How ChatGPT, Claude, Perplexity & Gemini choose sources
Each engine retrieves candidates via search partners (Bing, Google, in-house crawlers), re-ranks with an LLM, and cites the top few. Selection weights: relevance, authority, freshness, structural clarity.
What makes content citable by AI
- A quotable one-sentence answer.
- Verifiable stats with sources.
- Neutral, non-marketing tone.
- Author credentials visible on the page.
Factual density and credibility
AI models prefer paragraphs that pack multiple attributed facts. Vague opinion pieces rarely get cited.
Formatting for AI extraction
Short paragraphs, clear H2 questions, definition lists, and consistent brand naming all boost extraction confidence.
Building brand mentions across authoritative sites
Digital PR, podcasts, industry reports, and Wikipedia mentions bond your brand to its category in model memory.
Monitoring AI citations
Use tools like Otterly, Peec.ai, Profound, or scripted daily query panels to log which URLs get cited across engines.
The future of AI search attribution
Expect richer citation UIs, per-passage credit, and monetized referral programs from AI engines as they mature.
Key terms
- RAG
- Retrieval-Augmented Generation — LLMs fetching live sources before answering.
- Citation share
- Your share of citations across a set of tracked prompts.
- Prompt panel
- A recurring set of queries used to monitor AI answers.
Put this into practice, automatically
Eternity combines LLMO scoring, GEO optimization and citation-ready blog structure — every piece of content is shipped in the format AI engines cite.
Optimize with Eternity