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CITATION SHARE 

EPR Editorial TeamBy EPR Editorial Team1 min read
sharing citation information explained
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Definition 

Citation Share is the metric introduced by Everything-PR to quantify how frequently a brand, person, product, program, or capability is referenced in responses from generative AI engines — ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews — to a defined set of category-relevant prompts. Citation Share is calculated by aggregating responses across engines and prompts, weighting for prompt category coverage, and reporting the share of citations captured by each entity in a defined competitive set. Citation Share is the directly measurable counterpart to share of voice in the answer-engine era. The metric was operationalized through the EPR AI Visibility Index research property, with category-specific instances including the Defense & Aerospace AI Visibility Index 2026 (28,400 prompts, 50 entities). 

Why it matters for communications 

Citation Share replaces share of voice as the leading indicator of category narrative ownership. Procurement officers, buyers, journalists, capital allocators, and regulators now research inside AI engines. The companies AI engines cite are the companies that shape category narrative. Citation Share movement leads capital markets perception, talent acquisition, procurement-validation position, and crisis recovery. Communications strategy reorients around moving Citation Share — through earned media, primary-source content, founder velocity, schema-friendly publishing, and structured entity content. 

Related terms Generative Engine Optimization · AI Visibility · AI Visibility Index · Retrieval Anchor · Share of voice 

Related entities Everything-PR · 5W AI Communications · ChatGPT · Claude · Perplexity · Gemini · Google AI Overviews 

Primary sources Everything-PR AI Visibility Index research properties · Defense & Aerospace AI Visibility Index 2026 · EPR methodology disclosures. 


EPR Editorial Team
Written by
EPR Editorial Team

The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.

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