// LLM Visibility
How Visible Is Your
Business to AI?
ChatGPT, Claude, Gemini and Perplexity are changing how people find information. Find out if your brand appears in AI-generated answers.
// What Is LLM Visibility?
A New Dimension
of Visibility
LLM Visibility describes how present a brand or website is in the responses of AI language models. Unlike traditional SEO, it's not about search result rankings, but whether AI models like ChatGPT, Claude or Gemini know the brand and mention it in generated responses.
Large language models (LLMs) generate responses from a combination of training data and — for some models — real-time retrieval from the web. The factors that determine which brands get mentioned differ significantly from traditional SEO signals.
The field is evolving rapidly. Early studies show clear trends, but there are no guaranteed ranking factors like in traditional SEO. Those who optimize early gain an advantage — but humility about the complexity of the topic is warranted.
AEO: Answer Engine Optimization
Alongside traditional SEO, a new discipline is emerging: Answer Engine Optimization (AEO). While SEO targets search result rankings, AEO optimizes content so that it gets cited by AI models as an answer.
The numbers show why this matters: The CTR for position #1 dropped from 28% to 19% because of AI Overviews — a decline of 32%. At the same time, the number of keywords with AI Overviews grew 17-fold in 10 months (10,000 to 172,000).
The key difference: SEO gets you to page 1 of the search results. AEO gets you into the answer itself. While SEO relies on backlinks, keywords and page speed, AEO focuses on structured data, authority in training data and machine-readable content formats like llms.txt.
// Known Factors
What Influences AI Visibility
Based on current research and practical experience.
Structured Data
Schema.org markup and JSON-LD help AI models understand content. In published tests, GPT-4 accuracy increases with structured data from 16% to 54% — an improvement of 238%. Well-structured data dramatically raises the chance of being referenced in LLM responses.
llms.txt Standard
The new llms.txt standard (comparable to robots.txt) makes it possible to provide structured information about your own website to AI crawlers. In practice: a /llms.txt short version for fast crawling and a /llms-full.txt with detailed information on brand, services and USPs.
Brand Presence
Mentions in authoritative sources — trade publications, Wikipedia, industry directories — increase the likelihood of being represented in LLM training data. Microsoft Copilot mentions brands with 26.7% frequency — those present in high-quality sources get cited by AI.
Technical Foundation
Every LLM sources its data differently: ChatGPT (68% market share) uses training data + web search. Claude relies on training + RAG and is strong with long contexts. Gemini integrates Google Search directly (avg. position #1.6 in AI Overviews). Perplexity searches the web in real time with source citations.
// What Research Shows
Studies & Insights
Analyses of AI Overviews show: AI-generated answers in Google Search are fundamentally changing click behavior. Brands that do not appear in these answers lose visibility — regardless of their traditional SEO ranking.
Studies on the crawling behavior of LLM bots reveal significant differences from traditional search engine crawlers. The way AI systems index websites requires new technical optimizations.
The llms.txt standard is establishing itself as the new counterpart to robots.txt — specifically for AI crawlers. Early adoption can create a competitive advantage, similar to the early adoption of XML sitemaps.
Those who optimize early gain an advantage — but the field is young and the research landscape is evolving rapidly.
// Platform Comparison
| Feature | ChatGPT | Claude | Gemini | Perplexity |
|---|---|---|---|---|
| Market Share | ~68% | ~12% | ~10% | ~5% |
| Data Source | Training + Web | Training + RAG | Google Search | Real-Time Web |
| Source Citation | Rarely | Rarely | Yes (AI Overview) | Always |
| Strength | Reach | Analysis | Google Ecosystem | Recency |
// How the Check Works
3 Steps to Your Score
Technical analysis + AI assessment = actionable plan.
Enter Domain
We automatically check your website for AI-relevant technical factors.
Multi-LLM Assessment
Multiple AI models analyze how well your brand is known and whether it appears in AI-generated answers.
Score + Report
You receive a score from 0-100 with actionable recommendations via email.
// Optimization for Every LLM
How to Become Visible to AI
Concrete measures that improve your visibility across all LLMs.
📝 Content Structure That Gets Cited
- ▶ Phrase headings as questions (H2: "What does social media marketing cost?")
- ▶ Bullet points and numbered lists for clear answers
- ▶ FAQ schema markup for structured answers
- ▶ Definitions and explanations at the start of a paragraph ("X is...")
📄 Set Up llms.txt
- ▶
/llms.txt— short version for AI crawlers - ▶
/llms-full.txt— detailed version with all the specifics - ▶ Add company name, services, USPs and contact details
- ▶ Update regularly (quarterly recommended)
⏰ Freshness Signals
- ▶ Use dates and years in content ("As of: March 2026")
- ▶ Document version numbers and updates
- ▶ Publish new content regularly (blog, case studies)
- ▶ Update outdated content instead of deleting it
// Next Step
Want to Improve Your
LLM Visibility?
We help you systematically make your brand visible to AI models — from structured data to content strategy.
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