6 Steps to Get AI to Recommend Your Brand

Your content can rank on the first page of Google and still never be cited or mentioned by LLMs.

This makes sense once you understand query fan-out, a background process AI systems use to build answers.

When someone asks ChatGPT or Perplexity a question, it doesn’t default to the best-ranking page. Instead, it runs related searches behind the scenes, pulling from the most relevant and reliable sources, regardless of position.

High rankings don’t hurt, of course. But in AI search, coverage and retrievability are king.

In this guide, I’ll teach you how to optimize your content strategy for query fan-out to help increase your AI visibility. You’ll learn:

• Why LLMs use query fan-out
• How it behaves differently across major AI platforms
• Why it changes how you create and structure content
• A 6-step workflow for earning more citations in AI search

What Is Query Fan-Out?

Query fan-out is a process AI search systems use to break a single user query into multiple sub-queries to create the most helpful response. In other words, the AI “fans” the query out into a series of related sub-questions to build a more complete picture of the topic.

It then pulls information from multiple sources — editorial sites, Reddit threads, comparison and product pages — and synthesizes it into a single comprehensive answer.

AI systems use query fan-out for several reasons:

• Confirm information: A single source might be wrong or biased. Running parallel sub-queries allows the system to cross-reference multiple sources and find consensus before committing to an answer.
• Handle complex, specific queries: When a question has multiple layers, fan-out breaks it into manageable pieces that the system can research independently.
• Answer the real question: Fan-out anticipates needs that the user didn’t explicitly state and gathers evidence upfront.

This helps the AI build a more complete and useful answer:

What Query Fan-Out Is NOT

• [Keyword research](/content/tools/keyword "Free Keyword Research Tool by Backlinko"/index.html): Query fan-out is something AI systems do automatically, while keyword research is the process of finding terms your audience searches for.
• People Also Ask: PAA is a visible SERP feature that shows users what else they might want to search. Fan-out happens in the background whether you can see it or not.
• A fixed set of queries: Only 27% of fan-out sub-queries remain consistent across repeated searches, according to a SurferSEO study.

Why Query Fan-Out Matters for AI Visibility

Here are four shifts that should make you rethink how you approach content.

You Don’t Need Top Rankings to Get AI Citations

Top rankings don’t automatically translate to AI citations.

When AI breaks a query into sub-queries, it pulls the most relevant and complete source for each one, regardless of where it ranks. ChatGPT cites pages in position 21+ almost 90% of the time, according to a Semrush study.

AI Retrieves Passages, Not Pages

Rather than directing users to a page, AI systems scan your content and synthesize the exact passage that resolves a query. This means that the earlier you answer a question, the better your chances of being extracted.

You’re Competing Across a Whole Topic, Not Individual Keywords

SEO often revolves around individual keywords. Query fan-out revolves around comprehensive coverage.

Query Fan-Out Collapses the Buying Journey

With AI, awareness-level context, consideration-level comparisons, and decision-level specifics can all be pulled into one answer. This means your content needs to work across the full funnel, not just the stage you’re targeting.

The Query Fan-Out Workflow: 6 Steps to Earn More AI Citations

Step 1: Find Your Money Prompts

Money prompts are the conversational phrases or questions your ideal customer would ask when trying to solve a problem your product or service addresses.

Look for money prompts where your audience asks questions:

• Customer support tickets
• Community forums
• Sales call transcripts
• Internal chat logs
• Google Search Console queries

To find relevant prompts, you might need tools that deliver AI search data.

Step 2: Generate Your Fan-Out Set

There are two ways to generate fan-out sets: manually or with a dedicated fan-out tool. The manual approach is free and helps understand how fan-out behaves.

Step 3: Bucket Sub-Queries by Intent Type

Bucketing by intent tells you what types of content to create and the ideal format for each. Your sub-queries will help determine the formats needed.

Step 4: Audit Your Existing Content for Gaps

Check which sub-queries your site already covers and which it doesn’t (content gaps). Evaluate your pages against the sub-query they should cover.

Step 5: Structure Your Content So AI Can Extract It

Address specific questions directly and structure everything so AI can extract it cleanly:

• Lead with the answer, not background context
• Use content chunking
• Front-load key information early
• Use clear, precise language

Step 6: Measure Your Performance in AI Search

Track performance using the money prompts identified in step 1. Are you showing up? Is the information accurate? How do you compare to competitors?

How Query Fan-Out Works Across Different Platforms

Understanding the patterns of how each AI system inquiries is crucial:

AI Search Runs on Query Fan-Out — Your Content Strategy Should Too

Start with one money prompt, map the sub-queries, and audit where your content stands. Then work through the gaps, one topic at a time.