Jean-Romain
- The best platforms to measure share of voice in AI search are Profound, Peec AI, Otterly, Scrunch, and Semrush's AI toolkit for paid tracking, plus HubSpot's free AI Search Grader to run a first check at no cost.
- LLM Share of Voice is the core metric: (your brand mentions / total brand mentions across tracked prompts) x 100. A share above 15% in your core category signals strong positioning; category leaders reach 25 to 30%.
- Pick a platform on four things: which engines it tracks (ChatGPT, Perplexity, Gemini, Google AI Overviews), whether it separates mentions from citations, competitor benchmarking, and how often it refreshes the data.
- No tool replaces a prompt library. A reliable number comes from 50 to 100 structured prompts run across several platforms, because LLM answers are non-deterministic and a single test tells you almost nothing.
The best platforms to measure share of voice in AI search are Profound, Peec AI, Otterly, Scrunch, and Semrush's AI visibility toolkit on the paid side, with HubSpot's free AI Search Grader as a starting point. Each one runs a set of prompts across ChatGPT, Perplexity, Gemini, and Google AI Overviews, counts how often your brand shows up against competitors, and turns that into a share-of-voice percentage.
The tool is the easy part. The number is only as good as the prompts you feed it and the way you read mentions, citations, and sentiment. This guide ranks the platforms, gives you the formula and the benchmarks, and shows the step-by-step method to build a baseline you can actually report on. It connects to a broader AI SEO strategy built around measurable outcomes, not guesswork.
Best Platforms to Measure Share of Voice in AI Search
Every platform below runs a prompt set across the major AI engines and reports how often your brand appears versus competitors. They differ on engine coverage, whether they separate name mentions from linked citations, how deep the competitor and sentiment analysis goes, and how often they refresh. Here is how the serious options stack up.
1. Profound (broadest coverage, enterprise)
Profound tracks visibility, share of voice, and sentiment across 10 or more AI engines, including ChatGPT, Perplexity, Gemini, Google AI Overviews, Google AI Mode, Copilot, Grok, and Claude. It re-runs each tracked prompt daily and stores every answer as a snapshot, so you can see exactly when and why a number moved. Pricing is custom and aimed at enterprise and multi-brand teams.
2. Peec AI (sentiment and positioning)
Peec AI focuses on clean multi-engine tracking across ChatGPT, Perplexity, Gemini, and Claude, with strong sentiment and positioning analysis. It is the right pick when you care less about raw mention counts and more about how AI frames your brand against competitors.
3. Otterly (mentions plus citations, affordable)
Otterly tracks both brand mentions and link citations across Google AI Overviews, ChatGPT, and Perplexity. Unlike pure model-output tools, it monitors AI search surfaces that pull in live web results, which matters because 95% of AI citations come from third-party pages. Entry pricing starts around $29 per month, so it is the most accessible paid option for small teams.
4. Scrunch (enterprise, multi-brand)
Scrunch covers eight platforms and is built for agencies and enterprises managing several brands at once. Pricing starts higher (from roughly $250 per month) and scales to custom plans.
5. Semrush AI Toolkit (teams already on Semrush)
Semrush bolts AI visibility onto its existing SEO suite, tracking brand presence across AI Mode, ChatGPT, Perplexity, Gemini, and SearchGPT. If your team already lives in Semrush, it keeps traditional and AI share of voice in one place. It also offers a free AI visibility checker to get a first read.
6. HubSpot AI Search Grader (free starting point)
HubSpot's free AI Search Grader benchmarks your brand's share of voice across ChatGPT, Perplexity, and Gemini with week-over-week tracking. It is not deep enough to run a program on, but it is the fastest way to get a directional number before you commit budget.
7. Manual tracking (free, best for your first baseline)
A spreadsheet and 30 minutes a week of manual prompt testing gives you real, actionable data for zero cost. It does not scale, but it forces you to read actual AI answers, which is the single best way to understand how your brand is described before you automate.
| Platform | Engines tracked | Pricing (approx.) | Free option | Best for |
| Profound | 10+ (ChatGPT, Perplexity, Gemini, AI Overviews, Copilot, Grok, Claude) | Custom | No | Enterprise, daily snapshots |
| Peec AI | ChatGPT, Perplexity, Gemini, Claude | Custom | No | Sentiment and positioning |
| Otterly | ChatGPT, Perplexity, Google AI Overviews | From ~$29/mo | No | Small teams, mentions plus citations |
| Scrunch | 8 platforms | From ~$250/mo | 7-day trial | Agencies, multi-brand |
| Semrush AI | AI Mode, ChatGPT, Perplexity, Gemini, SearchGPT | From ~$199/mo | Free checker | Teams already on Semrush |
| HubSpot AI Search Grader | ChatGPT, Perplexity, Gemini | Free | Yes | Quick first assessment |
| Manual | Any platform you test | Free | Yes | Budget-conscious teams, first baseline |
Pricing moves fast in this category, so treat these as ballpark figures and confirm the current plan before you buy. The more important decision is coverage: pick the tool that tracks the engines where your buyers actually ask questions, not the one with the longest feature list.
Why Traditional SEO Metrics Miss AI Search Visibility
Google Search Console shows impressions, clicks, and average position. Those metrics work for traditional search. They do not capture what happens inside an AI-generated answer, which is why a dedicated platform exists in the first place.
Three gaps traditional metrics cannot fill:
- No mention tracking. If ChatGPT recommends your competitor by name but links to a different source, Search Console shows nothing.
- No sentiment data. AI answers describe, compare, and sometimes criticize brands. Traditional tools cannot tell you how your brand is framed.
- No cross-platform view. You might dominate Google AI Overviews but be invisible in Perplexity. Search Console only covers Google.
Research from Otterly shows that 95% of AI citations originate from third-party websites, not brand-owned domains. Your visibility in AI depends heavily on how others describe you across the web, not just what you publish on your own site.
The 5 Metrics That Define AI Search Visibility
Each metric captures a different dimension of how your brand appears in AI-generated answers. Together they give you a complete picture of your GEO and SEO performance.
1. AI Visibility Score (Mention Frequency)
Your AI Visibility Score is the percentage of relevant AI prompts where your brand appears. Track 100 prompts in your category, show up in 35, and your score is 35%. This is your top-level pulse check: trending up means your content and authority are working, trending down means competitors are gaining ground.
2. LLM Share of Voice (Competitive %)
Share of voice is the competitive version of the visibility score. It measures your brand mentions as a percentage of all brand mentions across tracked prompts (the full formula is in the next section). Top brands capture 15% or more across their core query sets; if your SOV is below 10%, competitors are dominating the AI conversation in your category.
3. Sentiment and Positioning
A mention is not always a good mention. If ChatGPT calls your product "affordable but limited in features," that is a different outcome than "the category leader." Track sentiment at the claim level, not just the mention level. A brand can be named five times in one answer with four neutral references and one sharply negative comparison, and the negative claim is what the buyer remembers.
4. Citation Frequency (Linked vs Unlinked)
There is a difference between being mentioned by name and having your URL linked as a source. Linked citations send traffic; unlinked mentions build awareness but do not generate clicks. A high mention rate with a low citation rate means AI knows your brand but does not trust your content enough to link to it. That is a content quality signal.
5. AI Referral Traffic
This is the most concrete metric. GA4 categorizes visits from ChatGPT, Claude, and Perplexity as referral traffic, so you can isolate and measure it directly. AI referral traffic converts at roughly 2x the rate of traditional organic: Perplexity referrals convert at 10.5% versus 1.76% for Google organic. The volume is smaller, but the value per visit is much higher.
| Metric | What It Measures | How to Track | Primary Tool |
| Visibility Score | % of prompts with your brand | Run prompt library across LLMs | Profound, Semrush, manual |
| Share of Voice | Your mentions vs competitors | Compare brand mention counts | Peec AI, Otterly, manual |
| Sentiment | How AI describes your brand | Analyze tone of AI responses | Peec AI, Scrunch, manual |
| Citation Freq. | Linked URLs vs name mentions | Count linked vs unlinked mentions | Otterly, Semrush |
| AI Referral Traffic | Actual visits from AI platforms | GA4 referral source filter | Google Analytics 4 |
How to Calculate AI Share of Voice (Formula and Benchmarks)
AI Share of Voice = (your brand mentions / total brand mentions across all tracked brands) x 100. If AI mentions brands 200 times across your prompt set and your brand appears 50 times, your share of voice is 25%.
What counts as "good" depends on how crowded your category is. Use these ranges as a guide:
- Niche B2B (3 to 5 competitors): leaders capture 40 to 60%, challengers 15 to 30%.
- Mid-market B2B (10 to 20 competitors): leaders 20 to 35%, challengers 8 to 15%.
- Broad consumer (50+ competitors): leaders 10 to 20%, challengers 3 to 8%.
Across most categories, a share of voice above 15% signals strong positioning. Focus less on the absolute number and more on the trend: consistent upward movement over 60 to 90 days is what tells you the strategy is working.
How to Build Your AI Visibility Baseline (Step by Step)
Before you can improve AI visibility, you need to know where you stand. A baseline gives you the reference point for every future optimization.
Step 1: Build Your Prompt Library
A prompt library is a structured set of queries that represent how your customers search in AI platforms. These are not keyword lists; they are full, conversational questions. Organize them into three categories:
- Category prompts: "What are the best [your category] tools?" or "How do I choose a [your service]?"
- Competitor prompts: "Compare [your brand] vs [competitor]" or "Is [competitor] better than [your brand]?"
- Use-case prompts: "What is the best solution for [specific problem your product solves]?"
Start with 50 to 100 prompts. That gives you enough statistical reliability without overwhelming your team. A single prompt test tells you almost nothing, because LLMs are non-deterministic and the same question can produce different answers each time.
Step 2: Select Platforms to Track
Each AI platform behaves differently. The same brand can see citation volumes differ by hundreds of times between one engine and another, so you need cross-platform coverage. Minimum viable coverage:
- ChatGPT (around 60% market share, where most buyer research happens)
- Google AI Overviews (appearing in 25 to 48% of searches)
- Perplexity (highest conversion rate at 10.5%, growing fast)
- Gemini (integrated across Google, Android, and Chrome)
Add Claude, AI Mode, and Copilot if you have the capacity, but the four above cover the majority of buyer-facing AI search.
Step 3: Run Your Initial Measurement
For each prompt on each platform, record whether your brand is mentioned, its position in the response, whether it is linked, and the sentiment of the mention (positive, neutral, negative). You can do this manually: open ChatGPT, Perplexity, and Gemini, run your prompts, and log results in a spreadsheet. It costs nothing and gives you direct insight into how AI describes your brand. To automate, the platforms ranked above run prompts across engines and track changes over time.
Step 4: Score Your Baseline
Calculate your AI Visibility Score and Share of Voice using the formula above, and record the date. This is your starting point. The brands that win AI visibility treat it the way they treat rankings: a number they report on monthly and push in a direction.
Measurement is also what proves the work. For Asset Digital Communication we ran a digital PR campaign engineered for LLM visibility, placements chosen for their probability of being ingested and cited by AI models. The result was 565 total placements, 22M potential reach, and a 25% detection rate on LLMs. Without a measurement framework, that last number does not exist. An AI SEO audit maps your current visibility, finds the gaps, and prioritizes fixes on competitive data.
Free vs Paid: Which Platform Should You Pick?
You do not need an expensive tool to start. Here is the honest decision tree:
- Just getting a number: HubSpot's free AI Search Grader or Semrush's free checker, plus a manual spreadsheet. Zero cost, directional data.
- Small team running a program: Otterly (from around $29 per month) for mentions and citations across the engines that matter most.
- Need sentiment and deep competitor analysis: Peec AI.
- Enterprise or agency, multiple brands, daily data: Profound or Scrunch.
There is no calculator that estimates "the cost of monitoring" for you, because it depends on how many prompts, engines, and brands you track. Start free, prove the metric matters to your buyers, then pay for the cadence and depth you actually need.
What to Do When Your AI Visibility Is Low
Measurement without action is a dashboard exercise. Each metric points to a specific type of fix.
Low Share of Voice: build brand authority. If competitors capture more mentions, AI models do not associate your brand strongly enough with your category. Earn mentions on third-party sites, publish original research, get listed on review platforms, and secure coverage in industry publications. This is exactly where the digital PR campaign above moved the needle.
Low Citation Rate: improve content structure. If AI mentions your brand but does not link to your content, your pages are not structured for extraction. Use clear headings, answer questions directly, include data points, and format content in scannable blocks. Your on-page optimization directly impacts whether AI links to your pages or just mentions your name.
Negative Sentiment: fix your messaging. If AI describes your brand negatively, the source material on the web is shaping that perception. Audit the third-party content that mentions you, then add case studies, reviews, and thought leadership that reframes your strengths.
Low AI Referral Traffic: check platform-specific gaps. If visibility is high but traffic is low, the platforms where you appear might not send clicks. Perplexity and Copilot link sources in 77%+ of responses, ChatGPT links in about 31%, and Claude does not link at all. Prioritize platforms that drive actual visits. The full playbook is laid out in our GEO playbook.
Frequently Asked Questions About AI Search Visibility
Which platform is best to measure share of voice in AI search?
For broad coverage and daily data, Profound is the strongest purpose-built option. For sentiment and positioning, Peec AI. For an affordable start that tracks both mentions and citations, Otterly. If you are already on Semrush, its AI toolkit keeps everything in one place, and HubSpot's free AI Search Grader is the fastest no-cost first read. The best choice is the tool that tracks the engines where your buyers actually ask questions.
How accurate are AI visibility tools if LLM answers are non-deterministic?
A single response is not reliable, which is exactly why these tools run a large prompt set repeatedly and report an average over time. Accuracy comes from volume and cadence, not from any one answer. Judge a tool on how many prompts it runs, how often it refreshes, and whether it shows you the trend rather than a single snapshot.
Can I extract Perplexity responses programmatically to monitor brand presence?
Yes. Perplexity and several engines expose APIs, and most paid platforms (Profound, Peec AI, Otterly) already automate this for you, running prompts and parsing mentions and citations on a schedule. If you build it yourself, respect each provider's terms of service and rate limits, and store the full answer text so you can audit mentions and sentiment later.
How often should I measure AI search visibility?
Run your prompt library weekly or bi-weekly for trend data, and report monthly to executives. Avoid daily measurement: LLM responses fluctuate day to day, and daily data creates noise that hides real trends. The trend line over 30 to 90 days matters more than any single data point.
Can I measure AI visibility without paid tools?
Yes. Open ChatGPT, Perplexity, and Gemini, run your prompts manually, and record mention, position, link status, and sentiment in a spreadsheet. It takes more time but gives you direct insight into how AI describes your brand. HubSpot's free AI Search Grader and Semrush's free AI visibility checker are useful starting points.
Does high AI visibility actually drive revenue?
The early data says yes. AI referral traffic converts at roughly 2x the rate of traditional organic, with Perplexity referrals converting at 10.5% versus 1.76% for Google organic. Brands cited in AI answers are discovered and trusted earlier in the buyer journey, which shortens the sales cycle. The volume is still smaller than Google, but the value per visit is significantly higher.
Want a measured baseline and a plan to move the number? Book a call with Awilix for a free AI SEO and GEO audit, delivered within 24 hours.
