Uber Eats Email Scraper

Uber Eats Email Scraper

Extract verified Uber Eats emails fast with this powerful Uber Eats Email Scraper! Use keywords, locations & custom domains to target restaurant listings. Perfect for lead gen, outreach, CRM enrichment, and more. Supports proxies & exports in CSV, JSON, Excel.

LEAD_GENERATIONAUTOMATIONOTHERApify

Uber Eats Email Scraper - Fast, Accurate & Affordable ⚡️📩

Unlock the power of Uber Eats email scraping with the Uber Eats Email Scraper! Fast, Accurate & Affordable ⚡️👌, this tool is crafted for marketers, researchers, and businesses looking to collect Uber Eats emails using targeted keywords.


🔍 Key Features

  • Keyword-Based Search: Enter keywords like "john", "marketing", and more to find specific Uber Eats email addresses.
  • Location Filtering: Narrow down results by targeting specific cities or regions.
  • Platform Selection: Specifically scrapes from Uber Eats restaurant listings.
  • Custom Email Domains: Filter emails by custom domains such as @gmail.com, @yahoo.com, and more.
  • Proxy Support: Avoid rate limits with proxy integration for seamless scraping.

📚 Input Parameters

1{
2  "keywords": ["john", "marketing"],
3  "location": "Los Angeles",
4  "platform": "Uber Eats",
5  "customDomains": ["@gmail.com"],
6  "proxyConfiguration": {
7    "useApifyProxy": true
8  }
9}

This Uber Eats Email Scraper uses the following input parameters:

  • keywords:

    • A list of keywords to search for (e.g., ["john", "marketing"]).
  • location:

    • Specify a city or region to filter your search (optional).
  • platform:

    • Scrapes from Uber Eats only.
  • customDomains:

    • Target specific email domains in results (e.g., @gmail.com, @business.com).
  • proxyConfiguration:

    • Optional proxy settings for large-scale or stealth scraping.

📈 Output Structure

Your data will be structured like this:

  • keyword: The keyword used for the search.
  • title: The name of the restaurant or business.
  • description: Text from which the email was extracted.
  • url: The source link from Uber Eats.
  • email: The extracted email address.

Example Output JSON

1[
2  {
3    "keyword": "john",
4    "title": "John's Tacos",
5    "description": "Reach out to us at johnstacosmarketing@gmail.com",
6    "url": "https://www.ubereats.com/store/johns-tacos/123456",
7    "email": "johnstacosmarketing@gmail.com"
8  }
9]

🛠️ How to Use

  1. Enter Keywords & Domains:

    • Add your target keywords and preferred email domains.
  2. Start the Actor:

    • Click Run to begin scraping email addresses from Uber Eats listings.
  3. Enable Proxy (Optional):

    • Add proxy configuration for higher success rate on large jobs.
  4. Export the Data:

    • Export scraped Uber Eats emails in JSON, CSV, or Excel formats.

👩‍🎓 Best Use Cases

  • Food Business Lead Generation: Find emails of restaurant owners or managers.
  • Marketing Campaigns: Build mailing lists for local eateries or food service providers.
  • Competitor Research: Understand who’s operating in the Uber Eats ecosystem.
  • CRM Enrichment: Add verified Uber Eats email data to your contact list.

💬 Support & Feedback

Need help with the Uber Eats Email Scraper or have a suggestion? We’re always listening. Contact our support team for quick assistance and feedback submission.

Frequently Asked Questions

Is it legal to scrape job listings or public data?

Yes, if you're scraping publicly available data for personal or internal use. Always review Websute's Terms of Service before large-scale use or redistribution.

Do I need to code to use this scraper?

No. This is a no-code tool — just enter a job title, location, and run the scraper directly from your dashboard or Apify actor page.

What data does it extract?

It extracts job titles, companies, salaries (if available), descriptions, locations, and post dates. You can export all of it to Excel or JSON.

Can I scrape multiple pages or filter by location?

Yes, you can scrape multiple pages and refine by job title, location, keyword, or more depending on the input settings you use.

How do I get started?

You can use the Try Now button on this page to go to the scraper. You’ll be guided to input a search term and get structured results. No setup needed!