Parametric Search

What is Parametric Search?

Parametric search (attribute/fielded search) retrieves items by applying structured constraints on numeric, boolean, enum, or hierarchical fields—e.g., price 50–100, in_stock:true, brand:Nike, rating ≥ 4.5. It complements keyword search by enforcing hard rules and precise ranges.

How It Works (quick)

• Schema: Map attributes to proper types (numeric, boolean, keyword, date).
• Indexing: Store filterable fields as doc values/columnar for fast range/term queries.
• Querying: Combine constraints with AND across facets and usually OR within a facet.
• UX: Sliders, checkboxes, chips; show counts and zero-state suggestions.
• Performance: Precompute facet counts; paginate long lists (e.g., brands).

Why It Matters in E-commerce

• Precision: Shoppers land on viable items (price, size-in-stock).
• Speed: Smaller candidate sets → faster ranking/UI.
• Compliance: Enforce assortment/region/ACL rules up front.

Best Practices

• Type hygiene: Use numeric/date types—not strings—for range filters.
• Units & locales: Normalize currencies/units; display localized values.
• Safe defaults: Enable in-stock and relevant locale/region gates.
• SEO control: Canonicalize; whitelist a few facet combos; block infinite param URLs.
• Analytics: Track filter usage, post-filter zero-results, and “filter → add-to-cart”.

Challenges

• Messy attributes (duplicates, casing), facet sprawl, crawl bloat from parameters, and performance on highly cardinal fields.

Examples

• “Sneakers” → filters: Size, In stock in your size, Price 80–150, Waterproof, Brand.
• B2B: voltage range + connector type + certification.

Summary

Parametric search turns clean attributes into fast, precise filtering. Normalize data, choose correct types, set safe defaults, and control crawl space to boost discovery and conversion.