How do I check my ChatGPT visibility?

Q: How do I check my ChatGPT visibility?

Run your category and direct brand prompts in ChatGPT twice: once in the default model (which answers from training data) and once with browsing or search on (which answers from the live web and cites sources). Note whether you are named, where you rank in any list, and which sources got cited. Repeat each prompt a few times, because answers vary run to run.

Q: What is the difference between ChatGPT's training data and browsing modes?

Without browsing, ChatGPT answers from training data, a frozen snapshot of the web up to the model's cutoff date, so it reflects your historical presence. With browsing or search on, it pulls live pages and usually cites 3-5 sources inline, reflecting the current web. A brand invisible in training data can still surface in browsing if the right pages rank.

Q: Why does ChatGPT recommend competitors instead of my brand?

In the default model, ChatGPT names the brands that were most written about when it was trained, so competitors with more reviews, listicles, and mentions get surfaced and you do not. In browsing mode, it names whoever ranks and gets cited on the live web today. If competitors own the comparison and best-of pages for your category, they win the citation.

Question

How do I check my ChatGPT visibility?

Maciej Grabek · Accepted Answer

ChatGPT has two modes and they give different answers. By default it answers from training data, a snapshot of the web up to the model cutoff that reflects your historical presence. With browsing or search on, it pulls the live web and cites sources. To check your visibility, run your category and brand prompts in both modes, note whether you are named, where you rank, and whether a source is cited. Results vary run to run. The two modes that decide what ChatGPT knows about you ChatGPT answers in one of two ways, and they reflect different things about your brand. Knowing which mode you are in changes how you read the result. Without browsing, ChatGPT answers from training data. That is a frozen snapshot of the web up to the model cutoff date, so it reflects your historical presence: the reviews, listicles, and mentions that existed when the model was trained. If you launched last month, the default model has likely never heard of you. With browsing or search enabled, ChatGPT pulls live pages and usually cites 3-5 sources inline. This reflects the current web and shows you exactly which pages it trusted. A brand invisible in training data can still surface here if the right pages rank for your category today. How to check it, step by step Run each of these in both modes, the default model with no browsing and again with search turned on, and record what you see. Run your category prompts. Ask the question a buyer would ask without naming yourself, like the example below. Note whether you are named at all, and if a list appears, where you rank in it. Run direct brand prompts. Ask "What is [your brand]?" and "Is [your brand] any good?". Check whether the description is accurate and whether it confuses you with a competitor. Note the sources. In browsing mode, ChatGPT cites the pages it used. Record which domains earned the citation: your own site, a review platform, or a competitor comparison page. Repeat each prompt 3-5 times. Answers vary between runs, so a single result is noise. Look for the pattern, not the one reply. A concrete category prompt for a project-management tool aimed at engineering teams: best project management tools for remote engineering teams Run that in the default model and you learn what ChatGPT absorbed about your category from its training data. Run it again with search on and you learn who ranks for it on the live web today. If you appear in one but not the other, that gap tells you where the work is. Why the same prompt gives different answers each run ChatGPT is probabilistic. It samples from a distribution of likely next words, so the same prompt produces different phrasing, a different brand order, and sometimes a different set of names each time. Browsing adds more variance, because the live search results shift and the model may cite different pages on each run. This is why a single check is misleading. A brand that appears in 4 of 5 runs is genuinely visible. A brand that appears once is on the edge. Manual spot-checks catch the obvious cases but miss this frequency signal unless you run every prompt several times and tally the results. Where the manual check runs out The manual method works for a quick read, but it has real limits. You are testing a handful of prompts by hand, on one day, from one account, in one region. ChatGPT personalizes on account history, and results differ by geography, so your check is not what a buyer in another market sees. Running 25 prompts five times each across both modes and tallying the mentions is hours of work, and you would repeat it every week to catch changes. This is the gap avisibli closes. It runs your prompts across ChatGPT and the other four engines, Perplexity, Gemini, Claude, and DeepSeek, on a schedule, then reports your mention rate, average rank, and which sources got cited over time. The manual check tells you where you stand today. Continuous tracking tells you whether you are gaining or losing ground. avisibli is the GEO platform that publishes this answer library. Self-references are limited to topics where a tool-based answer is genuinely useful to readers.