Prompt Research Guide: How to Find the Right Queries to Track

AI prompt research is a bit of a black box. Unlike traditional search engines, large language models don't reveal the exact prompts people use, publish keyword reports, or provide search volume data.

That makes one question especially challenging: Which prompts should you track? As an AI SEO agency founder, I get asked this all the time by clients. So, I built a framework that combines SEO data and user research to identify the prompts your audience is most likely to use. This guide will walk you through the process.

The main challenges of AI prompt research

In traditional search, everything was relatively predictable and measurable.

You have access to search volume, keyword difficulty, ranking data, and other metrics that help you decide which queries to target. Search results are also fairly stable, making it easier to measure performance over time.

AI search is fundamentally different for three reasons:v

• People prompt differently. Users don't search with short keyword phrases anymore. Instead, they ask longer, more personalized, and context-rich questions. Even when two people have the same intent, they may express it in completely different ways.
• There’s no prompt data. Unlike Google, AI platforms don't publish prompt data, so there's no equivalent of a keyword planner or Search Console that tells you what people are asking.
• LLM answers are volatile. Even if you knew the exact prompts, measuring AI visibility would still be difficult because LLM responses are highly volatile. The same prompt can produce different answers depending on who’s asking, when it's asked, the model being used, and the surrounding context.

In fact, research from SparkToro found there's less than a 1% chance that ChatGPT or Google's AI will return the exact same list of brands in any two responses when the same prompt is run 100 times.

These three challenges fundamentally change how prompt research should be approached. Instead of tracking a handful of keywords once a week, you need to build a diverse library of prompts that reflects real user intent and monitor them repeatedly over time.

3 types of prompts you should be tracking

People use AI for a variety of reasons. Some want to learn more about a topic, some are comparing options, and others want to validate a brand before purchasing.

For that reason, your prompt list should reflect each stage of the buying journey:

My prompt research framework

Because AI platforms don't expose prompt data, you have to reconstruct it from multiple sources. No single source provides a complete picture, but together they give you a reliable approximation of how your audience interacts with AI.

The framework consists of three steps:

1. Gather real user questions from Google Search Console, People Also Ask, forums, and customer conversations.
2. Transform SEO keywords into conversational AI prompts to expand your prompt library.
3. Organize prompts into clusters based on core business topics.

Let’s dive deeper into each step.

Step 1: Gather real user queries

The best prompts are rooted in real user behavior. While you can't see the exact questions people ask ChatGPT or other AI assistants, you can identify the problems they're trying to solve by analyzing the questions they already ask elsewhere.

Here are some of the best sources for discovering potential prompts:

Google Search Console

Your Google Search Console data is one of the most valuable sources because it contains the actual queries people use to find your website.

Although many searches are short keyword phrases, you'll also find plenty of questions and conversational queries that can be adapted into AI prompts.

To find these queries, open the Performance report, switch to the Queries tab, and apply a Custom (regex) filter.

Use the following expression to surface question-style searches:

^(who|what|when|where|why|how|which|can|does|do|is|are|should|will|could|would)\b

People Also Ask box

Google's People Also Ask (PAA) box is another excellent source of prompt ideas. The questions shown in PAA are generated from common search behavior and often reflect the follow-up questions users have as they research a topic.

Search for your primary keywords and record the questions that appear in the PAA section. Expand multiple questions, as Google will continue to load additional related questions.

Discussion forums

Many of your target audience are already asking questions in Reddit, Quora, and industry-specific forums. These discussions are particularly valuable because they capture the natural, conversational language people use when seeking advice, comparing products, or solving problems.

You can search for relevant threads in Google by typing your niche keyword + the name of the forum. For example: “AI visibility tracking reddit.”

Discovery calls

One of the best ways to understand how people discover your business through AI is to ask them directly. During discovery calls or sales conversations, include a few questions about how they found you before they reached out.

For example, ask:

• Did you use Google or an AI assistant to find us?
• If you used AI, which platform did you use (e.g., ChatGPT, Gemini, Claude, Perplexity)?
• What prompt or question did you ask?
• Did the AI recommend our company directly, or did it suggest an article or website that led you to us?

Step 2: Use search keywords to support prompt discovery

Search keywords are a valuable source of prompt ideas because they represent topics, problems, and needs that your audience is already actively searching for.

While the way people search on Google is different with AI assistants, the underlying intent behind those searches is the same. You just need to add contextual modifiers that reflect the user's situation, goals, or constraints.

Here’s how:

Gather SEO keywords from your SEO tool

Pull your keyword data from Ahrefs, Semrush, or any other keyword research tools that you’re using.

Focus on keywords that are relevant to your business, especially:

• Commercial keywords (e.g. best crm software)
• Branded keywords (e.g. how much does salesforce cost)
• Competitor comparison keywords (e.g. salesforce vs hubspot)

These will become the foundation of your prompt library.

Analyze the fan-out queries for your main topics

Fan-out queries are the related questions and subtopics AI models search internally when generating a response.

Analyzing these queries helps you discover keyword variations and subtopics that may not appear in your original prompt list. They often reveal the supporting questions you should also be tracking.

You can use tools like Promptwatch’s free ChatGPT Query Fan-Out Generator to surface the fan-out queries for your main prompts.

Transform those keywords into prompts

Once you have your keyword list, feed those keywords into an AI assistant like Claude or ChatGPT and ask it to transform them into realistic prompts.

For each keyword, ask the AI model to suggest different angles based on:

• Use cases. How different audiences might use the product or solution.
• User profiles. How prompts change based on company size, industry, role, or level of expertise.
• Pain points. The specific problems users are trying to solve.
• Comparison scenarios. How users evaluate alternatives or competitors.
• Buying criteria. The factors users consider before making a decision.
• Constraints. Budget, team size, technical requirements, or other limitations.

For example, the keyword "project management software" could become:

• What's the best project management software for a remote marketing team?
• Which project management tool is easiest for a small business to adopt?
• As a startup founder, what project management software should I use?
• Monday.com vs Asana: which is better for managing client projects?
• What project management tools are affordable for a team of 10?

Step 3: Cluster your prompts based on core business topics

Once you have collected prompts from different sources, the next step is to organize them into structured clusters.

Avoid treating every prompt as a standalone query. Instead, group related prompts into topic clusters based on your core business areas. This makes your prompt tracking more scalable and helps you understand your AI visibility at the topic level rather than looking at individual prompts in isolation.

Also, include the prompt type (informational, commercial, and branded prompts) for each query. This gives you a complete view of how AI platforms represent your brand—from general education to product recommendations and brand evaluation.

For example, here’s what a resource management platform’s prompt library looks like:

The next step: Track your prompts using Promptwatch

At this point, you should have a structured prompt library that reflects the different ways your audience searches, evaluates solutions, and researches your brand.

But finding the right prompts is only half the job. The next step is monitoring your prompts consistently to understand how your visibility evolves over time.

This is where AI visibility tracking tools like Promptwatch come in.

With Promptwatch, you can track your prompt library across major AI platforms and monitor key visibility metrics, including:

• Brand mentions: How often your brand appears in AI-generated responses.
• Citations: Which sources AI platforms reference when answering your prompts.
• Competitor visibility: How your brand compares against competitors across important topics.
• Sentiment and positioning: How AI describes your brand and whether the information is accurate.
• Visibility trends: How your AI presence changes over time.

Instead of manually running prompts and recording responses, Promptwatch helps you create a repeatable measurement system. You can identify where your brand is already visible, where competitors are gaining ground, and which content opportunities can improve your AI search presence.

Start your free trial today and start monitoring your AI visibility!