AI Search Metric
Citation share
Also known as: SOV in AI, answer share, share of citations
The proportion of times a domain or page is cited inside AI-generated answers (ChatGPT, Claude, Gemini, Perplexity, AI Overviews) across a tracked prompt set. The AI-era equivalent of share-of-voice and the metric most predictive of branded discovery in 2026.
What it is
Citation share is the proportion of times a given domain or page is cited inside AI-generated answers across a tracked set of prompts. It captures how often a model reaches for your content as a source relative to all sources it cites.
Why it matters
It is the AI-era equivalent of share-of-voice and, in 2026, the metric most predictive of branded discovery, because being cited is what puts a brand in front of users who never see a traditional results page.
How it works
Practitioners run a fixed prompt panel across models, log every citation, and calculate the share each domain holds, then lift it by publishing source-grade content that models prefer to quote and attribute.
When it applies
Track it continuously for any category where buyers ask AI assistants for recommendations or comparisons.
Examples
- A SaaS vendor cited in 40 of 100 buyer-intent prompts holds a leading citation share in its category
- A publisher comparing its citation share against three rivals across the same prompt set each month
- A brand watching its share rise after a cluster of well structured comparison pages is indexed
How it is measured
- Citations of your domain divided by total citations across the prompt set
- Citation share per model (ChatGPT, Claude, Gemini, Perplexity)
- Trend in citation share week over week
- Citation share for branded vs unbranded prompts
Related terms in AI Search Metric
- AI-referred trafficSessions referred from ChatGPT, Claude, Gemini, Perplexity, Copilot, and other LLM surfaces. Often under-counted in standard analytics because referrers are stripped or labelled as direct.
- Answer attribution rateThe proportion of AI answers that explicitly link back to source pages versus those that summarise without attribution. Attribution rate varies materially by platform and query type.
- Bounce-back rate (AI surface)The rate at which users return to the SERP or refine the prompt after seeing an AI Overview. Google's internal signal that an Overview failed, high bounce-back is associated with Overviews being silently removed for that query cluster.
- Brand mention rateThe frequency at which an LLM mentions a brand by name in answers across a prompt set, with or without citation. Brand mentions without citation are an early indicator of model-internalised brand awareness.
- Citation depthHow early in an AI-generated answer a source is cited. Earlier citations correlate with higher click-through from AI surfaces and stronger user trust signals.
- Citation diversity indexThe number of distinct domains an LLM cites across a prompt set, normalised by prompt count. Falling diversity in a category signals consolidation, and a closing window for new entrants.