Find Local Businesses

Give it a business type and a place — “restaurants” in “Bondi Junction, Sydney” — and it creates a row per business Google Maps returns.

What it does

• Query is what you would type into the Maps search box — a business type (restaurants, auto service centers), or a type plus a place
• Location is the place to search in — a suburb, a city, or a city and state (Bondi Junction, Sydney, Austin, TX)
• Include reviews opens each place detail page for reviews and richer data. Same cost per business, more work per place.

Only the query is strictly enforced, but a query with no geography searches everywhere and returns whatever Maps considers relevant. Treat location as required for anything you intend to work as a territory.

Listings give you names and websites; they do not give you contacts. Chain Scrape Emails from Website on the website column to get an address you can write to.

How to use it

1. Open the table and click Table → Import → Find Local Businesses
2. Enter the business type as the query and the suburb or city as the location
3. Set a result count — start at 20 while you check the output shape
4. Turn on reviews if you intend to qualify on ratings
5. Run it, map the fields to columns, and click Create Rows

Common use cases

• Build a territory list. A trade plus a suburb returns the businesses in that patch — the whole prospect universe for local services.
• Source SMB leads no B2B database carries. Restaurants, clinics, gyms and trades are on Maps long before they reach a firmographic index.
• Qualify on ratings and review volume. With reviews on, the list sorts itself into established businesses and ones that just opened.
• Find businesses with no website. A missing website column is itself the pitch for anyone selling web or marketing services.

Best practices

• One suburb per run. Broad city-wide queries return the same big chains repeatedly.
• Start at 20 results, confirm the columns, then scale the run
• Turn reviews on only when you will actually filter on them — it is more work per place for data you may ignore
• Dedupe across runs; adjacent suburbs overlap at their borders
• Scrape the website column for emails and phones before buying enrichment credits on the same rows
• Keep the Maps URL column — it is the fastest way to sanity-check a row by eye

Where to next

• Scrape Emails from Website — turn listing websites into contacts
• Google Maps integration — the same scraper as an action column
• google_maps_listings — run it from an AI client over MCP
• Local business outreach — the full workflow, end to end