Passage-Level Retrieval
AI citing or using specific sections of a page instead of treating the whole page as one ranking unit.
What is Passage-Level Retrieval?
Passage-Level Retrieval is part of the ai visibility vocabulary. In practice, it describes aI citing or using specific sections of a page instead of treating the whole page as one ranking unit. The exact implementation varies by platform, but the useful meaning stays the same: it helps teams name a specific part of how products, content, AI answers, or commerce operations work.
Why it matters
Passage-Level Retrieval matters because AI answer engines do not behave like traditional search result pages. Brands need to measure mentions, citations, position, and sentiment directly inside generated answers.
How Ranketta uses this concept
Ranketta measures this area by running conversational prompts across AI platforms through real web interfaces, then tracking visibility, share of voice, citations, sentiment, and position.