How to Choose Which Prompts to Track for Clear AI Visibility Analytics
Most brands guess which AI prompts matter. Here’s how to build a list grounded in real buyer intent so you can track, measure, and win visibility where it counts.
Updated October 2025
Knowing which prompts to track is the single most important step to understanding and improving your brand’s visibility in AI-generated answers.
Prompts are the questions users ask inside answer engines like ChatGPT, Claude, and Perplexity. In Generative Engine Optimization (GEO), everything flows downstream from them.
When you know which prompts matter, you know how AI perceives your brand, what narratives it pulls from, and where you can start shaping that story.
In this guide, you’ll learn which prompts to track, how to organize them, and where to find the best sources of inspiration so you can build a GEO strategy grounded in real buyer behavior.
The difference between SEO keywords and GEO prompts
The instinct for most marketers is to match prompts exactly to what real users type. That approach made sense in the SEO era, but in GEO, it’s nearly impossible.
There are a couple of reasons why:
- There’s no public data on prompt density like there is for keyword density. Even keyword data in tools like Ahrefs or Semrush is only a modeled estimate based on click-through rate curves and limited third-party panels, not the full universe of searches.
- LLM prompts are 5-10x longer than traditional Google searches. LLM users write full sentences, include context, and even add constraints. That makes exact matching across millions of natural language variations a statistical impossibility.
The good news? Major LLMs don’t require exact matches.
They interpret through semantic and contextual patterns rather than exact wording. That means you don’t need to chase every variation, you just need to cover the right intent clusters.
How LLMs 'research' their answers
Most people think LLMs just “know” things. They don’t. They research at scale.
Here’s how LLMs actually get their information:
When you ask AI something like, “What are the best affordable office chairs?” the model doesn’t just pull answers from memory. It fans that question out into multiple related queries.
For example:
- Best affordable bedsheets
- High-quality budget office chairs
- Office chairs under $200
Each variation helps the model explore the topic from slightly different angles, much like how an expert researcher might phrase the same question in a few ways to find the most credible sources.
From there, the LLM scans search results, databases, and reference content across the web to identify which pages appear most frequently, consistently, and contextually across those variations.
Then it fuses those findings with its own training data to form a unified “best possible” answer. Usually, that means citing sources that appeared most authoritative in those fan-out results.
In short:
- LLMs don’t care about exact keywords.
- LLMs do care about semantic patterns and contextual consistency.
That’s why you don’t need an exhaustive list of every possible phrasing. You just need prompts that cover the core intent clusters your customers explore.
What exactly are intent clusters?
Intent clusters are groups of related questions that mirror the key stages of the buyer journey.
Each cluster represents a different type of intent behind a user’s question: exploring, comparing, replacing, or validating. In other words, they capture why someone is searching, not just what they’re searching for.
From an AI lens, these clusters are critical because they map to the areas where LLMs have the least amount of reliable, structured data. That’s exactly where LLMs look outward to the web for credible, citable sources to fill those gaps.
Your goal is to show up in those moments and become one of the trusted sources the model references when it builds its answers.
How prompts fit into intent clusters
Now that you understand intent clusters, here’s how to start thinking about which prompts fit best into each.
Focus on these four areas, and your prompt list will take you as far as you need to go in GEO.
How to choose the right prompts to track for AI search
Now it's time to get to work. Here is a step-by-step guide for choosing the right prompts to track in AI search:
1. Use your existing SEO keywords
Start with your money keywords. These are the ones currently driving the most conversions and traffic. Your team should already have a comprehensive list of these.
2. Use paid competitor keywords
Your competitors might outspend you on Google, but LLMs level the playing field.
Use the Google Ads Transparency Center to see exactly which queries and headlines your competitors care about most. This is essentially their prompt strategy in disguise.
3. Find your 'fan-out' keywords using Google AI Studio
This is where it gets interesting. Google AI Studio can show you the exact search queries an AI model (like Gemini) uses to build its queries. These are known as “fan-out” keywords.
Here’s how to find them:
- Go to Google AI Studio.
- Click Chat from the left sidebar
- Select Gemini Pro and make sure Grounding with Google Search is on (you’ll see this in the right sidebar).
Note: Only Gemini Pro supports Grounding. Nano and Flash don’t. - Type a prompt like earlier: “What are the best affordable office chairs?”
- Scroll to the bottom of the answer, where you’ll see a section called Google Search Suggestion. These are the keywords AI used to research its response.
If you want more data, simply tell the model: “Run the query again and give me more Google Search Suggestions this time.”
These fan-out queries are a goldmine since they represent the variations LLMs actually use to find and rank information.
4. Dig through customer conversations
Your customers are already telling you the prompts. They just don’t call them “prompts.” You’ll find them hiding in sales calls, discovery calls, and support tickets.
Listen for recurring:
- Questions: “How does this integrate with…” or “Can it handle X use case?”
- Objections: “Seems expensive compared to…” or “I’m not sure it works for teams our size.”
- Comparisons: “We’re evaluating you vs [competitor]. What’s the difference?”
- How-to Scenarios: “How do I set up…” or “What’s the best way to…”
These are gold because they reflect how real buyers frame problems and evaluate solutions.
5. Tap into communities and UGC
We know LLMs love Reddit. It’s full of real conversations, phrased exactly how buyers think and talk. That also makes it one of the best places to find prompt inspiration.
In the example above, you can bet this person asked AI: “What is the best CRM system for micro-saas founders?” That’s a perfect prompt to track if your product fits the bill.
Beyond Reddit, you can also scan:
- Quora threads (“Which tool is best for…”)
- Niche Slack or Discord groups (“Anyone using X for Y use case?”)
- Product Hunt comments (“Does this integrate with…”)
The key is to look for natural buyer language. If people ask it in communities, they’re probably asking it in AI too.
How to turn keywords into trackable prompts
Keep all of your keywords in a spreadsheet and keep blank spaces for Prompt and Intent Cluster. When your list is ready, use the Google Sheets AI integration to turn your keywords into prompts.
“Rewrite these keywords into natural buyer questions and map them to the relevant intent clusters.”
You'll end up with something like this:
Now you’re ready to upload those prompts to Search Party for a comprehensive look at your presence in AI-generated answers within minutes.
How many prompts to track at a time
A good starting point is around 25 prompts.
That’s enough to cover your four core intent clusters with several natural variations in each. At that level, you’ll start seeing clear visibility patterns without getting overwhelmed by data.
From there, the more the better.
Every additional prompt adds another lens to how AI perceives your brand. The more coverage you have across use cases, audiences, and phrasing, the more complete your visibility map becomes, making it easier to spot gaps and new opportunities.
Start focused. Expand fast. That’s the formula.
Your final checklist
[ ] Pull your top keywords.
- Owned
- Competitor
- Fan-out keywords
[ ] Convert into natural buyer questions.
[ ] Search online communities and sales calls for more natural buyer questions.
[ ] Add prompts to a spreadsheet and organize by intent cluster.
[ ] Export your spreadsheet and upload it to Search Party
Conclusion
Prompt tracking is just as much about awareness as it is measurement. It’s how you start to see what the world’s most powerful models actually think about you. Every prompt you track is a window into how AI connects ideas, compares brands, and shapes perception.
Most marketers will keep guessing what works. The smart ones will track, listen, and adapt. Because the moment you can see which questions you appear in (and which ones you don’t) you stop reacting to algorithms and start shaping the narrative yourself.