You do not need a tool, a consultant, or a budget to find out whether ChatGPT recommends your padel club. You need five minutes and the discipline to ask the way a player asks.
This is the hands-on check we run at the start of every audit, written up so you can do it yourself. If you want the deeper explanation of why clubs end up missing from these answers, read why your padel club is invisible to ChatGPT. This article is the practical companion to it.
The questions players actually ask
Players do not ask assistants for “premier racket sport facilities”. They type the way they talk. Use these four questions, with your own city or area in them:
- “best padel club near me” (asked from your area, or with your area named)
- “where to play padel in [your city]”
- “padel lessons for beginners in [your city]”
- “where can I book a padel court this evening in [your city]”
Between them, these cover discovery, comparison, coaching, and booking intent. Every one of them ends with the assistant naming somebody. The whole point of the check is to find out whether that somebody is you.
How to run the check
Open a fresh chat in ChatGPT. If you are signed in, be aware that the assistant remembers context, so a clean session gives you a more honest read. You want the answer a stranger gets.
Ask the four questions one at a time. Do not correct the assistant, do not mention your club, and do not lead it. You are eavesdropping on the market, so behave like a player.
Run each question two or three times. Answers vary between runs, and that variation is normal. You are reading for patterns across answers rather than treating any single answer as a verdict.
Then repeat the same questions in Perplexity. It shows numbered citations under every answer, which turns it into a diagnostic tool: you can see exactly which pages the recommendation was built from. How it selects those pages is covered in how Perplexity picks padel sources.
Keep a simple score sheet as you go: question, clubs named, order, details given, sources cited.
Keep the test fair
Two details skew results if you ignore them. The first is location. “Near me” only means something if the assistant knows where you are, so run that question from your area, on the phone a player would use, or swap it for the version that names your city. The second is memory. An account that has discussed your club before will flatter you, which is why the fresh session matters more than any other instruction on this page.
It is also worth asking once with browsing or search enabled if the assistant offers it, and once without. One tests what the model can find about you live; the other tests what it already believes. Clubs often discover they are fine in one mode and missing in the other, and that split tells you where the work is.
How to read the answers
Five things matter in each answer.
Are you named at all? That is the headline result, and the rest of the check explains it.
Where are you named? First mention and seventh mention are different outcomes. Assistants order names by confidence, so position is information.
Are your details right? Check the address, indoor or outdoor courts, coaching, prices, and how the assistant says you take bookings. A club named with stale or wrong details is losing players at the last step.
Who keeps appearing? The competitors that recur across runs are the ones the assistant trusts most in your city. Their websites are worth studying, because whatever signals they carry are the local benchmark.
What does Perplexity cite? If the citations point at your own site, you are the source of record. If they point at directories, aggregators, or a news piece from three years ago, the assistant is working around you.
The absence patterns and what each one means
Pattern one: you never appear. The assistant cannot read or verify you. This is structural: thin content, missing structured data, key details locked in images or a booking widget. It says nothing about the quality of your club and everything about the readability of your information.
Pattern two: you appear, with wrong or old details. Your information disagrees across your site, your maps listing, and the directories. The assistant picked a version, and it picked badly. Consistency work fixes this.
Pattern three: the same one or two competitors dominate every answer. They have done the structural work, deliberately or by luck. Their pages show you the standard your city currently rewards.
Pattern four: no club gets named at all, and the assistant answers with directories or generic advice. Nobody in your area is readable yet. This is the best position on the list, because the first club that fixes its signals inherits the answer.
What a good result looks like
If you are named in most runs, named early, described accurately, and Perplexity cites your own pages, the check is telling you something equally useful: you currently own the answer, and your job is defence. Keep the details current, keep publishing content that answers player questions, and keep watching, because the club that displaces you will do it through the same structural work this check measures.
What to do with the result
If the check went badly, the fix list is structural and well understood: content that answers what players ask, valid structured data, consistent business information everywhere, and a site machines can parse. That is exactly the work of our AI visibility service.
If you would rather have the full picture measured properly, with the same questions tracked month over month, request a free AI visibility audit. We run the check at scale, across platforms, and hand you the prioritised fix list.
Either way, repeat the five-minute check monthly. The answers move, and the clubs that watch them move first.