Query Types
Definition
Query types are taxonomies that classify search queries by their structural characteristics, vocabulary, and user behavior patterns — distinct from Search Intent (which focuses on goal) but related.
Baymard’s 8 E-commerce Query Types
Baymard Institute’s taxonomy for e-commerce search (widely referenced):
| Type | Example | Challenge |
|---|---|---|
| Exact product match | ”Nikon D800” | Match by SKU/model number exactly |
| Category | ”cameras” | Return best in category, not just best-selling |
| Non-product | ”return policy” | Service content, not products |
| Symptom | ”blurry photos” | Infer product from problem |
| Compatibility | ”lens for D800” | Structured matching required |
| Comparative | ”mirrorless vs DSLR” | Educational content |
| Thematic | ”birthday gift for photographer” | Discovery + semantic search |
| Branded | ”Nike shoes” | Filter + rank within brand |
Academic Query Type Taxonomies
Factoid vs. Non-Factoid
- Factoid: has a short, definitive answer (“When was Napoleon born?“)
- Non-factoid: requires explanation, opinion, or multiple facts
Keyword vs. Natural Language
- Keyword: “iphone 15 review 2024”
- Natural language: “What do people think of the iPhone 15?”
Head vs. Torso vs. Tail
Based on query frequency:
- Head (>1000 daily): “shoes” — simple, broad, easy to optimize
- Torso (10–1000): “running shoes women” — specific, addressable
- Tail (<10): “waterproof trail running shoes wide toe box women” — rare, hard to optimize individually
Query Length and Complexity
| Length | Characteristics | Best Handled By |
|---|---|---|
| 1 word | Ambiguous, broad | Diversification + personalization |
| 2–3 words | Most common | Standard hybrid retrieval |
| 4–6 words | Specific | Semantic search excels |
| 7+ words | Conversational/complex | Asymmetric Semantic Search, RAG |
Query Type in Search Sampling
When building Judgment Lists, stratified sampling by query type ensures evaluation covers all types proportionally rather than being dominated by head queries.
Related Concepts
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Search Intent — goal-based classification (overlaps)
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Query Understanding — broader processing framework
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Judgment Lists — query type used in sampling strategy
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Diversity Metrics — exploratory/thematic queries need diversity
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Asymmetric Semantic Search — long queries benefit from asymmetric models
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Query Specificity — the degree of constraint in a query; head ↔ tail correlates with low ↔ high specificity
People
- Daniel Tunkelang — query type taxonomy; query understanding framework