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How to Find the Queries That Matter for AEO

A practical workflow for discovering the conversational, intent-rich queries AI engines answer about your category — and prioritizing the ones worth winning.

By Team @ LLM Metrix7 min read8 sections

Winning AI search starts with knowing which questions to answer. Unlike traditional keyword research, AEO query discovery focuses on the long, conversational prompts people actually type into ChatGPT, Perplexity, and Gemini — and the follow-ups those answers trigger.

Why AEO queries are different

Search keywords are short and ambiguous (“crm software”). AEO queries are full questions with embedded intent (“what’s the best CRM for a 5-person agency that needs invoicing?”). They carry constraints, comparisons, and use cases that map directly to how AI engines synthesize answers. Your job is to surface those questions and the entities they reference. If you’re new to the distinction, start with AEO vs SEO.

Step 1: Mine the AI engines directly

The fastest source of real AEO queries is the engines themselves.

  • Ask the seed question. Type your core category question into ChatGPT, Perplexity, and Gemini. Note which brands get cited and which sub-topics surface.
  • Harvest follow-ups. Perplexity and Gemini suggest “related” questions under every answer. These are gold — they’re the actual next prompts users send.
  • Probe variations. Add modifiers: “best,” “vs,” “alternatives to,” “how to,” “is X worth it.” Each modifier reveals a distinct query cluster.

Step 2: Build query clusters by intent

Group raw questions into intent buckets so you can match content formats to them:

Intent Example query Best format
Informational “how does AEO work” Explainer / definition
Commercial “best AEO tools for startups” Comparison / listicle
Navigational “Notion pricing” Product page + FAQ
Transactional “sign up for Perplexity Pro” Conversion page

Commercial and comparison queries are where brand visibility pays off most — see Comparison & ‘Best X’ Pages for AEO.

Step 3: Pull from non-search sources

AI engines are trained on conversations, not just search logs. Expand your list with:

  • Customer support tickets and sales call notes — the exact phrasing prospects use.
  • Reddit, Quora, and niche forums — long-tail questions with rich context.
  • People Also Ask” boxes in Google — these overlap heavily with AI follow-ups.
  • Your own site search logs — internal queries reveal unmet intent.

Step 4: Prioritize with a simple scoring model

You can’t chase every query. Score each candidate 1–5 on three axes and rank by total:

  1. Business value — does answering this query reach a buyer?
  2. Citation gap — are competitors already cited, or is the SERP/answer thin? A thin answer is an opportunity. Run a competitor benchmarking pass to confirm.
  3. Authority fit — can you credibly answer this given your existing content and expertise?

Queries scoring 12+ go to your roadmap first. Feed the winners into your AEO content calendar.

Step 5: Validate and close gaps

Cross-reference your prioritized list against what you already publish. Anything with high value but no matching asset is a content gap — the content gap analysis guide walks through closing them systematically. Tie everything back to a documented plan via how to build an AEO strategy.

A repeatable monthly cadence

AEO query landscapes shift as models update. Re-run this loop monthly:

  1. Re-prompt your top 10 queries across all engines.
  2. Log new follow-up suggestions.
  3. Note any citation changes (you gained or lost a mention).
  4. Add net-new queries to the backlog and re-score.

Track the trend, not the snapshot — a query you don’t appear in today is a roadmap item, not a failure.

Frequently Asked Questions

How many AEO queries should I target to start?

Start with 15–25 high-priority queries clustered around one or two core topics. Concentrating depth on a narrow set builds topical authority faster than spreading thin across hundreds of unrelated questions. Expand once you’re consistently cited on the first batch.

Do traditional keyword tools still help for AEO?

Yes, as a supplement. Tools that surface “People Also Ask” data and long-tail question keywords overlap meaningfully with AI follow-up prompts. Treat their output as raw input, then refine it with real prompts pulled from the engines themselves.

How do I know if a query is worth winning?

Score it on business value, citation gap, and authority fit. A query is worth winning when it reaches a buyer, has a thin or contested AI answer, and falls within a topic where you can credibly claim expertise. Anything that fails all three is a distraction.

How often do AEO queries change?

The underlying questions are fairly stable, but which brands get cited shifts as models retrain and competitors publish. Re-test your priority queries monthly so you catch citation losses early and add emerging questions before competitors do.

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