Restaurant Contact Scraper

Restaurant Contact Scraper

Restaurant Contact Scraper is an Apify actor that automates restaurant data extraction to solve one painful problem: finding the right restaurant contact information (emails, phone numbers, and social links) at scale without manual copy-paste. Built for marketers, lead gen teams, analysts, and researchers, it turns web research into export-ready results fast—so you can improve ROI and move campaigns forward quickly. 🚀

What is Restaurant Contact Scraper? 🔍

Restaurant Contact Scraper is an automated web scraping tool (an Apify actor) designed to scrape restaurant contact information from publicly available web sources associated with businesses you target. It focuses on extracting emails, phone numbers, and social media profiles—then saves everything into a structured Apify dataset so you can use it for restaurant lead generation, contact enrichment, and outreach workflows.

If you need a restaurant email extractor that scales beyond manual research, this restaurant contact scraper is built for efficiency. Use it as a restaurant lead generation tool to quickly build contact lists from local business directory scraping, then feed the data into CRMs or email tools for scraping automation and follow-up at speed.

What Data Does a Restaurant Contact Scraper Collect? 📊

Restaurant Contact Scraper captures structured business identity and contact details—so you can go from “restaurant search” to usable leads in one pipeline. It collects contact info and supporting business context like ratings, reviews, coordinates, and source status.

Data Category	Fields Extracted	Description
Contact	scraped_emails, scraped_phones	Extracted email addresses and phone numbers associated with the restaurant’s online presence
Identity	name, website, place_id	Restaurant business name and website link (plus a place identifier when available)
Address & Location	full_address, city, state, zip, country_code, lat, long	Structured address fields plus latitude/longitude for mapping and geo-segmentation
Discovery & Result Tracking	emails_found, pages_scraped, scrape_status	Counts and status that help you assess coverage and run success
Social Presence	scraped_social_media	Social media profiles/links found alongside the restaurant contact info

What Do Results from Restaurant Contact Scraper Look Like? 👀

Each result is a structured record saved to your Apify dataset (one row per business result produced by the actor). Here’s a realistic example:

{
  "name": "Saffron Spice Indian Cuisine",
  "website": "https://www.saffronspice.com",
  "phone": "+1 305-555-0198",
  "full_address": "1820 Collins Ave Miami FL 33139 US",
  "city": "Miami",
  "state": "FL",
  "zip": "33139",
  "country_code": "US",
  "scraped_emails": [
    "reservations@saffronspice.com",
    "info@saffronspice.com"
  ],
  "scraped_phones": [
    "+1 305-555-0198"
  ],
  "scraped_social_media": [
    "https://www.instagram.com/saffronspice.miami/",
    "https://www.facebook.com/saffronspice.miami/"
  ],
  "emails_found": 2,
  "pages_scraped": 7,
  "avg_rating": 4.6,
  "total_reviews": 312,
  "lat": "25.785445",
  "long": "-80.131375",
  "place_id": "ChIJD7fiBh9u5kcR4fJyo8aK4Vg",
  "scrape_status": "success"
}

The dataset is exported from Apify Console in JSON (default) and can be downloaded as CSV as well.

Core Features: Restaurant Contact Scraper ⚡

Feature	Benefit
✅ Location-based restaurant targeting	Use googleMapsLocation to focus on specific regions for lead generation
✅ Search term driven extraction	Set googleMapsSearchTerm (e.g., “Restaurant”, “coffee shops”, “dentists”) to match your niche
✅ Business result cap	Use maxBusinesses to control volume and cost for restaurant lead generation
✅ Per-location vs global limits	With scrapeMaxBusinessesPerLocation, you can cap per region or combine into one total
✅ Extract emails, phones, and social links	Pulls scraped_emails, scraped_phones, and scraped_social_media for better contact coverage
✅ Structured output for CRM import	Fields like full_address, city, state, and coordinates support downstream enrichment
✅ Proxy support for reliability	Built-in proxy support helps keep scraping automation stable under load
✅ Data cleaning and deduplication-friendly structure	Output fields are ready for filtering, normalization, and deduplication in your pipeline
✅ Status and counts included	emails_found, pages_scraped, and scrape_status make it easy to audit output

Getting Started with Restaurant Contact Scraper 🚀

1. Open Apify Store — Go to apify.com/store and search Restaurant Contact Scraper
2. Click Try for Free — Sign in or create an Apify account
3. Open the Input Tab — Configure your restaurant search settings
4. Set Your Search Term — Use googleMapsSearchTerm to describe your restaurant niche
5. Choose One or More Locations — Add cities/regions in googleMapsLocation
6. Cap the Run — Set maxBusinesses to control how many businesses are collected
7. (Optional) Enable Per-Location Capping — Turn on scrapeMaxBusinessesPerLocation if you want a fixed cap per location
8. Run and Export — Start the actor and download results from the dataset tab

First results are typically fast, and you can iterate quickly by adjusting the search term, location set, and caps.

Ways to Use Restaurant Contact Scraper 💡

• 🎯 Restaurant lead generation — Build segmented business contact lists for outreach and prospecting
• 📣 Email and phone number extraction — Enrich your CRM with scraped_emails and scraped_phones
• 🤝 Local market research — Compare restaurant contact availability across locations using structured outputs
• 📊 Data pipelines — Feed results into BI dashboards and automated workflows with clean fields
• 🔗 Social media outreach support — Use scraped_social_media links to expand your omnichannel approach
• ⚙️ Compliance-minded data work — Focus on publicly available sources and track scrape_status for auditability

Input Parameters — Restaurant Contact Scraper

Provide input via the Apify Console form or input.json.

{
  "googleMapsSearchTerm": "Restaurant",
  "googleMapsLocation": [
    "New York"
  ],
  "maxBusinesses": 5,
  "scrapeMaxBusinessesPerLocation": false,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

Parameter	Type	Required	Default	Description
googleMapsSearchTerm	string	✅ Yes	Restaurant	The business type or niche you want to scrape for email extraction (for example, “coffee shops” or “dentists”)
googleMapsLocation	array	✅ Yes	["New York"]	Target geographic location(s) to focus the extraction on (for example, “Miami, Florida” as a single string value)
maxBusinesses	integer	No	5	Target number of businesses to find (1–1000). The scraper stops when this target is reached
scrapeMaxBusinessesPerLocation	boolean	No	false	If enabled, collect up to maxBusinesses results per location; if disabled, combine locations up to one total limit
proxyConfiguration	object	No	(see example)	Proxy settings for scraping. Recommended for larger-scale scraping automation

Output Format — Restaurant Contact Scraper

The actor saves results into your Apify dataset using this schema:

{
  "name": "Saffron Spice Indian Cuisine",
  "website": "https://www.saffronspice.com",
  "phone": "+1 305-555-0198",
  "full_address": "1820 Collins Ave Miami FL 33139 US",
  "city": "Miami",
  "state": "FL",
  "zip": "33139",
  "country_code": "US",
  "scraped_emails": [
    "reservations@saffronspice.com",
    "info@saffronspice.com"
  ],
  "scraped_phones": [
    "+1 305-555-0198"
  ],
  "scraped_social_media": [
    "https://www.instagram.com/saffronspice.miami/",
    "https://www.facebook.com/saffronspice.miami/"
  ],
  "emails_found": 2,
  "pages_scraped": 7,
  "avg_rating": 4.6,
  "total_reviews": 312,
  "lat": "25.785445",
  "long": "-80.131375",
  "place_id": "ChIJD7fiBh9u5kcR4fJyo8aK4Vg",
  "scrape_status": "success"
}

Field	Label	Format	Description
name	Business Name	text	Restaurant business name
website	Website	link	Restaurant website URL discovered from the business listing
phone	Phone	text	Phone number captured for the business listing
full_address	Address	text	Full concatenated address string
city	City	text	City extracted from the listing/address
state	State	text	State extracted from the listing/address
zip	zip	text	ZIP/postal code extracted from the listing/address
country_code	country_code	text	Country code extracted from the listing/address
scraped_emails	Emails Found	array	List of extracted email addresses
scraped_phones	Phone Numbers	array	List of extracted phone numbers found from the associated website content
scraped_social_media	Social Media	array	List of extracted social media links
emails_found	# Emails	number	Count of scraped emails
pages_scraped	Pages Scraped	number	Number of pages processed during website scraping
avg_rating	Rating	number	Average rating value
total_reviews	Reviews	number	Total review count
lat	lat	text	Latitude value as text
long	long	text	Longitude value as text
place_id	place_id	text	Place identifier associated with the business listing
scrape_status	Status	text	Scraping outcome status for the record (e.g., success/failed/no_website/error)

Why Choose This Restaurant Contact Scraper? 🏆

If you’re looking for restaurant data extraction that produces structured output you can act on immediately, Restaurant Contact Scraper is a strong choice. It combines business contact information scraping (emails, phone numbers, and social media) with helpful metadata like ratings, reviews, and coordinates—so your restaurant lead generation outputs are usable, not just “found.” With proxy support for reliable scraping automation and dataset-ready fields for data cleaning and deduplication, it’s built for repeatable workflows. For questions, reach out via scrapidocontact@gmail.com.

How Many Results Can You Scrape? 📈

Use maxBusinesses (1–1000) to cap the number of businesses the actor targets. If you set scrapeMaxBusinessesPerLocation to true, the scraper aims for maxBusinesses per location; otherwise it combines across locations up to one total limit. Actual email/phone/social coverage depends on what’s publicly listed for each business, but your dataset will include emails_found, pages_scraped, and scrape_status to help you judge quality quickly.

Legal Guidelines for Scraping Restaurant ⚖️

Restaurant Contact Scraper collects information only from publicly available sources. No private or authenticated pages are used. Users are responsible for following applicable laws (including privacy requirements) and for respecting each website’s terms of service and relevant platform policies, especially for marketing communications. Always comply with GDPR/CCPA and local spam regulations when using scraped restaurant contact information. For data removal requests, contact scrapidocontact@gmail.com.

FAQ — Restaurant Contact Scraper ❓

How does the Restaurant Contact Scraper identify data?

It uses your googleMapsSearchTerm and googleMapsLocation inputs to discover restaurant business listings, then scrapes associated publicly available web content to extract emails, phone numbers, and social media links. The actor also provides summary fields like emails_found, pages_scraped, and scrape_status so you can evaluate each record.

What restaurant niches can I scrape with Restaurant Contact Scraper?

You can target a broad range of restaurant-related niches by changing googleMapsSearchTerm. The actor is designed for contact information extraction for businesses matching your niche phrase, such as “Restaurant” by default or other restaurant-adjacent categories you provide.

What do scraped_emails and emails_found mean?

scraped_emails is the array of extracted email addresses for that business. emails_found is the numeric count reflecting how many emails were extracted, which helps you quickly filter for high-yield records during restaurant lead generation.

Why might some businesses have fewer results?

Not every restaurant has publicly listed contact details in the same places. Some may provide emails but not phone numbers, while others may have websites without extractable emails. Use pages_scraped and scrape_status to understand whether scraping succeeded and how much content was processed.

How do proxies help with reliability?

Proxy support is included to improve scraping automation stability and reduce the chance of interruptions when making many requests across domains. This is particularly useful for larger runs where rate limiting handling and consistency matter.

How can I get help or request changes?

If you need support, have a bug report, or want a feature request, contact scrapidocontact@gmail.com. We’ll review feedback and help you get the best results from Restaurant Contact Scraper.

Conclusion 🏁

Restaurant Contact Scraper is a practical, dataset-first way to automate restaurant contact information scraping—turning business listings into structured contact records with emails, phones, social links, and location context. If you’re building restaurant lead generation lists, enrichments, or research datasets, you can ship cleaner leads faster and iterate confidently with scrape_status, counts, and export-ready fields. ✅

Multiple Email Type

Email Types keeps only the kinds of mailbox you want. Every row records what it was classified as in emailType.

Type	What it matches
Personal	Free webmail (Gmail, Outlook, Yahoo, iCloud, ...)
Business	Company domains — free webmail and institutions excluded
Education	.edu, .ac.uk, .edu.au and other academic suffixes
Government	.gov, .mil, .gov.uk, .gc.ca, ...
Non-profit	.org, .ngo, .org.uk, ...

A business found with no email at all is unaffected — whether those rows are wanted is already governed by the existing email-only setting.

Multiple Phone Type

Phone Types does the same for numbers, checked against the line's real type rather than a guess. Numbers on ranges where mobile and landline cannot be told apart are kept rather than dropped, since discarding them would lose good leads.

Outreach links

Field	Meaning
telLink	A clickable tel: link for the primary number
whatsappLink	A wa.me chat link, or empty for a landline or an invalid number
whatsappCapable	Whether the line could support WhatsApp
phoneContacts	Every kept number with its own type, links and validity

whatsappCapable never claims the person uses WhatsApp — only that the number is of a kind that could. Turn the links off with Include WhatsApp links; the capability flag is still reported.