Google Maps Scraper for Restaurants — Build a Lead List in Minutes

To scrape every restaurant in a city, you point a Google Maps scraper at that city and search for "restaurant" — the scraper grid-searches the area, collects every restaurant pin, and exports a CSV with names, addresses, phones, websites, and emails. With g-maps-scraper.com, this takes 5 minutes for most European cities and the result is a clean spreadsheet you can import into any CRM.

This guide walks through the workflow, what fields you get, and the most common ways B2B teams use restaurant data.

Who scrapes restaurant data and why

Restaurant lists are one of the most-requested categories on every Google Maps scraper. The biggest buyers are:

Food-tech sales teams — POS systems (Toast, Lightspeed), reservation platforms (OpenTable, SevenRooms), online ordering (Uber Eats white-label, Square Online), kitchen software, payment processors. Every food-tech vendor in 2026 needs a current list of every restaurant in their target geography.
Food and beverage suppliers — wholesale meat, produce, wine and spirits, coffee, bakery suppliers building a route plan or expanding into a new region.
Marketing agencies running local campaigns — social media management, photography, menu design, web design for restaurants.
Insurance brokers specializing in hospitality coverage.
Equipment leasing companies — commercial dishwashers, espresso machines, refrigeration.
Recruiters filling kitchen, bar, and front-of-house roles.

What's in the spreadsheet

A typical restaurant scrape returns these columns:

Column	Example
name	Trattoria San Marco
address	Via Roma 12, 00184 Roma RM, Italy
latitude	41.8954
longitude	12.4823
phone	+39 06 4827 1234
website	https://trattoriasanmarco.it
email	[email protected]
category	Italian restaurant
rating	4.6
reviews_count	1,847
price_level	$$
opening_hours	Mon-Sat 12:00-15:00, 19:00-23:00
google_maps_url	https://maps.google.com/?cid=…

Coverage by field varies. Name, address, phone, and website are present for almost every restaurant. Email is present for the 35–50% that publish one on their website (see our email extraction guide). Rating and review count are always present.

Step-by-step: scraping restaurants in your city

Sign up for g-maps-scraper.com — 30 free searches, no credit card.
Type the city name into the search box. The autocomplete covers 33,000 cities worldwide.
Type "restaurant" as the business type. You can also use more specific terms like "italian restaurant," "sushi," "vegan restaurant," "pizzeria" — the scraper will return only matching results.
Click search. The grid-search worker spins up and processes the city. Most European cities finish in 3–8 minutes.
Download the CSV. Open in Excel, Google Sheets, or import directly into HubSpot, Salesforce, Pipedrive, or any other CRM.

Tips for getting better restaurant data

Search by cuisine, not just "restaurant"

A search for restaurant in a major city like Paris or Madrid will return thousands of results. Often you only need a slice — Italian, Japanese, French, vegan, brunch spots, bistros. Searching for the cuisine narrows the result set and gives you a more targeted list.

Include neighbouring cities for complete coverage

Major metros span multiple Google Maps city boundaries. For Greater London, scraping just "London" misses restaurants in Croydon, Wimbledon, or Stratford that are technically separate Google Maps localities. Scrape each surrounding suburb separately and merge the CSVs in Excel.

Filter by minimum review count

Once you have the CSV, filter reviews_count >= 20 to drop ghost listings, recently-opened spots with no track record, and questionable entries. The remaining list is your "real" restaurant universe.

Watch for duplicates across categories

A bistro might be listed as both "french restaurant" and "bistro." If you run two separate scrapes and merge them, de-duplicate on the google_maps_url field, not the name (two different restaurants can share a name).

Sample use case: launching a POS system in Lisbon

Suppose you sell a restaurant POS system and you're launching in Lisbon next quarter. Your workflow:

Scrape "restaurant" in Lisbon → 4,200 results.
Filter reviews_count >= 50 → 2,100 results (drops new and abandoned listings).
Filter email IS NOT NULL → 980 results.
Import the 980 into your CRM, tag them "lisbon-launch-q2."
Run a 3-touch outreach sequence — opening email, follow-up, demo offer — and expect roughly 1.5–3% to book a demo (industry-standard cold-outreach conversion).

That's 15–30 demos from a single afternoon's work, for the cost of a single tier of g-maps-scraper.com.

Compliance for restaurant outreach

Restaurants are businesses, not individuals, so most cold-outreach to scraped restaurant emails is on solid ground under both GDPR (EU "legitimate interest" basis) and CAN-SPAM (US). Standard rules apply: identify yourself, offer an unsubscribe, include a physical address, and honor opt-outs immediately. See our legality guide for full detail.

Try it on your target city

Sign up for free → and run "restaurant" in any city you're targeting. The result is a downloadable CSV in under 10 minutes.

Looking for other categories? The same workflow works for dentists, real estate agents, gyms, and any other Google Maps category.