Lexical Search
Works with words and exact text signals and remains crucial for identifiers, brands and concrete product terms.
Lexical Search →Academy · Lesson 7
AI Search complements strong search fundamentals.
Semantic techniques help especially where customer language and catalog language do not exactly match. Exact product codes and clear brand names will continue to benefit from precise matching.
Semantic Matching
Tries to recognize substantive agreement when the same meaning is formulated differently.
Semantic MatchingVector Search
Uses numerical representations to find conceptual similarity between query and product information.
Vector Search →Hybrid Retrieval
Combines exact and semantic signals so that precision and wider recall can coexist.
Hybrid Retrieval →Guardrails
Confidence, constraints and fallbacks help prevent wider AI signals from dominating unexplained or unsuitable results.
Guardrails →Evaluation
Rate AI on query sets, relevance judgments and behavioral-KPIs, not the number of models used.
Evaluation →No replacement for data
AI Cannot make missing product knowledge reliable.
Good titles, categories, attributes and identifiers remain necessary. AI signals can make better use of that base, but not structurally replace them.
Query typeStrong signalSupplement
SKU/ModelExactLimited
Product NameLexicalSemantics
DescriptionHybridContext