Search
Site search functionality — from basic text matching to AI-powered semantic search.
Why Site Search Matters
Visitors who use your site search convert 3-5x higher than those who browse. They're mission-driven. They know what they want. If your search is bad, they leave. If your search is excellent, they buy.
Search quality is particularly critical for e-commerce. Product search, not category browsing, drives conversion. An e-commerce store with poor search loses 20-30% of potential revenue.
What Site Search Involves
Building searchable index of all content. Must stay in sync when content updates. Real-time indexing vs batch indexing (daily).
Not all matches are equal. "Iphone case" shouldn't rank generic "case" results equally. Requires tuning.
Search must return results in <200ms. Slow search feels broken. Users expect instant results.
"Ipohne" should find "iPhone". Common typos must be handled. Expensive to implement well.
E-commerce especially: filter by price, color, brand, rating. Complex to implement well. Must update counts as filters change.
Track what users search for, what they click, what returns zero results. This data reveals product and content gaps.
Platform Search Quality
Native platform search (WordPress, Shopify, Webflow) is often basic. Search for "blue shirt" might return every shirt and every blue item separately instead of blue shirts specifically.
Basic keyword matching. No advanced relevance tuning. No faceted filtering unless third-party app. Adequate for small catalogs (<500 products); poor for larger ones.
Very basic. Essentially LIKE query in database. Doesn't understand synonyms, typos, or relevance. Slow with large databases.
Limited. Client-side only, loads entire dataset into browser. Works for small sites (<200 items); breaks for larger ones.
Enhanced Search Solutions
For serious search, use a dedicated search engine. These index your content, handle relevance, and provide fast results:
Industry standard for e-commerce and SaaS. Instant typo tolerance, synonyms, faceting, analytics. $0-$4,000+/month depending on data size. Fast implementation. Great documentation.
Open-source or managed (Elastic Cloud). Powerful but complex. Steep learning curve. Self-hosted: cost is mostly engineering time. Elastic Cloud: $8-100+/month.
Simpler than Elasticsearch. Open-source or managed. Good balance of simplicity and power. Growing adoption. $15-200/month managed.
Developer-focused. Excellent UX. Open-source or cloud. Smaller ecosystem. $0/month self-hosted or $15-50/month cloud.
| Platform | Setup Time | Cost (basic) | Customization | Best For |
|---|---|---|---|---|
| Algolia | 1 hour | $0-100/mo | High | E-commerce, SaaS |
| Elasticsearch | 1 week | $8-100/mo | Maximum | Enterprise, large scale |
| Typesense | 2 hours | $15/mo | High | Medium scale, simplicity |
| Meilisearch | 30 min | $0/mo self-host | High | Startups, self-hosted |
| Platform native | Built-in | $0 | None | Small catalogs only |
E-Commerce Product Search
Product search has specific requirements beyond generic search:
Filter by price range, brand, color, size, rating, in-stock status. Essential for large catalogs. Must update counts dynamically as user filters.
Exact color match ("red") should rank higher than substring match (words containing "red"). Product name should rank higher than description.
"Cellphone" = "smartphone" = "mobile". "Tee" = "T-shirt". Manual dictionary of industry-specific synonyms.
When search returns nothing, suggest similar terms or popular products. Bad UX to show blank results.
Products with more sales or higher ratings should rank above low-engagement products. Encourages best-sellers.