Your buyers stopped typing keywords a while ago. They now type full sentences into ChatGPT, Perplexity and Gemini, with a budget, a team size and a constraint attached. Your keyword tool has no record of any of it.
That blind spot is what a prompt research tool fixes. It shows which questions people ask AI engines in your category, which of those questions name brands, and which ones your competitors already own. If you are a marketer, founder or brand manager deciding where to spend the next quarter, this research comes before content, before outreach and before any AEO budget.
Why keyword research breaks in AI search
A keyword is a compressed guess. "CRM agency" could mean a dozen different intents. A prompt removes the guess. "Which CRM works for a 20-person agency that already lives in Slack and needs client reporting" carries the buyer's whole context. The answer engine reads all of it and returns a shortlist of two or three names.
Two things follow. Volume data is thin or missing, because nobody publishes how often a given prompt gets asked. And one intent shows up in hundreds of phrasings, so a single target keyword stops making sense. You research patterns of questions, not single terms.
This is why LLM visibility work starts with the prompt set. Without one, you are measuring your brand against questions nobody asks.
What a prompt research tool should do
Strip away the marketing and the job has four parts.
It finds prompts you would not have written
Your team writes prompts that sound like your website. Buyers do not. A good tool pulls phrasing from sales calls, support tickets and community threads, then expands each seed into the variations people actually use. Look for tools that show you the messy versions, typos and half-sentences included.
It sorts prompts by intent
"What is prompt research" is a learning question. "Best prompt research tool for an agency" is a buying question. Only the second one moves revenue this quarter. The tool should tag each prompt as informational, comparison or purchase so you can put your effort where shortlists get made.
It shows who wins each prompt
A prompt list without answers is a spreadsheet. The tool should run every prompt across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews, then record which brands are named and which URLs are cited. Each prompt gets an owner, and you see which ones have none.
It keeps running
One snapshot lies. Ask the same question five times and you can get five different lists. Repeat runs turn an anecdote into a visibility rate, the share of runs where your brand appears at all.
Build your first prompt set in one afternoon
You do not need software to start. You need 40 prompts and two hours.
Start with sales. Ask for the last ten questions prospects raised before they bought, and write them down word for word.
Add support. Pull the ten most common pre-sales tickets. Remove company names, keep the phrasing.
Mine communities. Search Reddit and industry forums for threads in your category and copy the titles of the ones with long replies. Those are prompts in disguise.
Expand every seed three ways. Add a constraint like budget or team size, a comparison against a named rival, and a role such as CFO or agency owner.
Finally, tag each prompt by intent and funnel stage, and delete duplicates.
Signals worth acting on
Once results land, three patterns deserve your attention.
The first is prompts where a competitor appears in every run and you never do. That is your gap list. The second is prompts where you appear but a rival's page gets the citation. The model knows your name yet trusts someone else's evidence, which is nearly always a content problem. The third is prompts where nobody is named at all. That is open ground, and a strong page can claim it faster than any crowded search result.
Together these give you a ranked backlog. It is LLM brand visibility work in practice. Pick the prompts, fix the pages, re-run, and watch the rate move.
Mistakes that waste the budget
Teams treat one run as truth. They chase rank position in a system that reshuffles on every answer. They buy a tool that supplies volume estimates it cannot back up. They research prompts in English when their market buys in Portuguese or German. And they skip competitors, so the report says "you are visible" without saying visible compared to whom. Tracking AI share of voice fixes that last one.
Questions to ask before you buy
Ask where the prompts come from, real user data or model-generated guesses. Ask how many times each prompt runs per engine. Ask whether you can see the raw answer and cited URLs behind every number. Ask whether you can export the full history. A vendor who answers plainly is worth a trial.
Run the check today
Open ChatGPT, Perplexity and Gemini. Type five questions your buyers ask, exactly as they would. Write down which brands appear. If yours is missing from most, you have your first research finding and the business case for tracking it properly.
LLM Search Console turns that manual check into a scheduled prompt set across every major engine, with citations, sentiment and competitor share of voice in one dashboard. Start with a free check of your brand, then subscribe to this Substack for one practical breakdown a week on getting your brand into AI answers.