Brand monitoring

Practically, it means running the same set of brand- and category-level prompts against multiple AI engines — ChatGPT, Gemini, Perplexity, Claude — repeatedly, then logging whether the brand appears, how it is described, and whether the tone is positive, neutral or negative. None of these engines expose impressions data or a results page to rank on, so the only way to get a reading is to ask, repeatedly, and average the outcome. It is not the same as citation tracking: a citation is a linked source an AI answer draws on, while a brand mention is the model naming the brand in its own generated text — a brand can be mentioned with no citation attached, or cited with no mention at all. It is also not classic social listening: social conversations play out in public and can be scanned, but AI conversations happen out of view, so there is no public feed to monitor. The catch is non-determinism. As Ahrefs notes, the same prompt run twice against ChatGPT can return different mentions and different wording, so a single check is one data point, not a verdict — reliable tracking requires volume and repetition over time, not a one-off audit.