One page per answer engine: how it chooses sources, when it actually searches, how to measure it, and what our own tracking covers.
ChatGPT Search is the browsing mode of ChatGPT: when a question looks like it needs current information, the model issues a web search and writes its answer from the retrieved pages, citing them inline. Without that retrieval step the same question is answered from training memory, which is a different measurement entirely.
Perplexity is an answer engine whose Sonar models retrieve before they write: search first, answer second, with numbered citations attached to the claims. Because grounding is the default rather than a decision, its answers are the closest thing in this category to a direct read on what the live web says about a brand.
Gemini can answer from the model alone or ground its answer in Google Search, and it decides per query which to do. When grounding is used, the response carries grounding metadata — the search queries it ran and the sources it used — which makes the measurement unusually auditable.
Google AI Overviews are AI-generated summaries rendered inside the search results page for some queries. The defining property for measurement is that the surface itself is conditional: for many searches no overview is generated at all, and that absence is not the same as your brand being omitted.
Claude is a general assistant that can answer from its training data or, when web search is enabled, retrieve pages before answering. For brand-visibility measurement the distinction is decisive: an answer without retrieval describes the model's training snapshot, not the current web.
