Share of Voice (SOV) is one of the most strategic metrics in AEO. It measures your brand’s mention frequency relative to competitors when AI engines answer queries in your space. It pairs naturally with competitor benchmarking and your overall visibility score.
What is Share of Voice?
Share of Voice is your brand’s share of the mentions in a competitive set — how much of the conversation is you rather than the rivals you are measured against.
Counting mentions is a deliberate substitute for counting positions, because a generated answer has no ranked list to take a position from. The academic work makes the same move: GEO: Generative Engine Optimization had to define its own impression metrics for generative engines — weighted by how prominently a source appears in the answer text — rather than reuse the click- and rank-based metrics search inherited.
The formula:
Your Share of Voice = Your Mentions ÷ (Your Mentions + Competitor Mentions) × 100
The denominator is the part to get right, and it is narrower than the phrase “share of voice” suggests. In LLM Metrix it counts only the competitors configured on the project — every other brand an answer happens to name is discarded before the ratio is formed. So this is share-versus-your-tracked-list, not share of your category.
That is a deliberate design choice rather than an approximation. Answers vary wildly in how many brands they name, and counting all of them makes the metric a measure of answer length: a genuine 3-of-7 position collapses to 3-of-43 the moment one engine returns an exhaustive vendor list, and your number falls without anything about your brand changing.
Two consequences worth carrying:
- Your competitor list is a measurement instrument, not a wishlist. Add a rival and your SOV falls; leave one out and it is flattered. Choose the set that represents the decision your buyer is actually making, then leave it alone — changing it mid-quarter breaks the comparability of your own trend.
- Our figure will read higher than a category-wide SOV from another tool. That is the denominator, not a discrepancy to chase.
Example
For 100 queries about “AI productivity tools,” engines mention your brand 25 times, Competitor A 18 times and Competitor B 15 times, plus 42 mentions of brands you have not listed as competitors.
Your SOV = 25 ÷ (25 + 18 + 15) = 43%
Those 42 other mentions are not in the denominator. Read the number as “of the mentions among the three brands I am tracking, 43% are mine” — a statement about your competitive set. The separate question of how often you appear at all is mention rate: your brand named in 25 of 100 answers is a 25% mention rate. Both are useful and they answer different questions, which is why the dashboard reports them side by side.
Why Share of Voice Matters
1. Market Position Indicator
Your SOV shows your competitive position in AI responses:
- High SOV (40%+): You’re dominating AI conversations
- Medium SOV (20–40%): You’re competitive but not leading
- Low SOV (<20%): You have significant growth opportunity
Calibrate those bands against the size of your tracked set, because the denominator scales with it. Against two competitors, parity is 33% and 40% is a genuine lead; against nine, parity is 10% and 40% would be dominance. Read the bands as shorthand for a set of three or four, and adjust from there.
2. Revenue Impact
In traditional marketing, higher share of voice has long been associated with stronger brand awareness, demand, and pricing power. The same logic carries into AI answers: the more often you’re the brand named in your category, the more mindshare you capture at the moment of decision.
3. Growth Predictor
SOV trends predict future market share growth:
- Rising SOV indicates growing dominance
- Falling SOV signals losing position to competitors
- Stable SOV indicates market equilibrium
Share of Voice vs Market Share
| Metric | Definition | Lag Time |
|---|---|---|
| Share of Voice | Percentage of mentions in AI responses | Real-time to days |
| Market Share | Percentage of actual sales/revenue | Weeks to months |
SOV tends to lead market share — growing SOV often precedes revenue growth by weeks or months.
Share of Voice by AI Engine
Different engines may show different SOV due to different training data, ranking algorithms, sourcing approaches, and regional variations.
Example: Project Management Tools
| Engine | Your SOV | Competitor A | Competitor B |
|---|---|---|---|
| ChatGPT | 45% | 33% | 22% |
| Claude | 46% | 21% | 33% |
| Perplexity | 50% | 29% | 21% |
| Gemini | 34% | 38% | 28% |
Each row sums to 100% because the three tracked brands are the whole denominator — which is the clearest illustration of what the metric is measuring. Losing share on Gemini here means Competitor A took it, not that the category grew.
Monitor SOV by engine to identify where you’re strongest and where to focus. In LLM Metrix that breakdown lives on the Competitors page — a brand × engine matrix showing, for each engine, how much of the naming was you and how much was each competitor. Three properties of it are worth knowing before you build a routine on it:
- It is point-in-time. The matrix is derived from the scan’s own answers; the frozen per-scan rollup stores one whole-scan share-of-voice figure and no per-engine breakdown, so per-engine SOV exists for a scan you have open and there is no per-engine SOV series. The trend line you can read is your overall share against the whole competitor set.
- The headline SOV is a whole-scan figure, not an average of the per-engine percentages. It takes all mentions across every engine into one ratio, so an engine that answered more prompts contributes proportionally more.
- An empty cell and a 0% cell mean different things. A competitor that scored 0% on an engine that named somebody was measured and lost; an engine that named nobody at all has no denominator and shows a dash. The table renders those differently on purpose.
Multi-engine monitoring is the per-engine view of a different set of metrics — visibility score, mention rate, average rank and sentiment — and is where you go for those.
Share of Voice Benchmarks
Emerging Market (<$1B market)
- Market Leader: 35–50% SOV
- #2 Position: 20–35% SOV
- #3 Position: 15–25% SOV
Established Market ($1–10B market)
- Market Leader: 25–40% SOV
- #2 Position: 15–25% SOV
- #3 Position: 10–20% SOV
Mature Market (>$10B market)
- Market Leader: 15–30% SOV
- #2 Position: 10–20% SOV
- #3 Position: 5–15% SOV
Growing Your Share of Voice
Strategy 1: Increase Your Mentions — Publish more content addressing your query set. Build authority through backlinks. Increase brand mentions across the web. Create more linkable assets.
Strategy 2: Improve Mention Quality — Move from “listed” to “prominent” mentions. Increase “first mention” position. Build more citations of your content. Improve brand sentiment.
Strategy 3: Out-Invest Competitors — Create more content, build more authority, establish more visibility, and dominate the conversation.
Strategy 4: Target Underserved Queries — Find queries where you’re weak. Create targeted content for those queries. Build specific authority for those topics, drawing on building authority for AEO. Move mentions in those queries.
Share of Voice Action Plan
Month 1: Establish Baseline — Define your competitor set and query set, the two inputs competitor benchmarking needs before it can report anything. Calculate current SOV across all engines. Identify where you’re weak vs competitors.
Month 2–3: Content Push — Create content targeting high-volume queries. Publish assets that attract links. Build authority through citations.
Month 4–6: Optimization — Shift mentions from “listed” to “prominent.” Increase first mention frequency. Build competitive differentiation.
Month 6+: Domination — Defend and grow your #1 position. Outpace competitor growth. Expand to adjacent query clusters.
Share of Voice is your most actionable metric for competitive positioning in the AI era. Track it obsessively and use it to guide your strategy.
Frequently Asked Questions
What is share of voice in AI search?
Share of voice in AI search is the percentage of AI responses that mention your brand compared to competitors, across a defined set of queries or topics. It tells you how much of the AI “conversation” in your category you own.
How is AI share of voice calculated?
Run a representative set of category queries across AI engines, count how often each brand is mentioned, and express your mentions as a percentage of all brand mentions. Weighting by mention prominence (first vs. listed) gives an even sharper picture.
How do I increase my share of voice?
Win mentions on queries where competitors currently dominate by building stronger authority and citable content on those topics, then expand into adjacent query clusters. Note that this is a read you do prompt by prompt: results are reported per prompt and per engine, and nothing rolls scan results up by topic cluster — prompt discovery groups its suggestions into clusters before you pick them, but no cluster-level share-of-voice figure exists to sort by.
Is share of voice better than a visibility score?
They answer different questions. Share of voice is inherently competitive — your slice relative to rivals — while a visibility score summarizes your absolute presence. Use them together: visibility score for your own trend, share of voice for competitive positioning.