Ahrefs’ new Query Fan Out feature inside Brand Radar’s module reveals the sub-queries AI models silently generate before answering user prompts, proving that winning AI-generated visibility requires more than covering a unique keyword; it requires covering the whole cluster.
Launched in February 2026 and available for ChatGPT and Perplexity (with export coming soon), Fanout Queries allows SEOs to see, for any tracked prompt, the exact sub-queries the AI model ran to build its answer.
When a user asks ChatGPT, “What are the best project management programs?“, the model doesn’t search just for that specific keyword. Instead, it fans out across sub-queries like “best project management software programs comparison 2026” or “top project management tools features pricing reviews”; those sub-queries are long tail structure, but it’s not the rule.
Ahrefs’ update specifically addresses the “blind spots” that make AI search optimization so difficult:
- no visibility into how AI models decompose complex prompts,
- no way to know which sub-questions your content needs to answer to earn citations, and
- no connection between AI monitoring data and actionable content strategy.
No major competing tool, including Semrush or Moz, currently addresses these gaps at this level. It’s worth noting, however, that one independent tool explored this space before Ahrefs did. queryfanout.ai, built by Dan Petrovic, is simpler and less automated, but it works and deserves credit for getting there first.
Test this new feature from Ahrefs; it can be beneficial for covering all cluster-related keywords and improving SEO and AI SEO results.
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