What are AI Fan-Out Queries: How AI Search Tools Think (And How to Use It)

Ever wonder how tools like ChatGPT decide which brands to recommend when you ask them a question? It’s not magic, but a process involving what are called ‘fan-out queries.’ These are the extra searches an AI performs to gather information before giving you an answer. Understanding this can help your brand get noticed.

Key Takeaways

• Most AI queries trigger up to five fan-out searches, with many falling between two and four.
• Fan-out queries are largely unpredictable; a high percentage appear only once.
• Focusing on broader themes and topic clusters is more effective than targeting single keywords.
• A significant portion of fan-out queries share links to the same few sources.
• Keeping content up-to-date, especially with the current year, can improve visibility.
• Creating content around specific use cases and audience segments is beneficial.

The Science Behind AI Recommendations

When you ask an AI search tool a question, it doesn’t just pull an answer from thin air. Instead, it goes out and searches the web, looking at many different sources to compile the information you need. The different questions the AI generates for its research are called fan-out queries. Think of it like this: you ask for a CRM for your marketing agency, and the AI then searches for things like ‘HubSpot CRM integrations,’ ‘CRM pricing,’ ‘pipeline features,’ and ‘CRM plans.’ It’s essentially doing its homework before presenting the final answer.

A study looked into this process and found that most queries trigger around two to four fan-out searches. Sometimes, if the question is more complex, it might do more. The AI’s goal is to get a broad understanding of the topic first, then narrow it down to give you the most important information. It’s interesting to note that sometimes, for very common or simple questions, the AI might not even need to search the web; it might just use the information it already has. But for many searches, especially those requiring current or specific data, the AI does go out and look.

Why Traditional SEO Still Matters

If AI tools are searching the web for answers, then traditional Search Engine Optimization (SEO) is still super important. You want your website or your content to be one of the sources the AI finds and uses. These AI tools have their knowledge bases updated every six to twelve months. So, if you want your brand to be known by these tools, you need to consistently put out good content and make sure it’s visible to the AI systems that crawl the web.

The Unpredictable Nature of Fan-Out Queries

Here’s a surprising part: those fan-out queries are pretty unpredictable. You might think that asking the same question multiple times would lead the AI to use the same research questions, but that’s not really the case. The study found that only a tiny percentage of keywords consistently appeared across different searches. A large chunk of fan-out keywords showed up only once. This means trying to target one specific keyword from a fan-out query might not be the best strategy. Instead, it’s better to think about broader themes and topic clusters.

The Power of Topic Clusters

This is where things get really interesting. When researchers looked at the top results for all these fan-out queries, they found that a huge percentage of them shared at least one link to the same source page. Even more striking, many shared links to the same five pages. What does this tell us? If you want to be found by AI search tools for a specific topic, you should focus on creating content around at least four related topic clusters. This approach helps ensure your content is seen as a reliable and comprehensive source.

Practical Strategies for AI Visibility

So, how can you actually use this information?

1. Empathize with Your Customer: Try acting like your ideal customer. Use AI tools and ask them questions. Look at the fan-out queries they generate to spot trends.
2. Stay Current: Notice if fan-out queries often include the current year (like ‘2025’). Making sure your content is up-to-date, and even including the current year in your page titles, can make it more likely to be picked up by AI.
3. Cover Specific Use Cases: AI often includes specific details from your prompt in its fan-out queries. For example, if you ask for a CRM for a ’15-person agency,’ the AI might search for that specific detail. Similarly, it might look for ‘CRM under $100 per month.’

Instead of creating a separate page for every single specific query, you can create one comprehensive page that covers multiple related use cases. Imagine a page that has sections for:

• Top CRMs under $500/month
• Top CRMs under $250/month
• CRMs for 10-person teams
• CRMs for 15-person teams
• CRMs for 50-person teams

This approach creates content that caters to the specific queries and use cases that AI tools are looking for. Remember, the goal isn’t just for humans to read this, but for AI to digest it and then summarize it for users.

Building Your Content Clusters

To help with this, you can use tools like this one to identify potential content clusters. The idea is to find four main clusters around a topic, and then break those down further into subtopics or specific questions. You can then create a separate page on your website for each main cluster. Within those pages, use headings to answer the specific sub-questions. Don’t forget to do all the standard SEO best practices, like interlinking your pages and having a main ‘pillar’ page that ties everything together.

By focusing on content clustering and broader themes, you’re much more likely to increase your visibility and get traffic from AI search tools. It’s about creating a web of related information that AI can easily understand and reference.