Restaurant Email Scraper

Restaurant Email Scraper ⚡

Struggling to find restaurant contact emails fast—without manually hunting across dozens of sites? Restaurant Email Scraper pulls restaurant email leads, plus phone numbers and social links, from publicly available web data so you can build your outreach list in one run. This restaurant email scraper helps with restaurant contact email finding and restaurant marketing email list building. It’s a practical fit for outreach teams, analysts, and researchers who need local business email scraping at scale. In most runs, you can go from a location list and a restaurant niche to a usable dataset within minutes—rather than hours of copy‑paste work.

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See the Data: Sample Output

Here's a real record from a single run:

{
  "name": "Saffron Spice Kitchen",
  "website": "https://saffronspicekitchen.com",
  "phone": "+1-212-555-0199",
  "full_address": "123 Main St New York NY 10001 US",
  "city": "New York",
  "state": "NY",
  "zip": "10001",
  "country_code": "US",
  "scraped_emails": ["sales@saffronspicekitchen.com", "info@saffronspicekitchen.com"],
  "scraped_phones": ["+1-212-555-0199"],
  "scraped_social_media": ["https://www.instagram.com/saffronspicekitchen/"],
  "emails_found": 2,
  "pages_scraped": 6,
  "avg_rating": 4.6,
  "total_reviews": 248,
  "lat": 40.7128,
  "long": -74.006,
  "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4",
  "scrape_status": "success",
  "email_found": "sales@saffronspicekitchen.com"
}

Field	Type	What It Tells You
name	string	The business name you can use to de-duplicate and personalize outreach for restaurant outreach email automation.
website	string	The restaurant’s website link—your starting point for scraping emails from restaurant websites.
phone	string	The phone associated with the business listing entry, useful when you validate or enrich leads.
full_address	string	A ready-to-use address string for CRM imports and routing to the right location.
city	string	Helps you filter your restaurant database email list by geography.
state	string	Useful for state-level lead segmentation in email list building for restaurants.
zip	string	Postal code for fine-grained targeting and deduplication.
country_code	string	Adds standardized geography context for downstream matching.
scraped_emails	array	All emails found on the website (useful for review and QA across a restaurant contact email finder workflow).
scraped_phones	array	Phones extracted from the site—helpful when the listing phone is missing or incomplete.
scraped_social_media	array	Social profile links extracted from the website for multi-channel prospecting.
emails_found	number	Quick indicator of whether the run actually found usable contacts for a lead.
pages_scraped	number	How much browsing work was done per business during website scraping.
avg_rating	number	Listing rating to help prioritize restaurant lead email scraper results.
total_reviews	number	Reviews count to support lead scoring and sorting in a restaurant directory email extraction flow.
lat / long	number	Coordinates for location-based analytics and routing.
place_id	string	Unique identifier from the listing data to prevent duplicates across runs.
scrape_status	string	Indicates success/failure state for each business record (and helps troubleshoot restaurant email scraper issues).
email_found	string	In the dataset, this is used to flatten results per email when emails were found.

Export your full dataset as JSON, CSV, or Excel from the Apify dashboard.

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Setting It Up

Drop this into your input.json and you're ready to go:

{
  "googleMapsSearchTerm": "coffee shops",
  "googleMapsLocation": ["Miami, Florida", "Orlando, Florida"],
  "maxBusinesses": 50,
  "scrapeMaxBusinessesPerLocation": false,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

Parameter	Required	What It Does
googleMapsSearchTerm	✅	The restaurant niche or business type you want the scraper to search for (for example, “coffee shops”).
googleMapsLocation	✅	One or more target locations to search within (for example, “Miami, Florida”).
maxBusinesses	⬜	Sets your target number of businesses to find (bounded 1–1000). The actor stops once it reaches this goal.
scrapeMaxBusinessesPerLocation	⬜	If enabled, it collects up to maxBusinesses results per location; if disabled, it combines all locations up to a single total limit.
proxyConfiguration	⬜	Proxy settings for scraping. Recommended for larger jobs to improve reliability.
↳ proxy support	⬜	When set to true, the actor uses Apify Proxy for this run.

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What It Does

Restaurant Email Scraper searches for restaurant listings by your search term and location(s), then scrapes contact information from each business’s website. It’s built specifically to help you generate restaurant marketing email list style datasets without manual browsing.

Restaurant email leads from business websites

After collecting businesses, the actor scrapes their websites to find emails. It also extracts phone numbers and social media profiles, so your restaurant contact email finder output is more complete than “email-only” scraping.

Uses your keyword + location targeting

You control the restaurant niche via googleMapsSearchTerm and define the search areas through googleMapsLocation. This makes the workflow feel like a restaurant lead email scraper: pick a geography, pick a niche, get the contact dataset.

Clean, integration-ready dataset rows

Results are written to the default Apify dataset as records with consistent fields such as name, website, scraped_emails, emails_found, pages_scraped, and scrape_status. When emails are found, the dataset output is flattened using email_found, making it easier to import into CRMs and outreach tools.

Built-in proxy support for reliable scraping

For larger-scale restaurant database email builds, proxy configuration is available in the input via proxyConfiguration. Using proxies helps avoid IP blocks and rate limits so runs complete more consistently.

Statuses and failure handling included

Each record includes scrape_status (for example, values like success, failed, error, or no_website depending on what happened). That gives you visibility into incomplete restaurant directory email extraction runs and makes it easier to filter out bad rows during cleanup.

Overall, Restaurant Email Scraper turns location + restaurant niche inputs into a ready-to-use set of restaurant outreach email automation contacts.

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Why Restaurant Email Scraper?

There are plenty of ways to pull data from listing sites—here’s why Restaurant Email Scraper stands out.

Output that’s easy to use for outreach

The dataset includes both listing-level context (like avg_rating, total_reviews, place_id) and website-level contact data (like scraped_emails, scraped_phones, scraped_social_media). That means your restaurant marketing email list work doesn’t stop at raw extraction—you get the metadata you can use to prioritize and segment.

It targets exactly the contacts you need

Instead of returning only directory links, Restaurant Email Scraper scrapes each business’s website for emails and optionally finds related contact signals. This is especially valuable for email scraper for restaurants use cases where you want real outreach addresses, not just “business names.”

Includes resilience and clear results state

When issues happen (like missing websites or scraping problems), records include status fields such as scrape_status and may include scrape_error. That keeps your restaurant marketing email list building process auditable and easier to debug.

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Real-World Use Cases

Here's how different teams put Restaurant Email Scraper to work:

Sales Teams
A regional sales rep needs local restaurant leads for a week-long outreach push. They run the actor with a restaurant niche and target cities, then import the dataset and sort by avg_rating and total_reviews to prioritize high-signal prospects—so prospecting time drops from hours to minutes.

Marketing Agencies
An agency manages multiple campaigns and needs updated contact info for client-approved restaurants. They scrape restaurant marketing email list leads per location, review scraped_social_media for channel expansion, and keep a clean CRM-ready dataset using the consistent fields in the output.

Freelance Researchers
A researcher compiling a restaurant contact email finder dataset for a report needs structured results, not messy spreadsheets. They run Restaurant Email Scraper for their defined locations, then filter by emails_found and enrich with addresses and coordinates (lat / long) for analysis.

Data Engineers & Automation Specialists
A developer building an automation pipeline needs reliable, repeatable data ingestion. They trigger the actor, consume results via the Apify platform outputs, and push each email_found record downstream for lead routing, deduplication, and enrichment—without manual web browsing.

Local Outreach Managers
A community outreach lead wants contacts for restaurants with specific niches in specific neighborhoods. They use scrapeMaxBusinessesPerLocation when they need fairness across locations, and stop at maxBusinesses to keep the dataset size controlled for manageable follow-up.

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How to Run It

No code required. Here's how to get your first results in under 5 minutes:

1. Open the actor on Apify — go to the actor page at console.apify.com and find “Restaurant Email Scraper”.
2. Enter your inputs — set googleMapsSearchTerm (your restaurant niche) and googleMapsLocation (one or more locations). Optionally set maxBusinesses and scrapeMaxBusinessesPerLocation.
3. Configure proxy settings (optional but recommended) — in proxyConfiguration, enable proxy support for improved reliability on larger runs.
4. Start the run — launch and monitor the live logs to see progress while the dataset is being filled.
5. Open the Dataset tab — results appear as the actor pushes data row by row, including fields like scraped_emails, pages_scraped, and scrape_status.
6. Export your results — download as JSON, CSV, or Excel from the Apify dashboard.

The whole setup takes under 5 minutes — results start appearing within seconds of launch.

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Export & Integration Options

Once your data is collected, Restaurant Email Scraper fits directly into your existing workflow.

You can export your dataset from the Apify dashboard as JSON, CSV, or Excel. This is typically enough for spreadsheet-based analysis, CRM imports, and restaurant database email cleanup workflows.

For more advanced setups, you can connect the actor to your systems using the Apify API, or use automation tools such as Zapier or Make to move results into your outreach stack. If you use a webhook-based workflow, downstream actions can start as soon as the run completes.

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Pricing

Restaurant Email Scraper runs on Apify, which includes a free tier — no credit card needed to start. Free tier includes platform credits that are enough for several real test runs, letting you validate your restaurant email scraper results before scaling.

For heavier workloads, you’ll run on Apify’s pay-as-you-go compute model (billed per Actor compute unit). Start free at apify.com — scale up when you need.

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Reliability & Limitations

What We Handle	How
Rate-limit risk	Proxy support is available via proxyConfiguration to improve scraping reliability.
Incomplete businesses (missing websites)	Records are still returned with empty scrape fields and scrape_status like no_website.
Partial progress	Data is pushed to the dataset during website scraping, so you don’t lose everything if a run stops mid-way.
Output clarity	Each record includes scrape_status (and may include scrape_error) so you can filter failures.

Limitations: the actor works on publicly available sources and relies on each business having accessible website content for scraping contact details. If a business does not provide a website or provides no retrievable contact info, you may see empty scraped_emails and emails_found set to 0.

For enterprise-scale needs or custom configurations, reach out and we'll help.

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Frequently Asked Questions

Is there a free plan?

Yes—Apify provides a free tier with platform credits so you can run Restaurant Email Scraper and confirm results before scaling up.

Do I need to log in or create an account on the target platform?

No special login is required to run Restaurant Email Scraper, since it works with publicly available data. If a business listing or website content is not publicly accessible, you may not get contact details.

How accurate is the extracted data?

Accuracy depends on what the business publishes on its website and where contact details appear. The output includes scrape_status and counts like emails_found, so you can quickly validate extraction quality per record.

How many results can I get per run?

You control the limit using maxBusinesses (bounded 1–1000). If you enable scrapeMaxBusinessesPerLocation, it targets up to maxBusinesses results per location; otherwise it combines locations up to a single total limit.

How fresh is the data?

The dataset reflects what’s publicly available at the time of the run. For the most up-to-date restaurant contact email finder results, run the actor on your preferred schedule.

Is this legal? Does it comply with GDPR / CCPA?

Restaurant Email Scraper collects publicly available data and you’re responsible for using it in compliance with GDPR, CCPA, and applicable regulations. Always review your legal basis and your intended use before exporting a restaurant marketing email list.

Can I export to Google Sheets or Excel?

Yes. You can export from the Apify dataset tab as JSON, CSV, or Excel, then import into Google Sheets or your spreadsheet tool of choice.

Can I schedule this to run automatically?

Yes. Apify supports scheduled runs, so you can rerun Restaurant Email Scraper automatically to refresh your restaurant outreach email automation list.

Can I access results via the API?

Yes. You can trigger runs via the Apify API and retrieve results programmatically based on your workflow.

What happens when the actor encounters an error?

When errors occur, records include scrape_status and may include scrape_error, and the run continues where possible. This makes it easier to detect failed leads and re-run only the portions you need.

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Get Help & Use Responsibly

Got a question about Restaurant Email Scraper or a feature you'd like added? Reach out at dataforleads@gmail.com. We can help with practical setup tips—like tightening your maxBusinesses strategy or adjusting how you split results across multiple googleMapsLocation entries.

Restaurant Email Scraper collects publicly available data. It does not access private accounts, login-gated pages, or password-protected content. It’s your responsibility to comply with GDPR, CCPA, and platform Terms of Service when using and storing the results. For data-removal requests, contact dataforleads@gmail.com. Use responsibly, ethically, and only for lawful purposes.