How Do I Do Keyword Research for AEO?
Keyword research for AEO starts like traditional research but ends differently — you find topics and intent with the usual tools, then translate them into the real, conversational questions people ask engines and prioritize those by value. The deliverable is a ranked question backlog, not a keyword spreadsheet.
Keyword research for AEO starts like traditional research but ends differently — you find topics and intent with the usual tools, then translate them into the real, conversational questions people ask engines and prioritize those by value. The deliverable is a ranked question backlog, not a keyword spreadsheet.
Quick answer
Same start, different finish. Use keyword tools to find topics and intent, then convert each into the real question someone asks an engine and rank by intent, value, and winnability. Lean on conversational sources — People Also Ask, autocomplete, communities, the engines themselves. Ship a prioritized question backlog, not a phrase list.
What stays the same, and what changes?
The discovery stays; the output changes. You still use keyword tools to gauge demand and read intent, but instead of ending with phrases to target, you end with the questions people actually ask engines. That's why keywords still matter as research signals while the unit of work becomes the question. The shift is from "what phrase do I rank for" to "what question do I answer."
Which sources should I combine?
All of them, because each reveals something the others miss. Standard tools quantify demand; People Also Ask and autocomplete expose adjacent questions; Reddit and Quora show real phrasing (Reddit is among the most-cited domains in AI search); your support and sales logs hold the highest-intent first-party questions; and AEO tracking shows which questions you're already cited for. No single source is sufficient — the combination builds a realistic picture of the conversation in your space.
How do I prioritize the backlog?
Score each question on intent, business value, and winnability, then act on the top. Favor questions near a decision, ones tied to your goals, and citation gaps where competitors appear and you don't. Merge overlapping questions into comprehensive pages so you don't create thin duplicates. That ranked, deduplicated list is what feeds production — the alignment layer that keeps you answering questions that actually matter.
Related questions
Do keywords still matter for AEO?
Yes, as signals of topic and intent — but you optimize for the full conversational question.
Read the full answer →How do I find the questions people ask AI?
Mine support logs, communities, search features, and the engines' own follow-up suggestions.
Read the full answer →How do I find content gaps for AEO?
Compare the questions you're cited for against competitors and your tracking prompt set.
Read the full answer →Frequently asked questions
- How do I do keyword research for AEO?
- Use familiar tools to find topics and intent, then convert each into the natural-language question a person would ask an engine, and prioritize by intent and business value. The end product is a ranked list of real questions to answer with self-contained passages, not a list of phrases to repeat.
- What's different about AEO keyword research?
- The output and the unit. Traditional research ends with keywords to target; AEO research ends with questions to answer. You also lean more on conversational sources — People Also Ask, autocomplete, communities, and the engines themselves — because they reveal full questions rather than stripped phrases.
- What tools do I use for AEO keyword research?
- Standard keyword tools for demand and intent, plus People Also Ask and autocomplete for adjacent questions, Reddit and Quora for phrasing, your own support and sales logs for first-party questions, and AEO tracking tools to see which questions you're already cited for. Combine them; none alone is enough.
- How do I prioritize AEO keywords and questions?
- Score by intent (how close to a decision), business value (does answering it help your goals), and winnability (can you answer it better than competitors). Favor citation gaps where rivals appear and you don't, and merge overlapping questions into comprehensive pages to avoid thin duplicates.