// HOW AI CITATIONS WORK
AI models cite content differently than Google ranks it
When you ask an AI model a question, it does not run a keyword search and return a ranked list. It retrieves relevant passages from its training data or live web sources, synthesizes them into an answer, and cites the sources that informed that answer.
This retrieval-and-synthesis process is called RAG (Retrieval-Augmented Generation). Each platform uses its own RAG system: Perplexity favors multi-source synthesis (averaging 21.87 citations per response), ChatGPT leans on entity authority and FAQ schema, Gemini prioritizes factual density, and Claude looks for structured content with clear sourcing.
The critical insight: only 11% of domains are cited by both ChatGPT and Perplexity. A site invisible on one platform may rank well on another. Checking all four models is the only way to understand your true AI visibility.
// 6 FACTORS THAT DRIVE AI CITATIONS
What determines whether AI models cite you
Answer-first structure
Lead every page with a direct answer to the question. AI models extract from the first 30% of content for 44.2% of citations across all platforms.
Factual density
Include specific numbers, dates, named entities, and cited sources. Models verify content against other sources and reward claims backed by data.
Content recency
Content published in the last 30 days is cited 2.1x more often than older content. Perplexity is the most recency-sensitive platform at 82% last-30-days citation rate.
Schema markup
FAQPage, Article, and HowTo schema help AI models understand content structure. Pages with FAQPage schema see 34% higher extraction rates in ChatGPT responses.
llms.txt presence
An llms.txt file tells AI crawlers which pages matter most. Sites with llms.txt are 2.8x more likely to have their key pages cited across platforms.
Entity clarity
Clear brand signals (Wikipedia, Wikidata, LinkedIn) help models identify and trust your domain. Sites with verified Knowledge Graph entries cite 47% more often.
// WHAT THE CHECKER REPORTS
Per-model citation breakdown for every AI platform
Citation presence by platform
Whether your site appears in each model's responses for queries relevant to your domain. Reported per model with citation count and frequency.
Citation context and format
How each model uses your content: direct quote, paraphrased attribution, or linked reference without naming your brand. Format varies significantly by platform.
Competitor comparison
Which competitors appear instead of you on each platform, and how often. The cross-platform competitor gap reveals where your content is weakest.
Content gap analysis
Specific queries where your content should be cited but is not, organized by platform. Each gap includes a recommendation for closing it.
Cross-platform score
Your aggregate AI Visibility Score across all 4 platforms (0-70 scale), benchmarked against 318 sites in your industry.
GeoXylia makes real API calls to each AI platform and reports what they actually return. No heuristics, no approximations.
Compare your score across all platforms or run a Perplexity-specific check.
// PLATFORM COMPARISON
ChatGPT, Perplexity, Gemini, and Claude each cite differently
Only 11% of domains are cited by both ChatGPT and Perplexity. A site that ranks well on one platform can be invisible on another because each model uses different retrieval criteria.
ChatGPT leans heavily on entity authority and FAQ schema. Pages with FAQPage schema see 34% higher extraction rates. Perplexity favors recency most aggressively (82% of citations from the last 30 days). Gemini prioritizes factual density and structured data. Claude rewards content with clear sourcing and verifiable claims.
Checking one platform tells you almost nothing about your performance on the others. A comprehensive AI citation checker must cover all four to give you an accurate picture.
// FAQ