The Prompts Buyers Actually Type Into AI (and How to Win Them)

Most people optimize toward a fog: "be more visible." Winners optimize toward a target you can actually hit. That target is a handful of prompts your buyers really type, and once you have it written down in their words, the rest of this work stops feeling abstract.

What a money prompt is

A money prompt is a specific, commercial question, phrased the way a buyer would actually ask an AI, where being the named answer would lead to real business. Compare two: "be well known" is a wish with no finish line. "Be named when someone asks ChatGPT who's the best Shopify consultant for DTC brands" is a target you can test any day with a clean yes or no.

Think of it like darts, not fog

"Be more visible" is like being told to throw better without a dartboard in the room. There's nothing to aim at, so there's no way to know if you're improving. A money prompt hangs the board on the wall. Now every piece of content, every mention you earn, every hour spent tidying your profiles has a target to hit and a scoreboard to check. You throw, you look, you adjust. That feedback loop is the entire difference between "doing marketing" and actually getting better at being recommended.

Why the prompt comes first

Here's the thing. You can't aim at a target you haven't named. Choosing your prompts first forces an honest answer to a hard question: who exactly is my buyer, and what would they type? If you can't phrase their question, you don't know them well enough to be their answer yet. The exercise is worth it just for that clarity.

How to write them like a buyer, not a marketer

• Get specific. Not "best consultant". "Best B2B pricing consultant for seed-stage startups." Narrow is winnable and narrow converts.
• Use their words. Buyers type "who should I hire for," "who's the best at," "top people for." Superlatives and all. Match that, don't sanitise it.
• Stay commercial. Favour questions sitting right next to a buying decision over idle curiosity.
• Keep it to five to ten. A focused set you can move beats a sprawling list you can't.

Where to actually find the wording buyers use

Most people guess their money prompts from a desk, and the guesses tend to sound like marketing copy rather than something a real person would type at eleven at night while stressed about a decision. Better sources exist and none of them require special access. Read back through the actual emails and messages where a real client first reached out to you, and notice the words they used to describe their problem, not the words you used to describe your service. Ask a handful of recent clients directly, "if you'd asked an AI assistant before finding me, what would you have typed." Look at the questions in your own inbox, your booking form, your discovery call notes. The phrasing that shows up there, unpolished and a little clumsy, is almost always closer to a real money prompt than anything you'd write in a pitch deck.

Baseline before you build a thing

Before publishing anything, type each prompt into ChatGPT, Gemini and Perplexity and record who gets named, whether you appear, and the reasons given. Screenshot it. That's your "before". Skip it and you'll never be able to prove the work paid off, which is a terrible position to be in when you want to keep doing the work.

The four stages every prompt moves through

Most people's honest first baseline sits at stage one on most of their prompts, and that's completely normal. The point of the exercise isn't to feel bad about a low starting score, it's to know exactly which stage each prompt sits at today so you can see the exact movement next month. Moving from stage one to stage two is a different job than moving from stage three to stage four, and conflating them wastes effort.

Myth: more prompts means more visibility

A tempting shortcut is to build a list of fifty prompts instead of ten, on the theory that more targets means more hits. In practice this usually backfires. Fifty prompts split your limited publishing and outreach time fifty ways, so none of them move fast enough to notice, and a scattered non-result feels exactly like doing nothing, just with more spreadsheets. Five to ten sharp, honestly-chosen prompts that you actually revisit monthly will teach you more, and move faster, than fifty you glance at once and forget. Depth of attention beats breadth of coverage almost every time in this particular exercise.

A simple way to keep score without new software

You don't need a dashboard for this. A plain spreadsheet works fine, one row per prompt, one column per month, and a short note for what stage each prompt sits at, unmentioned, mentioned, cited or recommended, plus who else got named alongside you. Add a column for the exact wording the engine used, since that phrasing often tells you what it's noticing about you, and what it isn't, and a column for who else was named alongside or instead of you, so patterns across competitors become visible over time. Reviewing this sheet once a month takes fifteen minutes and gives you a far clearer picture of your actual progress than any vague sense of "things feel like they're going well," which is exactly the fog this whole exercise exists to replace.

Turn prompts into a scoreboard

Your prompts aren't a one-time exercise. They're the recurring measurement at the heart of everything. Re-run them monthly, mark the move from unmentioned to mentioned to named, and point next month's effort at the specific gaps. Effort you can't measure is effort you can't improve, and this is how you measure it. This pairs naturally with the wider check-up described in how to check whether ChatGPT recommends you, since your money prompts are simply the specific version of that same test.

A worked example: three months of one prompt

Here's a simple, hypothetical timeline to make the process concrete. Month one, a consultant baselines the prompt "who's a good pricing consultant for SaaS startups" and finds they're not mentioned at all, two competitors are. Rather than panic, they publish one detailed article directly answering that exact question and get quoted once in a small industry newsletter. Month two, re-running the same prompt, the consultant now appears mentioned, third in a list of four, alongside the same two competitors. Month three, after publishing a second piece and picking up one more mention, the consultant is now cited by name with a specific detail attributed correctly. They are not yet the lead recommendation, that may take longer, but the direction is unmistakable and the gaps that remain are now specific and known rather than vague and overwhelming.

What happens when the answer is simply wrong

Sometimes a baseline check turns up something worse than being unmentioned, the engine describes you inaccurately, gets your specialty wrong, or names an old job title you left years ago. That's a different and more urgent fix than absence, since when AI invents your credentials it can actively work against you rather than simply overlooking you. Treat a wrong answer as the highest-priority item on your list, above chasing any new prompt, because correcting the record usually matters more than adding to it. Winning the prompt with an inaccurate answer attached to your name does you no favors, it just spreads the inaccuracy faster.

What to do when nobody gets named at all

Occasionally a baseline check comes back with no clear name at all, the engine hedges, lists a category of professional rather than a person, or suggests the reader search further. This is actually useful information, not a dead end. It usually means the question is either too new for anyone to have a strong track record yet, or the field is so fragmented that no single reputation has pulled ahead. Either way, it's an opening rather than a wall. Being the first clear, well-documented, consistently named answer to a question nobody else has claimed is often faster than trying to unseat someone already firmly established on a crowded one. Scan your list of money prompts for the ones returning a shrug rather than a rival, and consider moving one of those up your priority list. An open field with no established name is often the cheapest visibility you'll ever earn, precisely because nobody else has bothered to claim it yet.

The payoff

Win one money prompt and something quietly shifts. Buyers start arriving pre-sold, because a machine they trust said your name before you ever spoke. Then you widen: one won prompt funds the patience to chase the next. That's how a fog turns into a map, and a map turns into a pipeline. If you want the deeper mechanics of what the engine is actually reading when it composes that answer, the anatomy of an AI answer is the natural next stop, and why AI recommends your competitor walks through diagnosing a stubborn loss. Either way, the darts are on the wall now, and every future action can be aimed rather than hoped for.