Uber Eats Restaurant Scraper - Menus, Prices, Ratings & Delivery Data

Scrape Uber Eats for restaurant listings, full menus, prices, ratings, delivery info, and cuisine types. Extract data for food delivery market analysis, competitive pricing research, and restaurant discovery. Filter by cuisine type, location, and delivery options.

Features

• Restaurant Search - Search by cuisine, restaurant name, or food type
• Full Menu Extraction - Menu items with prices, descriptions, and categories
• Ratings & Reviews - Extract ratings and review counts
• Delivery Info - Delivery fees, time estimates, and Uber One eligibility
• Cuisine Filtering - Filter by 13+ cuisine types
• Store Profiles - Complete restaurant profile data
• Anti-Detection - Fingerprint injection for stealth browsing
• No Login Required - Works with public Uber Eats data
• Demo Mode - Test with sample data before going live

Who Should Use This Actor?

Restaurant Owners

Monitor competitor menus and pricing on Uber Eats. Track delivery fees and ratings across your market.

Food Industry Analysts

Research food delivery market dynamics, pricing trends, and cuisine popularity by location.

Franchise Operators

Track franchisee pricing and ratings across locations. Monitor brand consistency on Uber Eats.

Marketing Agencies

Build prospect lists of restaurants for marketing services. Identify restaurants needing help with ratings.

Delivery Platform Consultants

Advise restaurants on menu optimization, pricing strategy, and Uber One participation.

Quick Start

Demo Mode (Free Test)

{
  "demoMode": true
}

Search by Cuisine

{
  "scrapeType": "search",
  "searchTerm": "sushi",
  "location": "San Francisco, CA",
  "maxResults": 25,
  "includeMenu": true,
  "demoMode": false
}

Scrape a Specific Restaurant

{
  "scrapeType": "store_profile",
  "storeUrl": "https://www.ubereats.com/store/sakura-sushi",
  "includeMenu": true,
  "demoMode": false
}

Filter by Cuisine Type

{
  "scrapeType": "search",
  "cuisineType": "Mexican",
  "location": "Los Angeles, CA",
  "maxResults": 50,
  "demoMode": false
}

Input Parameters

Parameter	Type	Default	Description
scrapeType	string	search	Type: store_profile, search, menu
storeUrl	string	-	Direct Uber Eats store URL
searchTerm	string	-	Restaurant name, cuisine, or food type
location	string	-	Delivery location (city, state)
cuisineType	string	all	Filter: pizza, chinese, mexican, italian, indian, thai, japanese, american, mediterranean, etc.
includeMenu	boolean	true	Extract menu items and prices
maxResults	integer	50	Maximum restaurants (1-500)
proxyConfiguration	object	-	Proxy settings
demoMode	boolean	true	Return sample data for testing
webhookUrl	string	-	Webhook URL for results delivery

Output Format

{
  "name": "Sakura Sushi",
  "url": "https://www.ubereats.com/store/sakura-sushi",
  "address": "123 Main St",
  "city": "San Francisco",
  "state": "CA",
  "zipCode": "94102",
  "cuisineType": "Japanese",
  "cuisineTypes": ["Japanese", "Sushi", "Asian"],
  "rating": 4.7,
  "reviewCount": 234,
  "priceRange": "$$",
  "deliveryFee": 2.99,
  "deliveryTime": "25-35 min",
  "uberOneEligible": true,
  "isOpen": true,
  "menu": [
    {
      "name": "Dragon Roll",
      "description": "Eel, avocado, cucumber with eel sauce",
      "price": 16.99,
      "category": "Sushi Rolls"
    }
  ],
  "scrapedAt": "2026-01-28T10:30:00.000Z"
}

Pricing (Pay-Per-Event)

Event	Description	Price
store_scraped	Per restaurant scraped	$0.01
menu_item_scraped	Per menu item extracted	$0.001

Example costs:

• 25 restaurants with menus: (25 x $0.01) + (750 x $0.001) = $1.00
• 100 restaurants, profiles only: 100 x $0.01 = $1.00
• Demo mode: $0.00

Common Scenarios

Scenario 1: Competitive Pricing Analysis

{
  "scrapeType": "search",
  "cuisineType": "pizza",
  "location": "Chicago, IL",
  "includeMenu": true,
  "maxResults": 30,
  "demoMode": false
}

Scenario 2: Multi-Platform Comparison

{
  "scrapeType": "search",
  "searchTerm": "burger",
  "location": "New York, NY",
  "maxResults": 50,
  "demoMode": false
}

Run alongside DoorDash and Grubhub scrapers for cross-platform analysis.

Scenario 3: Uber One Market Analysis

{
  "scrapeType": "search",
  "location": "Miami, FL",
  "maxResults": 100,
  "demoMode": false
}

Analyze Uber One participation rates by market.

Webhook & Automation Integration

Zapier / Make.com / n8n

1. Create a webhook trigger in your automation platform
2. Copy the webhook URL to webhookUrl
3. Route results to Google Sheets, Airtable, Slack, etc.

Apify Scheduled Runs

Schedule weekly runs for ongoing menu monitoring.

Official API Alternatives

Uber Eats does not offer a public data API. Partner APIs are for merchants only.

Alternative sources:

• Yelp Fusion API - Restaurant data (free tier available)
• Google Places API - Basic restaurant info ($17/1000 requests)
• DoorDash - No public API (see our DoorDash Scraper)
• Grubhub - No public API (see our Grubhub Scraper)

FAQ

Q: Do I need an Uber Eats account?

A: No. Uses public restaurant data.

Q: Can I filter by Uber One eligible restaurants?

A: Yes. The uberOneEligible field indicates participation.

Q: Why are delivery fees different than what I see?

A: Delivery fees vary by user location and Uber One status. The scraper captures publicly displayed fees.

Common Problems & Solutions

"No restaurants found"

• Check location spelling, try broader search terms
• Some areas have limited Uber Eats coverage

"Rate limited"

• Wait between runs, reduce batch size
• The actor uses anti-detection automatically

"Demo data showing"

• Set demoMode: false - no account required

---

📞 Support

• Actor Arsenal: Full Actor Catalog
• Developer: John Rippy

---

Built by John Rippy | Actor Arsenal