Track how ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, and Claude mention your brand, cite your pages, and recommend competitors. chatobserver turns AI visibility monitoring into a repeatable workflow instead of a spreadsheet chore.
Enter your domain to see how AI assistants describe your brand.
AI visibility is the share of relevant AI-generated answers that mention your brand, cite your content, or position you as a solution. AI visibility tracking turns those answers into measurable mentions, citations, sentiment, and competitor comparisons.
It's a presence score, not a rank
In traditional search there's a position 1. In AI answers, there's either mentioned or not mentioned, plus how prominently, how positively, and how often. AI visibility quantifies all of that across the questions that matter to your customers.
Each AI engine pulls from a different corpus
ChatGPT, Perplexity, Gemini, and Google AI Overviews each use different retrieval methods, different training data, and different citation policies. Being well represented on one gives you no guarantee on another. AI visibility tracks all of them together.
AI search visibility changes over time
Unlike a web analytics dashboard you can check whenever, AI visibility data doesn't exist until you go get it. You have to run structured prompts, capture the raw responses, and parse them. That's what chatobserver does at scale, on your schedule.
Each platform uses different retrieval methods, corpora, and answer formats. A brand visible in ChatGPT can be absent from AI Overviews, AI Mode, Gemini, or Perplexity. chatobserver monitors the whole answer surface from one workspace.
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AI visibility data doesn't exist until you capture it. Unlike web analytics or rank trackers, you cannot observe answer data passively. You need structured prompts, recurring runs, raw responses, and systematic parsing.
That is what chatobserver does across ChatGPT, Google AI Overviews, AI Mode, Gemini, and Perplexity, so your team never has to copy and paste AI answers into a spreadsheet again.
Prompt design
Start with the questions people ask AI about your category: comparison questions, recommendation requests, how-to searches. Segment by intent, persona, and product area.
Scheduled capture
Set hourly, daily, or weekly cadences. Every run timestamps the raw response, preserving the exact answer as it appeared, not a summary or paraphrase.
Parsing & extraction
Each response is parsed for brand names, competitor mentions, cited URLs, and sentiment signals. Entity normalization ensures "chatobserver" and "Chat Observer" both count.
Scoring & trends
Mention frequency, share of answers, citation domain authority, and sentiment roll up to a visibility score. Week-over-week deltas show whether you're gaining or losing ground.
Two small tools for planning your monitoring and making sense of a result.
See how questions, platforms and markets combine into a repeatable sample.
60 answers per round
Assumes one completed answer per question, platform and market in each round. This is a planning estimate, not a price or a plan allowance.
Compare mention rates. More mentions can still mean a lower share of answers.
Compare the same questions, platforms and markets over equivalent periods. This calculator describes the samples you enter; it does not establish statistical significance.
See how AI assistants describe your brand, who they recommend instead, and which sources they cite before you build a full tracking program.