Fast search still needs real relevance work
Partner
Algolia's index is fast by default. Its relevance is not: out of the box ranking gets you an alphabetized list with extra steps, and the real work is facets, synonyms, and ranking rules tuned to what your users actually search for.
We build the sync pipeline that keeps the index current, usually a CMS webhook into a serverless function, and configure the facets and ranking behind it. We run it in production on our own site's blog and article search, not just client work.
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Why
Where the real work is
- Sync is the hard part, not search
The index is only as fresh as the pipeline feeding it. We wire CMS webhooks into a serverless sync so a content change shows up in search results within seconds, not the next full re-index.
- Facets do the filtering work
Users narrow results with facets more than they type new queries. We model facet attributes around what a visitor is actually deciding between, category, price, availability, not just whatever fields the CMS happened to expose.
- Relevance is a config, not luck
Typo tolerance and AI ranking get the marketing attention, but most relevance problems get solved with boring ranking rules: business logic ordering, custom ranking attributes, and synonyms maintained as content changes.
- It's overkill below a certain size
Site search pays off once a catalog or content library is too big to browse. Under a few hundred items, a good filter and sort UI is often enough, and a hosted search service is overhead you don't need yet.
