AI Prompt Research for AEO: how to find the prompts that matter

What is prompt research for AEO?

Prompt research for AEO is the process of finding the questions and instructions people give AI assistants, so you can create content that those assistants can quote or cite in their answers. AEO stands for answer engine optimization, the practice of making your content easy for AI systems and search engines to use as a direct answer.

A prompt is the full text a person types or speaks to an assistant. It is often longer and more specific than a search query, such as "compare two accounting tools for a five-person firm and list the main trade-offs".

Prompts versus keywords: a keyword is a short phrase typed into a search box, while a prompt is a conversational request that often includes context, constraints and the format wanted. Keyword research shows which topics people search. Prompt research shows how they ask for help and what kind of answer they expect.

Where prompts come from: the best sources are places where buyers state problems in their own words.

• Sales calls, emails and support tickets
• Site search and on-site chat logs
• Community threads and review sites
• Your own tests of AI assistants using realistic buyer questions
• Search suggestions and "people also ask" boxes

For more on this topic, see our AI search (AEO/GEO) articles.

Why does prompt research matter for answer engine optimization?

Prompt research matters because people phrase AI questions differently from search queries, and the topics and wording you cover decide whether your content is a candidate for an answer. If your pages only match short, trimmed keywords, an AI assistant may find nothing that fits the question a buyer actually typed.

Prompt research also shows you which questions your market asks at all. That lets you spend writing time on topics that can plausibly be cited, instead of guessing.

Two shifts explain most of the value.

**Longer, conversational queries.** A search might be "crm small business". A prompt is more likely "Which CRM suits a ten-person service company that uses spreadsheets today?" The prompt carries context: company size, current setup, a constraint. Content that states those details plainly, in the same terms, is easier for an answer engine to match.

**Brand mentions inside AI answers.** AI answers often name a few brands or sources instead of listing ten links. Whether yours appears depends partly on whether your content addresses the prompt directly and whether your brand is described clearly and consistently across the web. Prompt research tells you which prompts to check and which ones you are absent from. Outcomes vary by assistant and are not guaranteed.

For more on this area, see our AI search (AEO/GEO) articles.

How is prompt research different from keyword research?

Keyword research studies short search phrases and their measured volume, while prompt research studies full conversational questions, their context and intent, and the answers AI tools return. The table compares inputs, outputs, data availability and use.

Data availability is the biggest practical gap. AI tools generally do not publish how often a prompt is asked, so prompt research leans on sales calls, support tickets, and testing the prompts yourself.

Use keyword research when you are planning site structure, service pages or local landing pages. Use prompt research when you want to know how buyers compare options, ask for recommendations or describe a problem in their own words.

The two methods work together. A keyword often points to a topic, and prompt research shows the specific questions inside that topic. For more on this area, see our AI search (AEO/GEO) articles.

How do you find the prompts your customers actually use?

You find real prompts by collecting customer questions from sales, support, reviews and forums, then checking them against search suggestions and by running them in AI assistants. Start with what customers already say, because their wording is closer to a real prompt than any keyword tool output.

**Sales calls, support tickets and reviews.** Ask your sales and support teams for the first question a buyer asks, the objection they raise and the comparison they request. Copy the wording exactly. Reviews often show the problem in the customer's own words, such as "I needed someone who could fix X without Y".

**Search suggestions and People Also Ask.** Type a seed question into a search box and note the autocomplete options. Open the People Also Ask box and record the follow-up questions. These show how people phrase the same need in different ways.

**Testing questions in AI assistants.** Run your candidate questions in several AI assistants. Note which sources get cited, which brands are named and where the answer is vague or wrong. Answers can vary between sessions, so repeat each test a few times and log the date.

**Community forums.** Read industry forums, Q&A sites and social groups where your customers ask for advice. Long, detailed posts are useful because people increasingly write prompts the same way, with context included.

Put everything in one sheet with the source, exact wording and topic. Our AI search (AEO/GEO) articles cover what to do with that list next.

How do you decide which prompts to prioritize?

Prioritize prompts that match a buying stage you serve, relate directly to your offer, and currently return answers that omit or misrepresent your brand. A long prompt list is only useful once it is ranked. Three filters do most of the work.

**Intent and buying stage.** Prompts such as "what is a site audit" signal early research, while "which agency should I hire for ecommerce SEO" signals a near-term decision. Favor the stages where your sales team actually wins business, and treat purely educational prompts as lower priority unless they feed later decisions.

**Fit with your offer.** A prompt fits when your product, service or location is a reasonable answer to it. If you could not serve the person asking, skip it, even if the topic looks popular.

**Gap in current answers.** Run each remaining prompt in the answer engines your customers use and record what comes back. Mark prompts where your brand is missing, described incorrectly, or replaced by outdated information. Those gaps are where new content or corrections can change the most.

Prompts that pass all three filters go to the top of the list. If you want help scoring a list, you can contact our team.

What is a step-by-step checklist for prompt research?

A practical checklist is: define topics, collect real questions, group them by intent, test them in AI assistants, record the sources cited, prioritize gaps, and recheck on a regular schedule. Each step produces a written output, so another person can repeat the work.

1. Define topics: list the products, services and problems you want to be known for.
2. Collect real questions: use sales calls, support emails, reviews and search data.
3. Group by intent: separate learning, comparing and buying questions.
4. Test in AI assistants: run each prompt in the assistants your customers use.
5. Record sources cited: note which pages and sites the answers rely on, and whether your brand appears.
6. Prioritize gaps: rank prompts by business value and how weak your current presence is.
7. Recheck on a schedule: repeat the tests and compare against your earlier notes.

Prompt research should be repeated regularly because AI answers can change from one run to the next and as assistants update. A quarterly review is a sensible starting point for most businesses, with a lighter monthly check on your highest-value prompts.

Keep the same prompt wording, assistants and spreadsheet columns each time. Consistent records make changes easier to spot, and they show whether your content work is affecting which sources get cited. Results still vary by assistant and are not guaranteed.

What should you watch out for when doing prompt research?

AI answers vary between runs and tools, and prompt volume data is limited, so treat findings as directional and repeat tests instead of relying on a single result. Three pitfalls cause most of the bad decisions in prompt research.

Inconsistent AI answers are the first pitfall. The same prompt can return different wording, different sources and different brand mentions from one run to the next. Run each prompt several times, on different days, and record how often your brand or a competitor category appears rather than whether it appeared once.

No reliable volume data is the second. Search engines publish keyword volumes, but AI assistants generally do not share how often a prompt is asked. Prioritize with proxies you can check: customer calls, sales emails, support tickets, on-site search and your own judgment of commercial value.

Overfitting to one assistant is the third. Each assistant draws on different sources and formats answers differently, so a prompt list tuned to one tool may miss how customers use another. Test your priority prompts across the assistants your customers are likely to use, and look for patterns that hold across them.

• Repeat every test at least a few times before drawing conclusions.
• Label all findings as directional, not measured demand.
• Log the tool, date and exact wording of each prompt.
• Re-test on a schedule, since answers change over time.

If you want help building and testing a prompt list, contact our team.

What should you do after you have your prompt list?

After building the list, map each prompt group to a page or section that answers it directly, then monitor how assistants respond, and ask an agency for help if capacity is limited. The list only has value once it changes what you publish and what you measure.

Turn prompts into pages and sections. Group similar prompts, then assign each group to one existing page or a new section. Put the direct answer in the first sentence under a question-style heading, then add supporting detail such as steps, specifications or comparisons.

Track mentions over time. Re-run a fixed set of prompts in the assistants your customers use, on a regular schedule, and record whether your brand is mentioned, cited or missing. Answers vary between runs and between assistants, so look for patterns across several checks rather than reacting to a single response.

• Save the exact prompt wording and the date of each check.
• Note which sources the assistant cites.
• Update the matching page when answers are wrong or incomplete.
• Add newly discovered prompts to the list.

When to get help. An agency makes sense if you lack time to write, test and review pages every month. Pugmarks Media starts with a discovery call and a site audit, then agrees a strategy and work plan with you before changes go live. Our team reports monthly, and you can contact us to discuss scope.