Restaurant Email Scraper

Restaurant Email Scraper 📬

Restaurant Email Scraper is an Apify actor that helps you find restaurants in specific locations and extract their contact information—especially email addresses—so you can build a targeted restaurant contact email list faster. It’s designed for use cases like restaurant emails finder workflows, restaurant prospecting email scraper projects, and restaurant CRM email scraping for B2B outreach.

Whether you’re a marketer, sales team, data analyst, or researcher, this tool streamlines scrape restaurant emails efforts by converting public web contact pages into a structured dataset—saving you hours of manual work.

---

🤝 Why choose Restaurant Email Scraper?

Feature	Benefit
✅ All-in-one restaurant email scraping	Finds businesses by location and extracts emails, phone numbers, and social media profiles.
✅ Built-in resilience for scraping	Includes retries/fallbacks for resilience to improve results when websites are inconsistent.
✅ Structured, dataset-ready output	Saves results in a consistent table format so you can export and analyze quickly.
✅ Scale with limits	Lets you cap results with maxBusinesses and optional per-location limits via scrapeMaxBusinessesPerLocation.
✅ Proxy support for reliability	Supports proxyConfiguration to help reduce IP blocking and rate-limit issues.
✅ Automation-friendly for outreach	Outputs contact fields that are easy to plug into CRM lead lists and targeted email campaigns.

---

✨ Key features

• 📍 Restaurant discovery by niche + location: Uses your googleMapsSearchTerm and googleMapsLocation inputs to target restaurants in the areas you care about.
• ✉️ Restaurant emails finder output: Extracts email addresses into dataset rows for downstream lead generation and targeted restaurant outreach emails.
• 📞 Phone number extraction: Collects phone numbers alongside emails for richer restaurant contact information.
• 🔗 Social media profile extraction: Captures social links so you can enrich each restaurant before outreach.
• 🌐 Website-based contact scraping: Pulls contact details from each business website to improve completeness of scraped restaurant contact information.
• 💾 Real-time dataset saving: Pushes results to the Apify dataset as it scrapes, reducing the chance of losing progress.
• 🛡️ Proxy configuration support: Helps improve reliability during larger scrape restaurant emails jobs.

---

🧩 Input

Provide input via an input.json file. Example structure:

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

Input Fields

Field	Required	Description
googleMapsSearchTerm	Yes	Enter the business type or niche for the restaurant email scraping (e.g., coffee shops, dentists). Use Restaurant for general discovery.
googleMapsLocation	Yes	Target geographic location(s) for the search (e.g., Miami, Florida). Provide as a list (e.g., ["New York"]).
maxBusinesses	No	Maximum businesses with emails to find. Range is 1-1000. The scraper stops when this target is reached.
scrapeMaxBusinessesPerLocation	No	Controls how the limit is applied across multiple locations. If true, it aims for up to maxBusinesses results per location; if false, it combines all locations up to a single total limit.
proxyConfiguration	No	Proxy settings for scraping. Recommended for large-scale scraping.
proxyConfiguration • proxy support	No	Enable Apify Proxy (pre-filled as true).

---

📦 Output

After execution, the actor saves results in a dataset view titled Businesses with Contact Information as a flattened structure (one row per email found when emails exist).

Sample output row:

{
  "street_address": "123 Example St",
  "city": "New York",
  "zip": "10001",
  "state": "NY",
  "country_code": "US",
  "full_address": "123 Example St New York NY 10001 US",
  "website": "https://example.com",
  "avg_rating": 4.5,
  "total_reviews": 120,
  "name": "Example Restaurant",
  "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4",
  "phone": "+1 555-123-4567",
  "lat": 40.7128,
  "long": -74.006,
  "scraped_emails": [],
  "scraped_phones": [],
  "scraped_social_media": [],
  "emails_found": 0,
  "pages_scraped": 0,
  "scrape_status": "no_website",
  "email_found": ""
}

Output Fields

Field	Type	Description
name	string	Business name of the restaurant.
website	string	Business website (used to scrape contact details).
phone	string	Phone number associated with the business listing.
full_address	string	Combined address string.
city	string	City from the business listing.
state	string	State from the business listing.
zip	string	ZIP/postal code from the business listing.
country_code	string	Country code associated with the business listing.
scraped_emails	array	List of scraped email addresses (may be empty depending on results).
scraped_phones	array	List of scraped phone numbers from the business website.
scraped_social_media	array	List of scraped social media/profile links.
emails_found	number	Count of emails found for the business.
pages_scraped	number	Number of pages processed while scraping the website.
avg_rating	number	Average rating from the business listing.
total_reviews	number	Total number of reviews from the business listing.
lat	number	Latitude for the business.
long	number	Longitude for the business.
place_id	string	Place identifier from the discovery step.
scrape_status	string	Status text such as success, failed, no_website, or error.

Note on email rows: when emails are found, the actor flattens results by pushing one row per discovered email using email_found, while removing scraped_emails from that flattened row copy.

---

▶️ How to use Restaurant Email Scraper (via Apify Console)

1. Open Apify Console
   Log in at console.apify.com and go to the Actors tab.

2. Find the actor
   Search for Restaurant Email Scraper and open the actor page.

3. Add your inputs
   In the INPUT section, set: googleMapsSearchTerm (your restaurant niche) and googleMapsLocation (one or more locations).

4. Set your limits (recommended)
   Adjust maxBusinesses to control how many businesses you want with emails.
   If you provide multiple locations, decide whether to enable scrapeMaxBusinessesPerLocation.

5. Configure proxy (optional but recommended for scale)
   Use proxyConfiguration if you’re running larger jobs. The form supports proxy support.

6. Run the actor
   Click Run. Watch the logs for progress updates as the actor collects restaurant contacts and scrapes websites for email scraping.

7. Open the dataset & export
   After the run completes, open the output dataset titled Businesses with Contact Information, preview results, and export to your preferred format (JSON/CSV depending on Apify export options).

No coding required—get targeted restaurant outreach emails in minutes. 🚀

---

🧠 Advanced features & SEO optimization

• 🎯 Engineered for restaurant email scraping: Works specifically as a restaurant email scraper for B2B lead building, capturing emails alongside phone and social profiles.
• 🌐 Website-first contact extraction: Improves results by scraping each business website for contact details rather than relying on listing-only data.
• 🧰 Designed for outreach-ready datasets: Pushes results directly into the Apify dataset so restaurant contact email list building is fast and repeatable.
• 🛡️ Proxy support for reliable scraping: Includes proxyConfiguration options to help maintain stability during larger restaurant emails finder projects.
• 💾 Flexible limits for scale: Use maxBusinesses and scrapeMaxBusinessesPerLocation to control output volume like a restaurant prospecting email scraper.

---

📌 Best use cases

• 📈 Marketing teams building restaurant lead lists: Export restaurant emails and contact fields to power targeted outreach campaigns.
• 🧾 B2B sales for local services: Build prospecting sequences by combining email, phone, and social media links for restaurants in chosen cities.
• 🔍 Data analysts enriching local datasets: Use structured fields like place_id, address parts, and rating/review counts alongside emails.
• 🗺️ Local research & competitive intelligence: Compare restaurants across multiple googleMapsLocation values with consistent scraped contact information.
• 🤝 Recruiters and partnerships ops: Find the right contact points for partnership inquiries by collecting restaurant owner email scraper style contact data.
• 💻 CRM pipeline automation: Ingest dataset output into a CRM workflow for restaurant CRM email scraping and follow-up segmentation.

---

🔧 Technical specifications

Supported Input Formats

• ✅ googleMapsSearchTerm: string
• ✅ googleMapsLocation: array of strings (e.g., ["New York"])
• ✅ maxBusinesses: integer within 1-1000
• ✅ scrapeMaxBusinessesPerLocation: boolean
• ✅ proxyConfiguration: object with proxy support

Proxy Support

• ✅ proxyConfiguration supported via Apify Proxy toggle (proxy support)

Retry Mechanism

• ✅ Includes retries/fallbacks for resilience (details are handled internally)

Dataset Structure

• ✅ Dataset view: Businesses with Contact Information
• ✅ Flattened output per email when emails are found
• ✅ Includes business fields (address, coordinates, rating) plus scrape fields (emails/phones/social)

Rate Limits & Performance

• ✅ Controlled via concurrency and scrape limits (tuned for practical speed and stability)
• ✅ Hard stop when maxBusinesses target is reached

Limitations

• ❌ Businesses with no website may not produce email results (they are pushed with scrape_status like no_website depending on settings).
• ❌ Output quality depends on publicly available contact information on each business website.

---

❓ FAQ

What does Restaurant Email Scraper extract?

✅ It extracts business details (like name, website, phone, and address fields) and scrapes websites to collect scraped_emails, scraped_phones, and scraped_social_media, along with counts like emails_found and metadata like pages_scraped and scrape_status.

How do I control how many restaurants I get?

Use maxBusinesses to set the target number of businesses with emails. If you run multiple googleMapsLocation values, you can enable scrapeMaxBusinessesPerLocation to aim for up to maxBusinesses results per location, instead of a single combined total.

Can I scrape multiple locations in one run?

Yes. Provide multiple entries in googleMapsLocation (it expects an array). The actor will process each location and apply your limit strategy based on scrapeMaxBusinessesPerLocation.

What is stored in the dataset?

The dataset view stores the business fields (e.g., full_address, city, state, zip, avg_rating) plus scrape results (e.g., scraped_emails, scraped_phones, scraped_social_media, emails_found, pages_scraped, scrape_status).

Does it save results as it goes?

Yes. It pushes data into the Apify dataset during the website scraping step, so progress is captured instead of waiting for the entire run to finish.

Do I need to provide proxy settings?

No. Proxy settings are optional. However, for large-scale restaurant email scraper runs, proxyConfiguration is recommended to improve reliability.

Is it legal to use this for email list building?

✅ The actor collects information only from publicly accessible sources. You are responsible for complying with applicable laws (including GDPR/CCPA where relevant), spam regulations, and each website’s terms of service.

Can you help with issues or custom requests?

For support or feature requests related to Restaurant Email Scraper, email dataforleads@gmail.com.

---

🤝 Support & feature requests

Want to improve Restaurant Email Scraper for your restaurant email scraper workflows? We’d love to hear from you.

• 💡 Feature Requests: Examples include enhancements like more export formats, additional contact-field parsing, or tighter dataset shaping for restaurant contact email list building.
• 📧 Contact: Reach out at dataforleads@gmail.com.

Your feedback helps shape the roadmap for Restaurant Email Scraper. 🙌

---

🏁 Closing CTA / Final thoughts

If you need the most comprehensive Restaurant Email Scraper for restaurant emails finder workflows, run it with your target niche and locations and let the dataset output do the heavy lifting.

Try Restaurant Email Scraper today and turn public restaurant contact information into outreach-ready results at scale. 🚀

---

Disclaimer

The Restaurant Email Scraper collects information only from publicly accessible sources. It does not access private profiles, authenticated data, or password-protected pages.

You are responsible for ensuring your use of the data complies with applicable laws and regulations (including GDPR/CCPA where relevant), spam regulations, and the terms of service of the websites you scrape.

For data removal requests, contact dataforleads@gmail.com. Always use this tool responsibly, ethically, and for legitimate purposes only.