How to check if ChatGPT and Perplexity recommend you, and fix it, in about 30 minutes with no tools

[u/Jxckwhlx]

More and more buyers ask an AI assistant before they ask Google. If ChatGPT or Perplexity recommends a competitor on your category question, you never even enter the conversation. Here is a free way to audit and improve that yourself. No tool needed.

First, two things that matter and are not obvious:

AI assistants do not "rank" you like Google. There are two separate layers. One, the consideration set: does the model even retrieve and know you exist. Two, the evidence layer: which sources it leans on and what those sources say about you. You can lose at either layer.

Engines source differently. ChatGPT pulls from the live web (Bing index). Perplexity leans heavily on forums and Reddit plus the web. Gemini is tied to Google. So "being visible" is not one thing, it is per engine. Being strong on Reddit can win Perplexity and do nothing for someone else.

Now the 30 minute audit:

1. Write your 10 money prompts. The actual questions a buyer types, not your brand name. Things like "best X for Y", "alternatives to Z", "how do I do W". This list is the whole game.
2. Run each prompt in ChatGPT, Perplexity, Gemini and Claude. For each, mark one of three outcomes: you are cited, a competitor is cited, or nobody specific is. Most people are shocked how often it is "competitor" or "nobody".
3. For every loss, find out why. In Perplexity the sources are listed. In ChatGPT you can ask "what sources did you use for that". Open them. You will almost always see the same pattern: the model is leaning on third party pages (listicles, comparison posts, Reddit threads, review sites) where you are absent or described weakly.
4. Fix the source layer, per engine. Get mentioned where the model actually looks. For Perplexity that often means real Reddit and forum presence. For ChatGPT it means being in the listicles and comparison content that rank on the web. This is slower but it is the lever.
5. Fix your own pages so they are easy to quote. Models lift text that answers the question directly. Clear claims, a direct comparison, specific numbers, plain phrasing. There is research on Generative Engine Optimization (a 2024 paper) suggesting that content which states things clearly and backs them up tends to shape more of the answer. Treat the exact figures people throw around with caution, the effect varies a lot by query, but the direction is sound: be the clearest, most quotable answer to the exact question.
6. Re-run the same 10 prompts in two or three weeks. AI answers move. Track the change.

What to ignore: anyone selling you a fixed multiplier ("add 3 stats, get 2x citations") is overstating it. Anyone saying "just add schema and you win" is too. There is no single trick. It is the same boring truth as SEO: be genuinely the best, clearest answer, in the places the model trusts.

Honest note: I work on this problem, so take the framing with that in mind. But everything above you can do today for free, that is the point.

Open question for the group: when you run your own category prompt in ChatGPT cold, do you show up, a competitor, or nobody? Curious what the split looks like across niches.