Updated guide available. For a more detailed measurement framework, read How to Measure Your Brand’s AI Visibility. For ChatGPT-specific tracking, see How to Track Brand Mentions in ChatGPT.
Your brand is being discussed right now. Not on social media. Not in reviews. But inside AI assistants. McKinsey research shows 50% of consumers now use AI-powered search.
Every day, millions of conversations happen in ChatGPT, Claude (Anthropic), Perplexity (perplexity.ai), and Gemini. People ask about solutions in your category. They compare brands. They make buying decisions.
And most companies have no idea what is being said about them.
This is a problem. Because AI recommendations are shaping purchase behavior at scale. If you are not monitoring what AI says about your brand, you are flying blind.
Here is how to fix that.
Step 1: Define Your Core Queries
Before you can monitor AI mentions, you need to know what questions people are asking.
Start with these query categories:
Direct Brand Queries
-
“Tell me about [Your Brand]“
-
“What does [Your Brand] do?”
-
“Is [Your Brand] worth it?”
Category and Solution Queries
-
“Best [your category] for [target customer]“
-
“What [category] should I use if I need [specific feature]?”
-
“Top [category] tools for [use case]“
Comparison Queries
-
“[Your Brand] vs [Competitor]“
-
“Should I choose [Your Brand] or [Competitor]?”
-
“Differences between [Your Brand] and [Competitor]“
Create a list of 15-25 core queries that represent how real buyers would ask about your solution.
Step 2: Run Manual Baseline Tests
Take your query list and manually test it across major AI platforms:
-
ChatGPT (free and Plus versions behave differently)
-
Claude
-
Perplexity
-
Gemini
-
Google AI Overviews (search results page)
For each query, document:
-
Is your brand mentioned? (Yes/No)
-
If yes, what position? (First, second, third, or buried in a list)
-
What is the sentiment? (Positive, neutral, negative)
-
Is the information accurate?
-
Which competitors are mentioned alongside you?
This baseline test will show you exactly where you stand. Most brands are shocked by what they discover.
Step 3: Set Up Ongoing Monitoring
Manual checks are useful for initial assessment. But they do not scale.
If you are serious about AI visibility, you need automated monitoring. Here is why:
-
AI responses change over time as models update
-
Competitor mentions fluctuate as their content strategies evolve
-
New inaccuracies can emerge as AI systems ingest new data
-
Running 25 queries manually across 5 platforms daily is not sustainable
Tools like friction automate this process. They run your query set daily, track changes, alert you to shifts in sentiment or visibility, and benchmark your performance against competitors.
Without automation, you are guessing. With it, you have data.
Step 4: Identify Patterns and Gaps
Once you have monitoring data, look for patterns:
Visibility Gaps
-
Which queries never mention your brand?
-
Are there categories or use cases where competitors dominate?
Accuracy Issues
-
Is AI describing outdated features?
-
Are there factual errors about your product or pricing?
Sentiment Trends
-
Is AI consistently neutral, or does it lean positive/negative?
-
Do certain platforms favor competitors over you?
These patterns tell you where to focus your optimization efforts.
Step 5: Take Action Based on Data
Monitoring without action is useless. Use your data to:
-
Publish content that fills visibility gaps
-
Correct inaccuracies by updating authoritative sources AI references
-
Strengthen weak areas where competitors outperform you
-
Double down on queries where you already have strong visibility
The goal is not just to track AI mentions. The goal is to systematically improve them over time.
What Good Monitoring Looks Like
Here is what a mature AI monitoring practice looks like:
-
Daily automated tracking across all major AI platforms
-
Real-time alerts when your brand is mentioned incorrectly or negatively
-
Benchmarking against 3-5 key competitors
-
Monthly reporting on visibility trends and share of voice
-
Integration with content and SEO strategy to address gaps
This is not optional. If you want to compete in a world where AI drives discovery, you need to know what AI is saying about you.
Most brands are still flying blind. Do not be one of them.
For detailed guides on each metric, see visibility, brand recognition, sentiment, and purchase intent.
Why Teams Choose friction AI
friction AI goes beyond basic AI visibility tools to focus on recommendation outcomes — helping brands understand not just whether they appear in AI responses, but when and why they are recommended, especially in high-intent commercial contexts.
See how friction AI tracks your brand’s AI recommendations and commerce visibility.