The average company we've tested scores 31 out of 100 on AI visibility. That means most brands are nearly invisible to ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews when users ask for recommendations. We built Be Recommended to measure exactly that.
AI visibility monitoring is a new category. It answers a question that SEO rank tracking was never designed for: when someone asks an AI engine "what's a good tool for X," does it recommend your brand?
What AI visibility monitoring actually is
Traditional rank tracking checks where your site appears in Google's ten blue links for a given keyword. AI visibility monitoring does something fundamentally different: it sends real prompts (the kind of questions users actually ask AI engines) and checks whether your brand appears in the response, how it's positioned, and what the AI says about you.
The unit of measurement shifts from "keyword position" to "prompt mention." We fan out 50+ real-world prompts across five engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) and score the result 0 to 100.
| SEO Rank Tracking | AI Visibility Monitoring | |
|---|---|---|
| What it measures | Position in search results for keywords | Whether AI engines recommend your brand in response to prompts |
| Input | Keywords | Real-world prompts (the questions users ask) |
| Engines | Google (sometimes Bing) | ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews |
| Output | Position number (1-100+) | Recommendation score (0-100) + competitor comparison + action plan |
| What it tells you | Where you rank for a search term | Whether you're being recommended when someone asks for help |
| Optimization target | Higher position for keyword | Becoming the default recommendation |
Why position tracking doesn't cover it
When a user types "best CRM for small teams" into Google, you need to rank on page one. When they ask the same question to ChatGPT or Perplexity, there's no page one. The AI either mentions you or it doesn't. And if it does, the framing matters. Being mentioned as "an option worth considering" is not the same as being named the top recommendation.
Search engines retrieve pages. AI engines synthesize answers. The same content that ranks well in search may be invisible to language models, and content that never ranked for any keyword can become a top AI recommendation if it's structured and attributed correctly.
From what we've measured across our portfolio at Inithouse, products with strong third-party mentions and structured comparison content score 60 to 80+. Products that rely only on their own website tend to score below 20, even if their SEO is solid.
How prompt fan-out replaces keyword lists
In rank tracking, you define a keyword list: "project management software," "best task manager 2026," and so on. The tracker checks your position for each.
In AI visibility monitoring, we define prompt sets: natural-language questions that a real user would ask an AI assistant. "What's a good tool for tracking AI visibility?" or "Which services monitor how ChatGPT recommends my brand?" or "Compare AI recommendation monitoring tools."
The prompt set matters because different phrasings trigger different model behaviors. A prompt that includes your category term might surface your brand. A prompt that uses a competitor's name might not. Be Recommended runs 50+ prompts per report, across all five engines, to produce a score that reflects your actual visibility, not just your best-case result on one engine with one prompt.
What a score of 31 actually means
We've found that the average company scores around 31. That doesn't mean 31% visibility. It's a composite index weighing mention frequency, positioning (first mentioned vs. last), sentiment, and competitor displacement across all prompts and engines.
A score of 31 typically means: some engines mention you for some prompts, but inconsistently. You might appear in Perplexity for one prompt phrasing and be completely absent from ChatGPT for the same question.
Top brands in established categories score 80+. They show up consistently across engines, get mentioned early in responses, and often get recommended by name rather than just listed.
The gap between 31 and 80 is the difference between occasionally appearing in an AI response and being the default recommendation when someone asks for help in your category.
The action plan side
Scoring is one half. The other half is telling you what to change. Each Be Recommended report includes a prioritized action plan: which engines you're weakest on, which prompt types miss you entirely, and what your competitors do that makes them more visible.
We've seen brands move from 25 to 55+ within weeks by addressing two or three specific gaps, usually around structured data, third-party mentions, and comparison content. The measurement tells you where to focus instead of guessing.
We build and measure a growing portfolio of products at Inithouse. Be Recommended came from noticing that our own products kept scoring differently across AI engines and wanting to understand why.
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