What is the Query Fan-Out tool?

The Query Fan-Out tool uses AI to expand a seed keyword into the wider landscape of related questions, intents, personas, and content opportunities, helping you identify the topics and user needs you should cover to build more comprehensive, intent-driven content.

Why is this useful?

If you're writing content around a single target keyword without understanding the wider landscape of related questions, intents, and sub-topics that users expect to be covered, your content is likely to underperform on topical authority. The Query Fan-Out Tool takes a seed keyword and uses AI to expand it into the full set of related queries, user intents, personas, and content angles - so you can build content that covers a topic comprehensively rather than just targeting one phrase.

How does the Query Fan-Out tool work?

The Query Fan-Out tool does not pull data from a search engine or third-party keyword database. Instead, it uses a custom AI-driven pipeline developed in-house to systematically expand a topic into the broader landscape of user questions, intents, and content opportunities.

The methodology is inspired by published research and patents describing how modern AI search systems generate and use synthetic queries to improve retrieval and answer generation, including:

• WO2024064249A1 — Generating and Using Synthetic Queries for Retrieval and AI-Generated Answers (the main one we worked from)
• US20250124067A1 — a related Google patent we also referenced

Overview

When you click Generate Queries, the system performs a three-stage process designed to map the full intent space surrounding a keyword:

Step 1: Entity Analysis

We send your seed keyword to ChatGPT with a structured prompt that breaks the topic down as below:

• Primary entity
• Entity type
• Underlying user intent
• Topic facets
• Likely user personas
• Related entities
• Decision factors

The result is a structured topic map that serves as the foundation for query generation.

Step 2: Query Generation

We then take that entity map and fire off 5 parallel prompts to ChatGPT, each responsible for a different group of the 15 query categories you see in the UI:

• Definitional
• Comparative
• Evaluative
• Procedural
• Troubleshooting
• Cost / Commercial
• Temporal
• Contextual
• Component
• Outcome
• Prerequisite
• Implicit
• Follow-Up
• Long-Tail
• Entity-Specific

Each query comes back tagged with intent, specificity, priority score, target persona, and reasoning.

This creates a diverse set of synthetic queries designed to represent how users may explore a topic from multiple angles.

Step 3: Clustering and Summary

A final prompt takes all the generated queries plus the entity map and produces the query clusters, persona-to-query mapping, intent/specificity distributions, top priority queries, and content recommendations.

Why We Use This Approach

Traditional keyword tools often focus on search volume and existing keyword databases. The Query Fan-Out tool takes a different approach by modelling how users may explore a topic across multiple intents and stages of their journey.

The aim is to give you visibility into the "fan-out" space around a keyword so you can plan content that covers the full intent landscape, not just the head term.

Updated on: 04/06/2026