Imagine you’re pulling back the curtain on the world’s most influential stage, where AI tools like ChatGPT, Perplexity, and Claude perform to answer billions of queries daily. The script for these performances? Fragments of online content combined, synthesized, and presented in seconds. The question for your brand is—are you a part of that script?
Tracking visibility in large language models (LLMs) represents a new frontier in Answer Engine Optimization (AEO). This is how you monitor if and how your content is becoming part of the answers in a zero-click environment where users never visit your site.
This guide will show you how to monitor your LLM visibility, analyze what works (or not), and take actionable steps to improve your position in AI-generated answers. If you lead SEO, manage content strategy, or are responsible for brand visibility, this is your opportunity to track how your business shows up in AI-generated answers and to take control of it.
What does it mean to track visibility in LLMs?
Tracking visibility in LLMs means knowing whether your brand, content, or domain shows up in the answers they generate. It's not just about being mentioned; it's understanding when and how your content is retrieved, synthesized, and presented to users.
How LLMs generate responses
To track LLM visibility, you need to peel back the layers of how these models work. LLMs create answers by pulling from multiple sources, including:
1. Training data
Pre-existing data collected prior to the model’s last update. This could include public datasets, books, or websites.
2. Live search results
Some tools, like ChatGPT with browsing and Perplexity, integrate live web searches to generate more current answers.
3. Cited sources
Platforms like Perplexity and Claude often include direct citations in their responses, revealing where the information comes from.
The goal of tracking
By tracking visibility, you can uncover answers to key questions:
- Which prompts include your brand or content in their responses?
- Are your competitors appearing more often?
- What gaps exist in your current strategy, and where can you improve?
This knowledge helps you refine your content for better AI recognition, ensuring your brand is part of the answers that matter.
Step-by-step: How to track your brand in LLMs
Step 1 – Start with real prompts
Think like your users. They’re not searching for your brand name; they’re searching for solutions, recommendations, and comparisons. The first step is crafting realistic, intent-driven prompts that reflect what users actually type into AI tools.
Examples of prompts to test:
- “Best eCommerce agencies for Adobe Commerce”
- “Eco-friendly packaging UK supplier”
- “Who are the best Shopify agencies for enterprise brands?”
- “Which companies offer Magento support services?”
- “Best AI SEO tools for B2B websites”
Create a mix of informational, commercial, and comparative prompts that align with your industry or target audience.
Step 2 – Run your prompts in each AI tool
Now it’s time to test. Use multiple tools to see where your brand stands in the AI-generated response ecosystem.
Platforms to use
1. ChatGPT
- ChatGPT responses vary depending on subscription level, model selection, and whether browsing is enabled.
- It can pull live data when browsing is turned on, but often synthesizes from prior training.
- Citations are not guaranteed—some answers include links, others do not.
- Useful for evaluating how your content is interpreted and summarized, even if unattributed.
2. Perplexity
- Designed around transparency, with citations shown by default for nearly all answers.
- Excellent for tracking which sources are influencing AI-generated answers.
- Follow-up questions allow you to test context retention and brand recall.
- One of the most consistent platforms for citation tracking.
3. Claude (Anthropic)
- Known for generating clear, well-organized answers, often with citations—especially for factual and research-oriented queries.
- Source visibility varies depending on the nature of the question.
- A strong platform to test your content’s inclusion in high-confidence summaries.
4. Gemini (Google)
- Google’s flagship AI assistant integrated into search and apps.
- Frequently includes source citations, especially for product, informational, and location-based queries.
- Taps into a mix of web content, YouTube data, and Google’s structured knowledge.
- Visibility here often reflects your brand’s overall presence in Google’s ecosystem.
4. Microsoft Copilot
- Built on OpenAI’s models with deep integration into Microsoft’s products.
- Typically includes hoverable citations, linking to Bing-indexed pages.
- Strong for local, product-based, and enterprise service queries.
- Useful for testing how well your structured, FAQ-style, and brand-specific content is picked up—especially across Bing’s index and Microsoft-integrated experiences.
5. DeepSeek
- A rising LLM with strong performance in multilingual and research-based queries.
- May include citations depending on interface and query type.
- Useful for assessing visibility across academic, technical, or international content domains.
Key tips!
- Keep a consistent testing environment by noting the model version, browsing capabilities, and session date.
- Be mindful of variations caused by personalization (e.g., account-specific behaviors or search histories).
Step 3 – Record what shows up
Once you’ve run your prompts, it’s time to gather insights systematically. A simple spreadsheet or a visual dashboard is all you need to get started.
Key information to log:
- Prompt tested (e.g., “Best AI tools for eCommerce”)
- Tool used (ChatGPT, Perplexity, Claude, etc.)
- Date tested Whether your brand appeared and how it was represented (e.g., metadata citation or paraphrase).
- Any competitors mentioned prominently
Example Dashboard.
| Prompt |
Tool
Used |
Date |
Your Brand
Mentioned? |
Competitor
Mentions |
Notes |
Eco-friendly
packaging supplier |
Perplexity |
7/20/2025 |
Yes, cited
by source URL |
Competitor B,
Competitor C |
Blogs cited
heavily |
Tools to help you monitor LLM mentions
Tracking your visibility manually can be a great starting point, but specific tools designed for LLM visibility can simplify and scale the process.
AnswerRank
- Purpose-built for tracking brand mentions across LLM-generated answers.
- Has dashboards showing prompt performance and competitor comparisons.
- Lets you test real-world prompts to see whether your brand shows up and how often competitors do.
- Ideal for content strategists and SEO leads looking to turn LLM monitoring into a measurable, repeatable process.
- Supports competitive benchmarking, trend monitoring, and prompt optimization at scale.
Semrush
- A major SEO suite that has integrated comprehensive AI visibility tracking features into its platform.
- Provides brand mention tracking, competitor benchmarking, and sentiment analysis across major AI platforms for holistic AEO.
LLMrefs
- Tracks brand visibility across a wide array of AI search engines, including ChatGPT, Claude, Gemini, Perplexity, and Grok.
- Offers a proprietary LLMrefs Score and insights into potential AI model biases affecting content visibility.
Scrunch AI
- Functions as an AI Brand Presence Monitor, helping track how a brand appears in AI-generated content.
- Focuses on proactive AI optimization strategies alongside ongoing monitoring.
Peec AI
- Specializes in monitoring brand visibility across a wide array of AI search engines.
- Offers detailed insights into brand mentions, sentiment, position scoring, and source analysis.
- Designed with a user-friendly interface, making sophisticated AI visibility tracking accessible for small to medium-sized businesses.
Profound AI
- Built for larger organizations and extensive SEO teams requiring deep AI search visibility analytics.
- Provides sophisticated tracking capabilities, competitive benchmarking, and high levels of customization for specific enterprise needs.
Keep in mind, tracking results requires time and repetition. Some LLMs may paraphrase content without attribution, making consistent testing a key strategy.
Tracking prompts in AIs helps you understand how your brand is performing and where to improve.
How to read the results and spot patterns
Whether your brand is mentioned or not, the data you gather should serve as a blueprint for improving your positioning.
When your brand is mentioned:
- Prominence – Is your brand cited as the primary answer or buried in a list of competitors?
- Accuracy – Are the details correct, or is outdated content being pulled?
- Type of content – Is the mention tied to something specific, like a blog post, landing page, or product page?
When your brand is missing:
- Competitors – Which brands dominate the responses? Do they appear repeatedly across multiple prompts?
- Sources – Are there major content hubs (like Wikipedia, top blogs, or SaaS directories) that AI frequently references?
- Variations across platforms – Notice how ChatGPT prioritizes one type of source while Claude or Perplexity favors another.
By identifying patterns, you can reshape your strategy to better align with the signals these platforms prioritize.
Expect variation across tests. LLMs don’t always generate the same answer twice. Even with identical prompts, tools like ChatGPT and Perplexity may cite different sources or paraphrase your content without attribution. That’s normal, and why repetition matters.
- Don’t rely on a single output. Run each prompt multiple times across sessions and tools.
- Track frequency, not just presence. Showing up 7 out of 10 times is a stronger signal than a one-off mention.
- If your brand appears inconsistently, study the competitors that do show up consistently. What formats or sources are they using?
- Use trends over time to spot shifts in visibility, influence, and missed opportunities.
LLM visibility isn’t fixed—it fluctuates. The goal is to move from being occasionally mentioned to being the default source for specific queries.
Wrapping up
AI-generated visibility is no longer a guessing game. It’s measurable, actionable, and essential for staying ahead in how people discover and engage with content. By tracking your presence in LLMs like ChatGPT, Perplexity, and Claude, you can better understand how users interact with AI-generated responses and position your brand as a trusted part of the answers they seek. Monitoring how your content ranks and is presented in these AI-driven platforms, helps you make informed decisions to improve your reach and engagement. This approach is followed by the best AEO agencies as it ensures that your strategy aligns with the latest AI trends.
Start small. Even testing a handful of intent-driven prompts monthly can uncover actionable insights. From there, refine your AEO strategy to thrive in the growing AI-powered search environment.
AEO and traditional SEO, though both essential, serve different purposes, and incorporating GenAI optimization services into your strategy can be a game-changer, enabling you to stay ahead of the curve.
