LLM prompt tracking gives you visibility into how large language model tools (also called AI systems) mention your brand, allowing you to optimize your content strategy.
This guide will show you how to set up prompt tracking, including a real-world example of how one agency used it to improve its visibility in LLMs.
What Is LLM Prompt Tracking?
LLM prompt tracking is the process of monitoring and analyzing the text queries (prompts) users enter into AI models, as well as the responses these models generate.
For example, if a user asks ChatGPT, “What are the best tools for UX?”, prompt tracking would let you:
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Log the query
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Record ChatGPT’s answer
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Note whether your brand was mentioned
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Track how the response evolves over time
The main difference from traditional SEO monitoring? Instead of tracking keyword rankings on search engine results pages, you’re tracking brand mentions and sentiment within conversational AI responses.
Prompt tracking is becoming increasingly important as more users rely on LLMs. It provides an additional way to understand how users are discovering your brand.
For example, using Semrush’s AI Traffic dashboard, we analyzed five major websites’ traffic from LLMs between August 2024 and August 2025. All five saw growth, with Roblox experiencing an increase of over 1,000%.
| Website | August 2024 AI Traffic | August 2025 AI Traffic | % Increase |
|---|---|---|---|
| roblox.com | 35.5K | 402.7K | 1,034% |
| nytimes.com | 81.2K | 218.1K | 169% |
| dailymotion.com | 10K | 106.3K | 963% |
| walmart.com | 67.3K | 526.9K | 683% |
| bbc.com | 111.5K | 245.7K | 120% |
What Are the Benefits of Prompt Tracking?
The primary benefit of prompt tracking is that it reveals your AI visibility, allowing you to take strategic actions that can ultimately drive more revenue.
More specifically, prompt tracking helps you:
1. Manage Your Brand Reputation
Tracking LLM prompt responses helps you catch outdated or incorrect brand information, so you can ensure users get accurate details about your business.
For example, an LLM might mention a pricing tier you discontinued two years ago. Prospects could dismiss your business as “too expensive” based on that incorrect data. Prompt tracking allows you to spot these errors.
Once identified, you can tweak your content strategy to guide LLMs toward the correct information. For instance:
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Update your review site profile with current pricing
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Respond to user questions in forums regarding pricing
2. Find Content and Messaging Gaps
Prompt tracking helps identify topics where AI highlights your competitors but not your brand—uncovering new content opportunities.
Example: You work for a software company. Prompt tracking shows LLMs frequently mention “integrations” when discussing your competitors, but your brand isn’t mentioned. This signals that your website lacks content on integrations.
By creating content that addresses these gaps, you can capture mentions and increase your visibility in LLM responses.
3. Uncover Content Optimization Opportunities
Tracking prompts reveals which topics and content formats—like how-to guides, product comparisons, or listicles—earn the most mentions. This insight allows you to replicate what works and improve your LLM share of voice.
You may also notice that different LLMs favor different types of content. For instance, Steve Morris, Founder and CEO of Newmedia, conducted a visibility audit for a client and found:
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ChatGPT recommended the client as the best solution for certain queries
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Perplexity and Gemini did not mention the client at all
To fix this, Steve and his team rewrote existing high-performing pages in formats tailored for each LLM:
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Reddit Q&A thread for Perplexity
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Listicle page for ChatGPT
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Blog post for Gemini highlighting alternatives to the client’s product
They tracked whether each LLM mentioned the client, quoted the client’s page directly, provided a link, or paraphrased content without a link.
Steve notes:
“Once you’ve done this for a few dozen prompts and a couple hundred passes, you start to see patterns.”
In six weeks, his efforts helped the client gain:
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Five Perplexity citations
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An increase in LLM mention rate from 40% to 70%
How to Do LLM Prompt Tracking
Prompt tracking follows a three-step process:
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Capture prompt and response data
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Add tags for additional context
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Analyze patterns over time to optimize your LLM strategy
Here’s how it works in practice:
Step 1: Capture Prompt and Response Logs
The foundation of prompt tracking is systematically recording AI interactions relevant to your brand or industry.
You have two options:
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Manual tracking – Set up a custom script that sends prompts to LLMs via APIs and logs the outputs
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Automated tracking – Use an LLM monitoring tool that tracks prompts automatically
Manual tracking is tedious and requires technical knowledge, as it involves collecting a large number of prompts and consistently recording responses to observe changes over time.
That’s why most marketers rely on tools. For example:
Semrush’s AI SEO toolkit allows you to track prompts and provides additional insights to improve rankings.
To get started:
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Open the Visibility Overview dashboard
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Enter your domain
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Click “Analyze”