Filter

What is a Filter?

A filter is a constraint applied to a result set—often on a specific field (size, brand, price, stock)—to include or exclude items. Filters can be user-selected (UI controls) or system-enforced (e.g., region/ACL, in-stock by default).

How It Works (quick)

• Types: Value filters (brand: Nike), range filters (price: 50–100), boolean flags (in_stock), geo/region, ACL/security.
• Combination: Usually AND across facets, OR within a facet (configurable).
• Execution: Pre-filter before retrieval (early binding) or post-filter after recall; cache frequent combos.
• State & UX: Chips/breadcrumbs show active filters; “clear all” and per-filter remove.

Why It Matters in E-commerce

• Precision: Shoppers see only viable items (in-stock, in size, in budget).
• Speed: Smaller candidate sets → faster ranking and rendering.
• Compliance: Region/assortment and ACL filters prevent leaks.

Best Practices

• Safe defaults: Enable in-stock and locale/region filters by default.
• Prioritize useful filters: Size, availability, price, rating, key attributes first.
• Prevent dead ends: Hide empty values; show counts; suggest relaxations on zero results.
• Persist & share: Keep filter state in the URL; support bookmarking.
• SEO control: Canonicalize; whitelist only a few high-value filter combinations for indexing.
• Analytics: Track “filter → add-to-cart” and zero-results after filtering.

Challenges

• Over-filtering creates tiny or empty sets; facet sprawl bloats crawl space; messy attributes cause duplicate values.

Examples

• Default in_stock:true on apparel; expose size-in-stock for the user’s size.
• Price presets (Under €50, €50–€100) + rating ≥4.5 + brand groupings.

Summary

Filters are the backbone of efficient product discovery. Default to in-stock and essential attributes, avoid dead ends, preserve state, and keep SEO/crawl under control.