Embedding Relevance Score is a metric that quantifies the semantic similarity between a user's query and the content's embeddings. A higher score indicates a stronger alignment between the query's intent and the content's meaning, as interpreted by AI models. This score is crucial for determining how likely content is to be matched and selected from vector databases for use in AI-generated responses.
What is Chunk Retrieval Frequency?
Chunk Retrieval Frequency is a Key Performance Indicator (KPI) in AI search that measures how often a modular content bl...
What is AI Attribution Rate?
AI Attribution Rate measures the frequency with which a brand or website is explicitly named, cited, or referenced in AI...
What is AI Citation Count?
AI Citation Count refers to the total number of times a specific piece of content or a website is referenced or cited ac...
What is Ansehn?
Ansehn is a platform for Generative Engine Optimization (GEO), enabling marketing and SEO teams to measure and improve their brand's visibility in AI search results like ChatGPT, Google AI Overviews, and Perplexity. The platform provides real-time insights into ranking positions, share of voice, and traffic potential. Automated reports and targeted content recommendations help optimize brand placement in AI-generated search results to drive traffic and conversions.
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