/terms/attribution-rate
Attribution rate
Citation status
Last checked 2026-05-21
What is attribution rate?
Attribution rate measures how often an AI search engine credits a specific source when answering queries about a topic. The formula is straightforward: sample N representative queries, record whether each AI response cites the target source, then divide. A high attribution rate (commonly >20% across a sampled topic) suggests the source has become a citation-default — the engine reaches for it reliably when the topic comes up.
Status in 2026
The de facto KPI for GEO programs. No standardized formula yet — practitioners differ on whether to count any mention (broadest), inline citation with a link (narrower), or top-three cited sources only (strictest). Profound, Otterly, and similar tools each implement slightly different definitions, which makes cross-tool comparison hazardous.
How it relates to other concepts
- Companion to citation match rate, which counts only linked citations.
- Output frame of cite-ability — cite-ability is the input property; attribution rate is the measured outcome.
- Distinct from citation share, which compares relative citation between competing sources.
- Direct success metric for Generative Engine Optimization programs.
Related terms
FAQ
- Is attribution rate the same as citation rate?
- Often used interchangeably. Strict definitions: attribution rate counts any source mention; citation rate counts only inline citations with linked attribution. The distinction matters for measurement design but most practitioners treat them as synonyms.
- How many queries do I need to sample for a meaningful attribution rate?
- Industry minimum is ~30 queries per topic. Lower counts produce noisy estimates that aren't actionable. Practitioners with budget run 100+ queries per topic refreshed weekly.
- Which AI engines report attribution data natively?
- None yet. Bing Webmaster Tools surfaces some 'AI search' impression data but does not break down attribution rate per source. Measurement requires third-party tools (Profound, Otterly) or manual probing.