RRF Rank Contribution refers to the weight or influence a piece of content holds within hybrid ranking systems that utilize Reciprocal Rank Fusion (RRF). RRF is an algorithm that combines results from multiple ranking methods (e.g., traditional keyword-based and modern vector-based retrieval) to produce a more robust and relevant final ranking. This metric helps understand how content contributes to the ultimate re-ranked results presented by AI search engines.
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 Embedding Relevance Score?
Embedding Relevance Score is a metric that quantifies the semantic similarity between a user's query and the content's e...
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 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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