What is AI Visibility?

AI visibility is a metric that is steadily becoming more and more important to companies. As the paradigm shifts from Google Search to various AI engines powered by LLMs, companies are seeing drastic drops in their organic traffic. For many, this is a pipeline that inbound revenue relies on. 

This fundamental change in how customers are finding information is defining a new key metric: AI visibility. AI visibility is a holistic metric that is meant to track the strength of a brand’s pipeline from ChatGPT. While other companies rely on superficial methods like “mention frequency” to track AI visibility, Bear AI takes a far more nuanced approach.

How Bear AI Tracks Visibility

At Bear AI, we measure brand visibility across AI search engines using our proprietary AI Search Score — an internal visibility index that quantifies how often, how prominently, and how positively your brand appears in AI-generated answers.

Unlike traditional SEO metrics that focus on rank or traffic, the AI Search Score focuses on complete AI visibility — how generative search engines like ChatGPT, Gemini, Perplexity, and Claude perceive, cite, and represent your brand.

Here’s how the AI Search Score breaks down:

Each factor is normalized on a 0–100 scale and weighted to generate your overall AI Search Score.
A score of 80+ suggests your brand is a trusted, frequently cited authority in your domain, while below 50 signals limited visibility and retrieval.

This score is how Bear AI evaluates and prioritizes visibility improvements for each client within our platform. It’s an effective KPI in tracking returns holistically.

Why AI Visibility Matters

Generative AI has fundamentally changed how people discover information.
Instead of scrolling through links, users are asking conversational engines for advice, recommendations, and analysis.

According to a 2025 HubSpot AI Search Trends Report, 37% of users now prefer AI-assisted answers over traditional search.

That means visibility inside AI responses is the new form of brand awareness.
When a model like ChatGPT lists your brand in its top recommendations — or cites your research in an answer — it signals trust and authority to millions of users.

If your content is missing from AI responses, you’re missing a growing share of attention, influence, and organic reach.

What AI Search Visibility Really Means

AI visibility goes beyond rankings.
It’s about how your brand exists within the context of generative answers — what AI systems say about you, and whether they position you as a reliable voice in your space.

We track four forms of AI visibility:

1. Citations — Direct links or attributions to your website in AI responses.

2. Mentions — Natural references to your brand name in answers.

3. Context — The surrounding language, tone, and sentiment.

4. Representation — Whether the AI describes your product or values accurately.

Visibility is both quantitative (how often) and qualitative (how you’re framed).
Even one high-trust citation in a frequently surfaced query can have the impact of hundreds of keyword rankings.

Key Metrics That Define Visibility

When analyzing AI search performance, Bear AI focuses on six key metrics that directly influence your AI Search Score:

These metrics give a 360° view of how your brand performs in AI ecosystems, not just on traditional search pages.

How Bear AI Tracks and Improves Visibility

At Bear AI, tracking visibility is not just about counting mentions — it’s about understanding how and why AI systems retrieve your brand.
Our platform combines live AI querying, data parsing, and the AI Search Score framework to continuously measure your brand’s performance across multiple engines.

Here’s how we do it step-by-step:

1. Prompt Universe

We curate a set of high-intent prompts across your category — the same kinds of questions your audience actually asks generative engines.
Example:

“Best marketing analytics platforms 2025”
“Top AI SEO tools for startups”
“How to measure brand visibility in AI search”

These prompts are updated monthly to reflect changing trends and new model behaviors.

2. Multi-Engine Querying

Bear AI runs those prompts across leading AI systems: ChatGPT (Browse), Perplexity, Gemini, and Claude.
Each engine has its own retrieval logic — we capture the full answer output and metadata, including citations and references.

3. Scoring & Benchmarking

The AI Search Score algorithm aggregates your visibility across models using the weighted framework above.
Each client’s score is benchmarked against peers in their sector (e.g., SaaS, e-commerce, AI infrastructure) for relative context.

4. Lead Tracking

Bear AI tracks your leads from ChatGPT and AI search engines in real time, including their journey on your website, and shows you how it’s changing over time. This closes the loop: it directly tracks returns in real-time. This tells us exactly what to optimize, what’s working, and what isn’t.

5. Insights, Alerts & Recommendations

• Trend Analysis: Track visibility growth over time.

• Sentiment Insights: Detect shifts in tone or topic association.

• Action Recommendations: Our system suggests optimizations and a curated content strategy to dominate results.

All of this data lives in the Bear AI dashboard — giving you a real-time understanding of your brand’s presence in AI ecosystems.

Best Practices to Boost AI Search Visibility

Based on data from our visibility studies and the principles outlined in Generative Engine Optimization (Aggarwal et al., 2023), here’s what consistently improves AI visibility:

1. Create Structured, Crawlable Content

   • Ensure all core pages are indexable by Google and Bing.

   • Add FAQPage and Article schema for retrieval clarity.

   • Avoid gating or rendering critical text dynamically.
     
     

2. Optimize for Prompts, Not Keywords

   • Focus on “how,” “best,” and “why” phrasing used in conversational queries.

   • Track prompts that capture your potential customers’ intent— general, curious, but intentful
     
     

3. Publish Data-Rich, Cited Content

   • Include statistics, quotes, and credible outbound links.

   • Studies show AI models prefer content with explicit factual grounding.
     
     

4. Encourage External Mentions

   • Being referenced by other authoritative sources (press, academic, industry blogs) increases your retrievability score.
     
     

5. Update Regularly

   • AI retrievers prioritize fresh content. Refresh articles quarterly with new data or examples.
     
     

6. Monitor Tone and Accuracy

   • Check not just if your brand is mentioned but how.

   • Bear AI flags tone shifts that could impact brand trust.
     
     

FAQ

1. What exactly is AI visibility?

AI visibility measures how your brand appears inside AI-generated search results — including mentions, citations, and tone.
Unlike SEO, which tracks how you rank in search, AI visibility shows how generative engines talk about you.

2. How often should I measure AI visibility?

We recommend monthly tracking, since model updates and retrieval shifts happen frequently.
Bear AI automates this cycle and provides weekly micro-updates for brands in fast-moving sectors.

3. What causes visibility to drop?

Common causes include model retraining, content deindexing, or stale metadata.
Bear AI’s alert system flags these events automatically so you can act quickly.

4. Does improving AI visibility also help SEO?

Yes. The core principles overlap — structured data, authority building, freshness, and clarity.
Improving AI retrievability often leads to better indexing and higher engagement across all search platforms.

5. What AI search engines should I show up on?

ChatGPT dominates AI search volume with an 80% market share, according to a study done by First Page Sage. This is by far the most important AI search platform that you should aim to show up for. But at Bear AI, we track over 6 different LLMs and help you dominate all of them.

Final Thoughts

Tracking brand visibility in AI search is no longer optional — it’s essential for staying relevant in how users now consume information.
Generative engines are the new gateways to discovery, and brands that appear consistently in their responses will shape user perception at scale.

Bear AI makes this measurable.
Through real-time querying, NLP analysis, and the AI Search Score framework, we help brands see exactly how they’re represented across AI engines — and how to improve it.

Learn more at usebear.ai.