When a potential customer asks ChatGPT "Who is the best accountant in my city?" or tells Perplexity "Find me a reliable plumber near me," does your business come up? For most business owners, the honest answer is: they have no idea.
This is a new dimension of visibility. It did not exist two years ago. Today it is growing fast enough that an entire category of tools has appeared to track it. We analysed 10 of them.
The findings are striking. AI search is not a niche curiosity. Rank.ai, which tracks AI search traffic for its clients, reports that visitors arriving via AI search convert at 4.4 times the rate of traditional Google visitors. That is their own client data, so the exact multiple varies by industry. And an entirely new set of factors determines whether your business appears in those AI-generated answers.
Enter your business type and city. Copy each prompt into the corresponding AI engine and track whether you are mentioned.
A new channel, not an extension of SEO
AI visibility is a distinct channel with different rules, not an extension of traditional SEO. Where SEO relies on backlinks and page-level ranking signals, AI visibility depends on entity authority built across multiple data sources. Where search engines rank individual pages, AI engines synthesise information from many sources and generate a recommendation. The ranking factors, the measurement tools, and the optimisation tactics are all different.
In traditional SEO, you optimise your website and build backlinks. In AI visibility, you build entity authority across multiple data sources: your Google Business Profile, your reviews, your directory listings, your website's structured data, and the third-party content that mentions you. AI engines do not crawl and rank pages the way Google does. They synthesise information from multiple sources and generate a recommendation. If those sources are inconsistent, incomplete, or missing, the AI simply recommends someone else.
Pages that rank well in organic search frequently appear in AI Overviews, according to Authoritas research on organic-to-AI correlation. But the reverse is not guaranteed. A business can have poor organic rankings and still appear in AI answers if it has strong entity signals elsewhere. And a business can rank well in organic search and be completely absent from AI responses if its structured data and entity authority are weak.
The non-determinism problem
AI language models are non-deterministic by design, meaning the same prompt can produce different answers on consecutive runs. Your business might appear in one ChatGPT response and be absent from the next. This inherent variability makes single-check measurement unreliable and forces any credible tracking approach to run repeated queries and report consistency as a percentage rather than a binary yes or no.
AI language models are non-deterministic by design. The same prompt can produce different results on consecutive runs. Your business might appear in one response and be absent from the next. That behaviour is inherent to the technology.
This creates a measurement challenge. A single check is not reliable. The best tools we analysed handle this by running the same query 3 to 5 times per engine and reporting a consistency percentage. A business that appears 4 out of 5 times has 80% consistency. One that appears once out of five has 20%. Both numbers are more meaningful than a simple yes-or-no check.
Peec AI, which tracks AI citation patterns for its clients, reports that 40 to 60% of cited domains change monthly across AI engines. AI answers are volatile. Tracking visibility once and assuming it holds is like checking the weather once and assuming it stays the same for a month.
The BTR Signal Score asks AI assistants, with web search switched on, the question a real customer would ask, built from the searches the owner confirmed: "Who's a good pool cleaner in Centurion?", not "top pool companies". A generic question gets a generic answer.
The 5 AI engines that matter
Each engine has its own data sources, its own weighting, and its own output style. Perplexity always cites sources with links. ChatGPT sometimes names businesses without linking. Gemini draws heavily from Google's own knowledge graph. Copilot integrates Bing's index. Claude draws from its training data and any retrieval-augmented sources. A business might be cited by Perplexity and completely absent from Copilot.
This is why checking one engine is not enough. A proper AI visibility check queries all five and reports per-engine results.
What we learned from 10 AI visibility tools
Five tools stood out across our analysis of 10 AI visibility platforms. Profound offers the deepest analytics with brand mention and citation tracking. Otterly.ai leads in accessibility for smaller teams with over 40,000 users. Peec AI treats citation volatility itself as a trackable metric. HubSpot's free AI Search Grader provides a 100-point entry-level score. Authoritas delivers enterprise-grade multi-frequency tracking alongside traditional SEO reporting.
| Tool | Primary Function | Strength | Limitation |
|---|---|---|---|
| Profound | AI search analytics | Deepest brand mention, citation, and sentiment tracking | Plans start at $99/month, scaling to $399 |
| Otterly.ai | AI visibility tracking | Best balance of depth and usability for smaller teams | Trades analytical depth for accessibility |
| Peec AI | Citation volatility analysis | Tracks domain churn rates and categorises source types | Priced at $100 to $505 per month |
| HubSpot AI Search Grader | Free AI visibility scoring | Most accessible entry point with 100-point scale | Snapshot only, not ongoing monitoring |
| Authoritas | Enterprise AI visibility tracking | Multi-frequency tracking, separates branded from unbranded queries | Built for enterprise teams, priced $95 to $249 per month |
Profound: the deepest analytics platform
Profound raised $96 million in funding to build what they describe as the analytics platform for AI search. It tracks brand mentions, citation URLs, sentiment, and competitive positioning across multiple AI engines. We rated its analytical depth as the highest of any tool in this category. Its pricing reflects that depth: plans start at $99 per month and scale to $399 for enterprise features.
Otterly.ai: the accessibility leader
Otterly.ai has over 40,000 users and focuses on making AI visibility tracking accessible to smaller teams. It tracks daily visibility across engines, reports consistency percentages, and shows which competitors appear when you do not. We rated its balance of depth and usability as the best in the group for businesses that do not have a dedicated marketing team.
Peec AI: the volatility analyst
Peec AI treats volatility itself as a metric. Its research shows that 40 to 60% of cited domains change monthly, and it uses that instability data to frame the need for ongoing monitoring. It categorises sources by type (editorial, corporate, user-generated, institutional) so businesses can see what kind of content earns AI citations in their category.
HubSpot AI Search Grader: the free entry point
HubSpot built a free AI Search Grader that scores businesses on a 100-point scale across five weighted dimensions: Sentiment (40%), Presence (20%), Recognition (20%), Share of Voice (10%), and Competition (10%). It is the most accessible entry point for a business owner who wants a quick read on their AI visibility without subscribing to a paid platform.
Authoritas: the enterprise tracker
Authoritas provides multi-frequency tracking (daily, weekly, monthly) and separates branded from unbranded queries. It is built for teams that need to report AI visibility alongside traditional SEO metrics. We rated it as the best option for businesses already using enterprise SEO tools and wanting to add an AI visibility layer.
What makes a business visible to AI
After mapping 44 checks across all 10 tools, we identified six factors that consistently correlate with higher AI visibility: entity consistency across data sources, review volume and quality, structured data on your website, AI crawler access in robots.txt, content citability through clear claims and supporting data, and third-party validation from authoritative external sources. Businesses strong in all six appear most reliably in AI-generated answers.
1. Entity consistency
AI engines cross-reference multiple data sources to verify business information. If your Google Business Profile says one thing, your website says another, and your directory listings say a third, the AI engine has low confidence in any of them. Consistent name, address, phone number, category, and description across all sources builds the entity authority AI engines need to make a recommendation.
2. Review volume and quality
Review content (not just star ratings) provides the raw material AI engines use to describe a business. If customers frequently mention "quick turnaround" or "fair pricing" in reviews, those phrases may appear in AI-generated descriptions.
3. Structured data on your website
Schema markup (LocalBusiness, FAQ, Product, Organization) makes your website machine-readable. AI engines can extract structured facts directly from schema markup, rather than trying to interpret unstructured text. A business with complete schema markup is significantly more parseable by AI crawlers.
4. AI crawler access
Many websites accidentally block AI crawlers in their robots.txt file. GPTBot, ClaudeBot, PerplexityBot, and Google-Extended each have their own user agent. If your site blocks them, AI engines cannot independently verify your website's claims. This is a binary gate: blocked means invisible.
5. Content citability
AI engines are more likely to cite content that makes clear claims, supports them with data, and uses structured formatting (headings, lists, tables). Content that reads like a press release or a generic service description is less citable than content that answers specific questions with specific facts.
6. Third-party validation
AI engines trust businesses that are mentioned by other authoritative sources. Press coverage, industry directory listings, review platforms, and citations in articles all build the third-party evidence that AI engines use to decide whether a business is recommendation-worthy.
What the 10 AI visibility tools do not cover
Despite the rapid growth of this category, we found three significant gaps across all 10 tools. No tool tests with prompts specific to a business's actual service and location. No tool connects AI visibility to the other channels that drive it, such as directory listings, reviews, and schema markup. And no tool is priced for the local business owner who needs ongoing monitoring rather than a one-time snapshot.
No tool tests with prompts specific to a business's actual service and location. They use generic category queries. The difference matters. "Best plumber in [city]" and "emergency plumber in [suburb] available now" trigger very different AI responses.
No AI visibility tool we tested connects its results to your other channels. AI visibility exists in isolation. But the reasons a business is invisible to AI often trace back to a wrong GBP category, inconsistent directory listings, too few reviews, or missing schema markup on the website. Those are problems in other channels, with downstream effects on AI visibility.
No tool is priced for the local business owner. Profound costs $99 to $399 per month. Peec AI costs $100 to $505 per month. Authoritas costs $95 to $249 per month. HubSpot's free grader is a snapshot, not ongoing monitoring. The local business owner who wants to track whether AI is recommending them has limited affordable options.
A customer who arrives from an AI answer has already asked a question and been given your name. That makes AI visibility a present revenue factor. A business that AI answers never name cannot see the enquiries that went elsewhere.
What the BTR Signal Score checks for AI visibility
The BTR Signal Score asks AI assistants, with web search switched on, the question a customer would ask for your service and area. The free report asks one question and shows who they named and whether you were among them. The full report asks for every search you chose and lists the websites they used to choose, and which of them you are missing from.
Your own website matters more than you might expect. In the businesses the BTR Signal Score checked, where an AI assistant recommended the business, it linked to the business's own website. Where an assistant did use a site you are missing from, the report says so.
That cross-channel view is the difference between "you are not showing up in AI search" and "here is exactly why, and here is what to change in which order to fix it."
Check if AI is recommending your business across all five engines, with the specific queries your potential customers would ask.
About the author
Will Barnardt founded BTR Consult after 15+ years running revenue operations. This post is part of BTR Consult's research into what decides whether customers find, choose and contact a business.
Frequently asked questions
How do I check if AI is recommending my business?
Ask ChatGPT, Perplexity, Gemini, Copilot, and Claude a buyer-intent question like "Who is the best [your service] in [your city]?" and see whether your business is mentioned, recommended, or cited. Do this 3 to 5 times per engine because AI answers are non-deterministic. Tools like Otterly.ai, Profound, and HubSpot AI Search Grader automate this process and track changes over time.
What is AEO and why does it matter?
AEO stands for Answer Engine Optimisation. It is the practice of making your business visible in AI-generated answers, not just traditional search results. It matters because early vendor data, including client benchmarks from rank.ai, shows that AI visitors convert at multiples of the rate of traditional Google visitors. As more people use ChatGPT, Perplexity, and Google AI Overviews to find businesses, AEO is becoming as important as SEO.
How do I get my business cited by AI?
Three foundations matter most. First, make your website machine-readable with complete schema markup, clean HTML structure, and an llms.txt file. Second, build entity authority through consistent information across your Google Business Profile, directories, and social media. Third, accumulate reviews: review text gives AI engines the words they use to describe what you do. Content that is structured, factual, and frequently cited by other sources is more likely to be referenced by AI engines.
Why does ChatGPT give different answers each time?
AI language models are non-deterministic by design. The same prompt can produce different answers on consecutive runs. This means a business might appear in one response and be absent from the next. The best tracking tools handle this by running the same query 3 to 5 times per engine and reporting a consistency percentage. A business that appears 4 out of 5 times has 80% consistency, which is a more reliable metric than a single yes-or-no check.