Restaurants Google Maps Scraper

Scrape restaurants from Google Maps and enrich each result with emails, social media links, cuisine, price range, dietary options, menu highlights, customer review sentiment, online ordering / reservation detection, metro area classification, and restaurant type.

Built for restaurant marketing agencies, food-delivery sales teams, hospitality recruiters, restaurant tech SaaS, and food critics that need structured, CRM-ready data from Google Maps.

What data do you get?

Each scraped restaurant includes up to 35+ fields across these categories:

Category	Fields
Identity	name, category, cuisine
Location	address, city, state, postalCode, country, latitude, longitude
Contact	phone, website, email
Social Media	instagram, facebook, linkedin, twitter
Restaurant	priceRange, dietaryOptions, menuHighlights
Niche	hasOnlineOrdering, orderingPlatform, orderingUrl, hasReservation, reservationPlatform, reservationUrl, isMetroArea, metroName, metroTier, restaurantType, restaurantTypeLabel, restaurantConfidence
Reputation	rating, reviewCount, reviewSentiment (label, score, topThemes, snippets)
Operational	hours, isOpenNow
Metadata	placeId, mapsUrl, scrapedAt, searchTerm, searchLocation

Sample output

{
    "name": "Carbone",
    "category": "Italian restaurant",
    "cuisine": "Italian, Pasta",
    "address": "181 Thompson St",
    "fullAddress": "181 Thompson St, New York, NY 10012, United States",
    "city": "New York",
    "state": "NY",
    "country": "United States",
    "postalCode": "10012",
    "latitude": 40.7280123,
    "longitude": -74.0001234,
    "phone": "+12122541313",
    "website": "https://carbonenewyork.com/",
    "email": "reservations@carbonenewyork.com",
    "instagram": "https://instagram.com/carbonenewyork",
    "facebook": "https://facebook.com/carbonenewyork",
    "linkedin": null,
    "twitter": null,
    "priceRange": "$$$$",
    "dietaryOptions": ["vegetarian", "gluten-free"],
    "menuHighlights": ["Spicy Rigatoni Vodka", "Veal Parmesan", "Caesar Salad"],
    "hasOnlineOrdering": false,
    "orderingPlatform": null,
    "orderingUrl": null,
    "hasReservation": true,
    "reservationPlatform": "resy.com",
    "reservationUrl": "https://resy.com/cities/ny/carbone",
    "isMetroArea": true,
    "metroName": "New York Metro",
    "metroTier": 1,
    "restaurantType": "fine_dining",
    "restaurantTypeLabel": "Fine Dining",
    "restaurantConfidence": "medium",
    "rating": 4.6,
    "reviewCount": 3200,
    "reviewSentiment": {
        "label": "Positive",
        "score": 86,
        "topThemes": ["foodQuality", "service", "ambience"],
        "reviewsAnalysed": 10,
        "avgRating": 4.6,
        "snippets": {
            "positive": [
                "Absolutely incredible Italian-American food. The spicy rigatoni is legendary...",
                "Service was attentive and the atmosphere felt like a 1950s supper club..."
            ],
            "negative": []
        }
    },
    "hours": {
        "Monday": "5:30–11 pm",
        "Tuesday": "5:30–11 pm",
        "Wednesday": "5:30–11 pm",
        "Thursday": "5:30–11 pm",
        "Friday": "5:30 pm–12 am",
        "Saturday": "5:30 pm–12 am",
        "Sunday": "5:30–11 pm"
    },
    "isOpenNow": true,
    "placeId": "0x89c2598ad12f1a8b:0x123abc456def7890",
    "mapsUrl": "https://www.google.com/maps/place/Carbone/...",
    "scrapedAt": "2026-05-23T10:56:47.935Z",
    "searchTerm": "italian restaurant",
    "searchLocation": "New York, USA"
}

How to use

1. Search terms — Enter restaurant categories like italian restaurant, sushi bar, pizza, vegan restaurant, steakhouse.
2. Locations — Enter cities or regions like New York, USA, London, UK, Mumbai, India.
3. Max results — Set how many places to return (up to 500).
4. Toggle enrichment — Enable or disable email extraction, social media, restaurant fields, and niche classification independently.

Input example

{
    "searchTerms": ["italian restaurant", "sushi bar"],
    "locations": ["New York, USA", "Los Angeles, USA"],
    "maxResults": 100,
    "minRating": 4.0,
    "enrichEmails": true,
    "enrichSocials": true,
    "enrichRestaurant": true,
    "enrichRestaurantNiche": true
}

Enrichment pipeline

The scraper runs a 4-stage enrichment pipeline for each restaurant:

1. Google Maps scraping

Extracts name, category, address, phone, website, rating, reviews, hours, coordinates, and place ID directly from Google Maps search results.

2. Restaurant enrichment

• Cuisine — Extracted from Maps category tags and "About" section attributes.
• Price range — Read from the Maps header ($, $$, $$$, $$$$). Maps "Inexpensive / Moderate / Expensive / Very Expensive" labels are mapped to the matching dollar count.
• Dietary options — Scanned from Maps service-options attributes, then falls back to the restaurant website (/menu, /dietary, /allergens pages). Captures vegan, vegetarian, halal, kosher, gluten-free, dairy-free, keto, paleo, and more.
• Menu highlights — Pulls Google Maps "Popular dishes" tiles, with a fallback that scans /menu pages on the restaurant website for headline dish names.
• Review sentiment — Clicks the Reviews tab on Maps, extracts up to 10 reviews, and runs keyword-based sentiment analysis. Returns a sentiment label (Positive/Mixed/Negative), a 0-100 score, top themes (foodQuality, service, ambience, value, waitTime, cleanliness), and representative snippets.

3. Restaurant niche classification

• Online ordering — Checks for ordering buttons on Maps and scans the website for delivery platforms (DoorDash, UberEats, Grubhub, Toast, ChowNow, Square Ordering, Deliveroo, Just Eat, Swiggy, Zomato).
• Reservation — Checks for reservation buttons on Maps and scans the website for booking platforms (OpenTable, Resy, SevenRooms, Tock, TheFork, Yelp Reservations).
• Metro area — Classifies the restaurant location against a curated database of metro areas across USA, UK, India, UAE, Australia, and Canada with tier rankings (1-3).
• Restaurant type — Classifies as fine_dining, casual, fast_food, cafe, food_truck, bar, or unknown based on name keywords, category, cuisine, and price range.

4. Contact enrichment

• Email — Visits the restaurant website and extracts the best email address using domain matching and scoring. Prefers role mailboxes like reservations@, chef@, owner@, manager@, catering@, events@. Tries /contact, /contact-us, /about, /about-us pages as fallback. Filters out generic addresses (noreply, support, etc.).
• Social media — Extracts Instagram, Facebook, LinkedIn, and Twitter/X profile links from the restaurant website.

Use cases

• Restaurant marketing agencies — Build targeted lead lists of restaurants by cuisine, price range, and online presence.
• Food-delivery sales teams — Find restaurants without online ordering for DoorDash / UberEats / Toast onboarding.
• Reservation platform sales — Find restaurants without OpenTable / Resy for outbound pitches.
• Hospitality recruiters — Filter by restaurant type (fine dining vs casual) for chef / FOH placement.
• Market research — Analyze restaurant density, cuisine mix, sentiment, and competitive landscape by metro area.

Proxy

This actor requires residential proxies to avoid Google Maps blocks. Apify residential proxy is configured by default. For best results, use the RESIDENTIAL proxy group.

Cost estimate

Each Google Maps search page processes up to ~20 results. With all enrichment enabled, each restaurant takes 20-40 seconds (website visits for email, dietary options, menu highlights). A typical run of 100 results with full enrichment uses approximately 0.5-1.0 compute units on Apify.

Limitations

• Google Maps may return different results based on proxy location.
• Review sentiment analysis uses keyword matching (no LLM) — works best with 5+ reviews.
• Dietary detection relies on keyword matching and may miss restaurants that only show dietary tags on menu PDFs or images.
• Metro area classification covers major metros in USA, UK, India, UAE, Australia, and Canada.