Answer share is the term most AEO platforms use for what AskRanker calls brand mention rate or share of voice in AI search. The vocabulary across vendors is fragmented in 2026 — answer share, brand share, share of voice, mention frequency, citation share, AI visibility — and the differences matter when comparing dashboards. This is the canonical mapping.
Answer share, formally
Answer share is the percentage of AI-generated answers (across a defined question basket and engine set, sampled to wash out variance) that name your brand. It is mathematically identical to brand mention rate over the same basket. The difference is rhetorical: 'answer share' frames it as competitive market share, 'mention rate' frames it as a per-question probability. Public dashboards usually use 'answer share' for executive summary slides; technical reports use 'mention rate.'
How vendors compute it differently
Three differences in implementation worth knowing. Sample size: some platforms sample once per question per day (high noise), others sample 25 to 50 (low noise). Engine coverage: some report ChatGPT only, some include four to nine engines. Question basket: some let you pick, some impose a generic basket that may not match your category. Comparing answer-share numbers across vendors without confirming all three is a comparison of dashboards, not of the underlying metric.
The metrics commonly conflated with answer share
Citation share is different — it is the percentage of answers where your URL appears in the source list, distinct from whether your brand was named in the answer text. Brand share usually means answer share, but a few vendors use it to mean share of mentions weighted by sentiment. Mention frequency typically means raw mention count rather than rate. AI visibility is a marketing term that loosely means 'all of the above combined,' usually computed as a vendor-specific weighted index.
What to report internally
Pick one term and stick to it. AskRanker reports 'mention rate' (per question, per model) and 'share of voice' (the basket-weighted rollup), with confidence intervals on both. Inside our customers' organizations, we recommend translating once to whatever term leadership already uses ('answer share' is the most common in SaaS) and reporting that single rollup at the executive level, while keeping the per-question detail for the operating team.
Cross-vendor comparison gotchas
Two warnings. First, never compare absolute answer share between two vendors without confirming sample size, engine set, and question basket are identical — they almost never are. Second, do not assume rank order is preserved across vendors: a brand at position 2 in vendor A's ranking can be at position 6 in vendor B's, because the question baskets weight different sub-categories differently. Trust your in-house basket and engines, and use vendor numbers as background context only.