Restaurant and Local Business Discovery
Building local discovery features on top of search API local-pack results.
The problem
A useful local discovery feature needs current hours, price range, cuisine or category, and reputation signal for potentially thousands of nearby businesses, and no single business directly maintains and publishes all of that in a structured, queryable way.
How the workflow is built
Local-pack-flavored queries scoped by category and geography pull structured business data — name, address, rating, price tier — directly from search results, supplemented by targeted follow-up queries for specific detail (current hours, a recent menu) when the base result is thin. Refresh cadence is tied to how volatile the category is: restaurant hours and closures change faster than, say, a hardware store's.
Example queries
best ramen near [neighborhood]"[restaurant name]" hours todayhighly rated coffee shops [city] open late
Pitfalls to watch for
- Business closures are one of the most common data-quality failures in local discovery — a business search result can persist for months after a business has actually shut down, so a 'permanently closed' signal needs active checking, not just trust in the indexed listing.
- Review and rating aggregation across sources (search-surfaced ratings, a business's own site, third-party review platforms) can disagree meaningfully, and presenting one without context misleads users about how mixed the actual sentiment is.
- Local-pack results are heavily influenced by the searcher's exact location, so a discovery feature built on a single origin point for query purposes needs to account for that skew rather than assuming results are location-neutral.