Mention rate
Updated 2026-09-15
Mention rate is the share of valid, sampled AI answers in which a brand is mentioned at all. It is the base rate of AI visibility: before position, sentiment or citations mean anything, the brand has to appear.
How it is calculated
Per prompt and engine, a mention score is the number of answers that mention the brand divided by the number of valid answers for that prompt. The reported mention rate is the mean of those per-prompt scores, so a prompt sampled five times does not outweigh one sampled twice. Answers that failed, or where the surface never appeared, are excluded from the denominator rather than counted as misses.
Worked example (illustrative numbers)
Three prompts, three samples each on one engine. Prompt A mentions the brand in 2 of 3 answers (0.667), prompt B in 0 of 3 (0), prompt C in 3 of 3 (1.0). Mention rate = (0.667 + 0 + 1.0) / 3 ≈ 0.556 — not 5/9, which would let the most-sampled prompt dominate.
Common mistakes
- Averaging raw answer counts instead of per-prompt scores, which silently weights prompts by how often they were sampled.
- Counting provider errors as non-mentions, which invents a visibility problem out of an API outage.
- Reporting mention rate without prompt coverage: a brand can hold 0.5 mention rate on three prompts while being invisible on the other twenty-seven.
Frequently asked questions
- How many samples does a mention rate need?
- Enough that a single lucky or unlucky answer does not move the number visibly. Three samples per prompt per cycle is a common floor; fewer produces a rate that swings between cycles for reasons that have nothing to do with your content.
- Does a mention have to be positive to count?
- No — mention rate counts appearance, not tone. Sentiment is measured separately on the answers that do mention the brand, precisely so that a critical mention is not silently averaged into a visibility number.
