A retrieval trigger is the model’s implicit decision to invoke live web retrieval rather than answer from parametric memory. In ChatGPT, approximately 46% of queries trigger retrieval. Shorter, more search-like queries trigger retrieval more often than long conversational prompts.
Retrieval optimization only affects responses where retrieval is triggered. For the roughly 54% of ChatGPT queries answered from parametric memory alone, content structure and crawlability are irrelevant — parametric presence is the only lever. Understanding which query types trigger retrieval determines where to invest optimization effort. Queries that imply current information, specific data, or citations are more likely to trigger retrieval than general explanatory queries on established topics.