Also known as: Citation rate, AI citation rate, Citation frequency
The citation rate is the central visibility metric for generative engine optimisation: the share of AI answers to a given search phrase in which a specific domain is cited as a linked source (citation). Formally: Citation Rate = number of answers citing the domain ÷ total number of queries × 100. Because LLM answers are not deterministic (the same query produces slightly different answers), the citation rate is averaged across several repetitions — a majority vote (for example three repetitions per phrase) is the standard approach.
Useful GEO reports measure the citation rate separately for each engine, because answering behaviour varies considerably between them: ChatGPT often cites 1–3 sources per answer, Perplexity 4–8, Gemini in AI Overviews 2–5, and Claude tends towards 1–3. A domain may have a citation rate of 40 % in one engine and 5 % in another — which calls for different optimisation levers. An aggregated ”citation rate across all engines” is usually misleading and hides important differences.
An important distinction in reporting: a citation is a linked source (a clickable outbound link). A mention is a textual reference to the brand or domain without a link. Mentions contribute to brand authority but generate no direct click traffic. Good tracking records both separately — citations as a traffic lever, mentions as a brand-building indicator.
Example: A B2B SaaS provider tracks its citation rate for 12 prioritised money queries across 5 engines with a threefold majority vote = 12 × 5 × 3 = 180 LLM queries per run, carried out weekly. Starting citation rate: 18 % averaged across all engines. After a four-month optimisation roll-out (Schema.org sameAs, clear H2 structures, FAQ sections, visible author bylines, Wikidata entity): aggregated citation rate at 42 %, with peaks of 67 % in Perplexity and 51 % in AIO. AI referral traffic increased fivefold over the same period.
Citation rate tracking in Rankmio
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