Question 1

What is query fan-out in AI search?

Accepted Answer

Query fan-out is the process of mapping all the different ways buyers might search for your product or category in AI assistants like ChatGPT and Gemini. Unlike Google keyword research (which focuses on exact queries), AI search query research must cover conversational variations, comparison questions, and problem-first queries - because AI users phrase their questions differently than traditional search users.

Question 2

How many queries does a typical brand have?

Accepted Answer

Most B2B brands have 20–50 relevant AI search queries across the 5 intent types. Highly competitive categories (like CRM or project management software) may have 100+ variants. This tool generates up to 50 queries for your brand; the full AEOVisor platform lets you track all of them across multiple AI engines.

Question 3

What are the 5 AI buyer intent types?

Accepted Answer

Discovery queries test early-stage research ('best CRM for small business'). Comparison queries test brand awareness ('HubSpot vs Salesforce'). Problem/Solution queries test topical authority ('how to reduce customer churn'). Commercial queries test purchase intent ('HubSpot pricing 2025'). Local/Geo queries test geographic discovery ('CRM software companies in London'). Each type requires different content and AEO strategies.

Question 4

How is this different from keyword research tools?

Accepted Answer

Traditional keyword research tools (like Ahrefs or SEMrush) show you search volume for exact keyword phrases on Google. This tool generates the conversational, intent-based queries that buyers actually type into ChatGPT, Gemini, and Perplexity - which are often longer, more conversational, and not measurable by traditional volume metrics.

Question 5

Can I use these queries in AEOVisor's tracker?

Accepted Answer

Yes. Once you've generated your query set, you can export it directly to an AEOVisor tracker that monitors your brand's appearance in AI-generated answers for each query - weekly, with sentiment and citation analysis.

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