How to Check if ChatGPT Recommends Your Website

TL;DR

To check if ChatGPT recommends your website, ask it five prompts: a category search, a direct recommendation, a brand-awareness question, a competitor comparison, and a problem-solving query. Repeat across Gemini, Claude, Perplexity, and Grok, because each gives different answers. Analytics cannot track this, so asking the models directly is the only way.

Someone is asking ChatGPT "what's the best [your category] tool" right now. Maybe they'll get your name. Maybe they won't. You have no way of knowing, because Google Analytics can't track this, and there's no "AI impressions" tab in Search Console. This post shows you how to check if ChatGPT recommends your website, along with four other LLMs that matter.

This matters more than it might seem. As of early 2026, ChatGPT handles over 2 billion queries per day. Gemini has over 750 million monthly users. A growing number of purchase decisions start with an AI assistant, not a search engine. If the AI skips your brand, that traffic is gone. You'll never see a zero in any dashboard, because there's nothing to measure.

The industry calls this AI Visibility — part of a broader shift known as GEO, or Generative Engine Optimization.

So here's what you can do right now: ask.

Five prompts to check your AI Visibility

Open ChatGPT (or any LLM) and run these prompts. Replace the bracketed parts with your actual brand, category, and competitor.

1. Category search

What are the best [your category] tools/websites?

This tests whether the model places you in your category at all. If you sell project management software and ChatGPT lists ten tools without mentioning yours, that tells you something.

2. Direct recommendation

Which website would you recommend for [your service/problem]?

Slightly different from a category search. Here you're asking for a single recommendation — and the model has to pick favorites. Are you one of them?

3. Brand awareness

What is [your brand name]?

Does the model know you exist? Is the description accurate? Some brands get confidently wrong descriptions — wrong founding year, wrong product category, features they don't actually have. Hallucinated brand info is worse than no mention at all.

4. Competitive positioning

Compare [your brand] vs [known competitor]

This reveals how the model frames you against competitors. Pay attention to whether it considers the comparison reasonable. If it says "these aren't really comparable," the model might not understand what you do. And if the comparison isn't in your favor — that's still useful. A "losing" comparison tells you exactly how the model perceives your positioning relative to a competitor.

5. Problem-solving

I need [problem your product solves]. What should I use?

The most natural query pattern. A real person with a real need, asking for help. This is where AI recommendations translate directly into traffic and sign-ups.

What to look for in the answers

After running the prompts, check a few things:

First, the obvious: did it mention you? If your brand doesn't appear in a category search, you have a visibility gap. But showing up isn't everything. Check whether the description is accurate — some models confidently make up features you don't have, which is worse than being ignored. If ChatGPT says you were founded in 2005 when you launched last year, that needs fixing.

Pay attention to tone. There's a gap between "X is a tool that exists" and "I'd recommend X for this." Only the second version sends traffic your way. Also note which competitors the model puts next to you, and whether it provides a link. Perplexity cites sources with URLs. ChatGPT usually doesn't. That difference affects how much real traffic you get from a mention.

Why one LLM isn't enough

Here's the part that makes manual checking harder than it sounds. We tested how different LLMs describe the same brands, and the results diverge in ways you wouldn't expect.

For one domain we checked: Grok described the product accurately with correct details. Gemini fabricated features the product doesn't have. Claude said it didn't have enough information to comment. Same brand, same day, three different answers.

This isn't unusual. The overlap between platforms is surprisingly low — each model has different training data and different real-time sources. Being visible on one platform says nothing about the other four.

The five worth checking: ChatGPT (largest user base), Gemini (Google's ecosystem), Claude (growing in enterprise), Perplexity (research-focused, always cites sources), and Grok (pulls from X/Twitter data).

That's 25 prompt sessions. And LLM answers aren't stable — ask the same question tomorrow and you might get a different brand list. It's not a one-time check.

A faster way

Running 25+ prompts across five platforms, reading each response, tracking changes over time — it's a lot of manual work for something you'll want to repeat regularly.

friendly4AI automates this. It queries all five LLMs, gives you an AI Visibility result plus an AI-Readiness Score based on 40+ technical parameters, and scores your site from 0 to 100. Free, no signup required — just enter your URL.

If you find gaps — your brand missing, wrong descriptions, competitors taking your spot — the next step is understanding what influences these recommendations and what you can change. One concrete fix is opening each section with a direct answer the model can quote, so the LLM has a clean sentence to lift instead of guessing from filler.

Related articles

• How LLMs Choose Which Websites to Recommend — the mechanics behind AI recommendations
• What Is AI Visibility and Why It Matters — broader context on why this matters
• How to Improve Your AI-Readiness Score — actionable steps after you find issues