sentence that AI can quote. It should always come first (following the BLUF—Bottom Line Up Front principle). If the main point is buried in the third sentence, the passage may be discarded during the Retrieval stage.
2
Context: Explain who the statement applies to, under what circumstances, and when. Without context, the claim is too broad, making it difficult for AI systems to use as a reliable answer. For example: "For eCommerce websites with catalogs containing more than 1 000 products."
3
Proof: Support the claim with data, research findings, case studies, or named sources. Specific evidence performs better during the Reranking stage, while vague statements tend to lose out.
4
Takeaway: Explain what the reader should do next. A clear, actionable recommendation completes the passage.
Example:
Weak
"Website speed is important for SEO. Search engines consider page speed when ranking websites. That's why you should optimize images and code."
Strong
"According to Google, the probability of a visitor leaving a page increases by 32% when load time grows from 1 to 3 seconds. For eCommerce websites, this translates directly into lost revenue: A slow page means abandoned carts. Check your LCP score in PageSpeed Insights (the recommended threshold is under 2.5 seconds) and optimize your images accordingly."

EAV: A Page Structure AI Can Understand

AI systems store knowledge as triples: Entity (who/what) → Attribute (property) → Value (specific information). Your page structure should follow the same logic:

  • H1 = Entity (the main subject of the page). For example: "Tesla Model 3" or "Mortgage Options from Chase."
  • H2 = Attribute (one specific characteristic or aspect). A simple test: If a heading could answer several different questions, it's probably too broad. "Key Features" is a weak heading because it could refer to almost anything. "Tesla Model 3 Driving Range on a Single Charge" is a strong heading because it focuses on a single attribute.
  • The paragraph under the H2 = Value (the specific answer). It should provide a clear answer supported by facts, numbers, or practical guidance. Instead of saying, "Driving range depends on operating conditions," write, "The Tesla Model 3 has a WLTP range of up to 576 km at temperatures above 20°C."
Around 40% of H2 headings should be phrased as questions people would ask AI chatbots. This is a rule of thumb rather than a strict requirement.

Entity-first & the Liftability test

AI extracts passages without surrounding context. If you use pronouns instead of naming the entity directly, the passage may no longer make sense on its own.
Three rules:
  • Explicitly name the entity in every paragraph. Avoid vague references such as "it," "the company," or "the service." Use the actual product, brand, or company name instead.
  • One term = one concept. Don't alternate between terms such as "robot vacuum," "device," and "appliance" when referring to the same product. While this may reduce repetition for human readers, it can create ambiguity for AI systems. Repeating the exact name is usually better than losing clarity. If repetition feels excessive, use pronouns only within a single paragraph where the context is obvious. Always restate the entity when starting a new paragraph.
  • Avoid references to surrounding context, such as "as mentioned above." AI systems don't understand the concept of "above" or "below" on a page.
The Liftability test: Show a paragraph to a colleague without the rest of the article. If they immediately understand it, the paragraph has high liftability. If they ask, "What is this about?" rewrite it.

How Websites Get Cited in AI Answers

AI systems read the entire web, not just your website. If ten independent and authoritative sources describe you as an expert in a particular field, AI systems may reach the same conclusion even without citing your website directly.

In GEO, this is known as the consensus principle: The more independent sources say the same thing about you, the more trustworthy that information appears to AI systems.
According to an Ahrefs study (September 2025), Wikipedia, YouTube, and Reddit are among the most frequently cited domains in Google AI Mode. Research by Profound (March 2026) found that LinkedIn was the most frequently cited domain for professional queries across six AI platforms: ChatGPT, Gemini, Google AI Overviews, AI Mode, Microsoft Copilot, and Perplexity.

What works in practice

1
Publish expert content on trusted platforms. Contributing to industry websites, professional media outlets, and respected communities does more than generate backlinks. These mentions become part of the broader consensus AI systems build around your brand.
2
Participate in interviews and podcasts. Being recognized as an expert in someone else's content often carries more weight than publishing on your own website. AI systems tend to treat third-party mentions as independent validation of your expertise.
3
Get featured in comparison and roundup articles. Appearing in competitor comparisons, industry roundups, or aggregator websites gives you an endorsement from an independent source.

GEO in Action: Real-World Results

Everything covered in this guide—from technical optimization and structured data to AI-friendly content—is already being implemented in real client projects at Rush Agency. Here are a few examples:

Example 1. Large furniture retailer: 43x increase in ChatGPT traffic over 10 months

Example 2. Dental clinic: 620+ queries in AI Overviews and 8x traffic growth

Both cases have one thing in common: AI traffic doesn't happen by chance. It's driven by deliberate technical and content decisions. Don’t wait until this becomes the industry standard — by then, catching up will be much harder.

Checklist: Is Your Website Ready for AI Search

1
Technical accessibility
  • "robots.txt" doesn't block CSS or JS for Googlebot
  • Search AI bots aren't blocked: OAI-SearchBot, Claude-SearchBot, and PerplexityBot
  • Training bots are managed separately from search bots in "robots.txt" (GPTBot ≠ OAI-SearchBot)
  • URLs are stable: No UTM parameters on indexable pages, and canonical tags are configured correctly
  • PageSpeed Insights metrics meet the recommended thresholds: LCP < 2.5 seconds, CLS < 0.1, INP < 200 ms
  • Third-party scripts (chat widgets, tracking pixels, analytics tools) are kept to a minimum
2
Content
  • Every paragraph follows the Answer Unit structure: Claim → Context → Proof → Takeaway
  • The main point always appears in the first sentence of the paragraph (BLUF)
  • Entities are named explicitly in every paragraph, avoid references such as "it," "this service," or "this platform"
  • Each page includes at least 3 facts that don't appear in the top three competing results
  • Author profiles include a photo, biography, job title, and links to published work
3
Structured data
  • JSON-LD Article schema has been added, including: Headline, author, dateModified, publisher, and @id
  • FAQPage schema has been added after key sections (answers are self-contained and 50-150 words long)
  • Organization schema has been added, including the company name, website, description, and social media profiles
  • The markup has been validated using Google Rich Results Test, and no errors were found

What's Next

GEO isn't a replacement for SEO, it's the next stage of search optimization. Technical improvements can usually be implemented within a week, and content can often be updated within a month. Companies that start adapting now will appear in AI-generated answers before their competitors, while many businesses are still focused solely on optimizing meta tags.

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