AI Reputation

AI ReputationAI Reputation describes how a brand is perceived in AI answers, that is how often, how prominently, in what tone and based on which sources it appears. It results from the brand's own website, third-party sources and model behavior.Open glossary entry → goes beyond whether a brand is mentioned. It assesses the quality of the portrayal: share of voiceShare of Voice in AI answers measures the proportion of mentions a brand receives within a prompt set compared to competitors. It indicates the competitive position in AI answers.Open glossary entry → versus competitors, answer position, sentimentSentiment describes the tone in which a brand is portrayed in AI answers, for example positive, neutral, mixed, negative or uncertain. It measures the quality of a mention, not just its presence.Open glossary entry → and the sources that shape the brand's AI image.

AI Reputation cannot be controlled directly. It emerges from the interplay of the brand's own website, third-party sources, user reviews, search results, crawlerCrawling is the process by which a search engine bot fetches a URL and downloads its content. It is the first step before a page can be indexed.Open glossary entry → access, prompt context and model behavior. A critical statement in an AI answer can influence purchase decisions before a user even visits the website.

Professional AI monitoring includes:

• fixed prompt sets and repeated measurement,
• separate evaluation per platform,
• competitor comparison,
• source analysis,
• sentiment evaluation over time.

AI Reputation is improved through topical authority, clear differentiation, genuine root-cause fixes and consistent, credible signals. Manipulation such as fake reviews is risky and counterproductive in the long run.