Cognitive search uses AI to understand meaning, not just keywords. In online stores, it connects products, content, and customer signals to show smarter results.
Cognitive search is an AI-enhanced search approach that combines NLP, ML, knowledge signals, and vector/semantic retrieval to understand intent and context. It unifies structured and unstructured data—catalogs, guides, FAQs, reviews—so results reflect what the shopper actually means.
Cognitive search blends semantics, signals, and content understanding to answer what shoppers mean, not just what they type—raising relevance, reducing dead-ends, and accelerating decisions.
Cognitive search vs “semantic search”?
Semantic search focuses on meaning via embeddings; cognitive search is broader—semantics plus signals, rules, and content understanding.
Do I need a knowledge graph?
Helpful for relationships (brand ↔ collection ↔ care guide) but start with hybrid retrieval first.
Will this replace merchandising rules?
No—use rules for business goals, let AI handle intent/meaning; combine both in re-ranking.