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🚀 Uber Eats Scraper Actor | (PPR) Pay per results version

🎉 Uber Eats Scraper extracts comprehensive restaurant data from Uber Eats in two ways: by address (or address + query) or by store URLs. Perfect for gathering restaurant insights, menus, and pricing.

✨ Features

• 📍 Option A – By address or address + query: Provide a delivery address (required). Optionally add a query (e.g. cuisine, restaurant name) and a storeType (Uber Eats vertical tab: restaurants, grocery, pharmacy, etc.).

• 🔗 Option B – By URLs: Provide a list of Uber Eats store page URLs to scrape those restaurants directly. When urls is not empty, query, address, and storeType are ignored.

• 🏪 Store type filter: Target restaurants only, grocery, convenience, pharmacy, and other Uber Eats category tabs—without mixing unrelated verticals in your dataset.

• 📊 Rich Detailed Data: For each restaurant you get:

  • 🏠 Restaurant Name & Sanitized Title
  • ⭐ Ratings & Customer Reviews
  • 📍 Complete Address (latitude, longitude)
  • 🍕 Full Menus & Pricing Details
  • 🕑 Opening Hours & Availability
  • 📞 Contact Information (Phone Number & Emails)
  • 🖼️ High-Quality Images (Logo & Hero Image)
  • 📐 Distance & Delivery ETA
  • 🚧 Open/Closed Status & Messages

• 💻 Integrations: Google Sheets, Slack, Zapier & Make.

🛠️ Input

Choose one of the two options below.

Option 1: 📍 Address (or address + query)

Provide a delivery address (required). You can use address alone or add an optional query:

{
"address":"1600 Pennsylvania Avenue NW, Washington",
"query":"pizza",
"storeType":"RESTAURANTS",
"locale":"en-US",
"maxRows":100,
"getMenuCustomizations":false
}

• address (required when not using urls): Delivery location (Address, City, Zip, etc.)
• query (optional): Cuisine type, restaurant name, or keyword. Ignored for browse-only storeType values (see below).
• storeType (optional): Uber Eats vertical tab. Omit for ALL (default—same as the “All” tab). Use RESTAURANTS to limit results to restaurants. Not used when urls is set.
• locale: Language/region (e.g. en-US, fr-FR)
• maxRows: Max stores saved to the dataset when using address/query (each saved restaurant/store counts as one row). Not used in URL mode.
• getMenuCustomizations (optional): When true, loads full customization trees for each menu item (modifiers, add-ons, etc.). Increases scraping time and payload size (default: false).

🏪 Store type (storeType)

Maps to the category tabs on the Uber Eats home screen. The scraper picks the right internal API for each type (home feed, search feed, or category browse feed).

Aliases: HEALTH is treated as PHARMACY;

Examples

{
"address":"71 Avenue Du Général Leclerc, Paris",
"locale":"fr-FR",
"storeType":"GROCERY",
"maxRows":50
}

{
"address":"1600 Pennsylvania Avenue NW, Washington",
"query":"sushi",
"storeType":"RESTAURANTS",
"locale":"en-US",
"maxRows":20
}

⚠️ Behavior change if you omit storeType

If you do not set storeType:

• Address only (no query): Same as before—home-style listing for the delivery area.
• Address + query: Search runs across all verticals (ALL), not restaurants only. For the previous restaurant-only search behavior, set "storeType": "RESTAURANTS".

Option 2: 🔗 Store URLs

Provide a list of store page URLs. When urls is not empty, query and address are ignored:

{
"urls":[
"https://www.ubereats.com/fr/store/mcdonalds-paris-alesia/eHoH6Q_2RRikwI-xKk7qaQ?"
],
"locale":"fr-FR",
"getMenuCustomizations":false
}

• urls: Array of Uber Eats restaurant/store page URLs. All given URLs are scraped (maxRows is ignored in this mode).
• locale: Used for API calls (e.g. fr-FR for French stores).

🚀 Output Example (JSON)

The scraper returns detailed restaurant information, like:

{
"title":"NY Pizza Grill (DC)",
"sanitizedTitle":"NY Pizza Grill (DC)",
"merchantType":"MERCHANT_TYPE_RESTAURANT",
"emails":["contact@mypizzagrill.com"],
"phoneNumber":"+12025473838",
"cuisineList":["Italian","Pizza","American"],
"location":{
"address":"1442 Pennsylvania Ave SE, Washington, DC 20003",
"streetAddress":"1442 Pennsylvania Ave SE",
"city":"Washington",
"country":"US",
"postalCode":"20003",
"region":"DC",
"latitude":38.8799987,
"longitude":-76.9840023,
"geo":{
"city":"washington-dc",
"country":"us",
"neighborhood":"capitol-hill-washington-dc",
"region":"dc"
},
"locationType":"PHYSICAL"
},
"currencyCode":"USD",
"rating":{"ratingValue":4.4,"reviewCount":"700+"},
"storeAvailablityStatus":"AVAILABLE",
"isOpen":true,
"closedMessage":"",
"etaRange":"Delivered in 35 to 55 min",
"fareBadge":"Delivery Fee: $0.99",
"hours":[
{
"dayRange":"Sunday - Thursday",
"sectionHours":[{"startTime":630,"endTime":60}]
},
{
"dayRange":"Friday - Saturday",
"sectionHours":[{"startTime":630,"endTime":150}]
}
],
"categories":["Italian","Pizza","American"],
"categoriesLink":[
{"text":"Italian","link":"/us/category/washington-dc/italian"},
{"text":"Pizza","link":"/us/category/washington-dc/pizza"}
],
"featuredItems":{
"title":"Mozzarella Sticks",
"itemDescription":"5 breaded mozzarella sticks with marinara.",
"price":999,
"priceTagline":"$9.99",
"isSoldOut":false,
"isAvailable":true,
"hasCustomizations":false,
"endorsement":"Popular",
"uuid":"b7ac95d8-11ea-4917-bc31-dd20c2407f29",
"rating":"96%",
"numRatings":4,
"featuredItems":"#1 most liked"
},
"menu":[
{
"catalogName":"Appetizers",
"catalogSectionUUID":"71871c25-cb39-4375-b395-b95fe87f9edc",
"catalogItems":[
{
"title":"Mozzarella Sticks",
"itemDescription":"5 breaded mozzarella sticks with marinara.",
"price":999,
"priceTagline":"$9.99",
"isSoldOut":false,
"isAvailable":true,
"hasCustomizations":false,
"endorsement":"Popular",
"labelPrimary":"$9.99, 96% liked based on 4 reviews.",
"uuid":"b7ac95d8-11ea-4917-bc31-dd20c2407f29",
"rating":"96%",
"numRatings":4
}
]
}
],
"logoImageUrl":"https://example.com/logo-image.jpeg",
"heroImageUrl":"https://example.com/hero-image.jpeg",
"distance":{
"text":"1.1 KM",
"accessibilityText":"1.1 kilometers"
},
"supportedDiningModes":["DELIVERY","PICKUP"],
"storeReviews":[
{
"rating":5,
"text":"Great pizza and quick delivery!",
"timeSinceReview":"1 week ago",
"formattedDate":"March 1, 2025",
"createdAt":"2025-03-01T13:45:00Z",
"eaterName":"John D.",
"contentUUID":"abcd-1234-efgh-5678"
}
],
"featuredReviews":[
{
"rating":5,
"text":"Best pizza in DC!",
"timeSinceReview":"2 months ago",
"formattedDate":"January 1, 2025",
"createdAt":"2025-01-01T13:45:00Z",
"eaterName":"Emily S.",
"contentUUID":"ijkl-9876-mnop-5432"
}
],
"uuid":"bff91760-2d67-54d7-91db-9f6f875086a6",
"url":"https://ubereats.com/us/store/ny-pizza-grill-dc/v_kXYC1nVNeR259vh1CGpg"
}

💻 Integrations & Automation

• Google Sheets 📊: Automatically export restaurant data for analysis.
• Slack 📩: Real-time restaurant data updates delivered instantly.
• Zapier & Make ⚡️: Connect effortlessly with thousands of apps for automated workflows.

📋 Example Use Cases

• Competitive Analysis: Quickly gather detailed competitor menus, prices, and ratings.
• Grocery & retail intelligence: Scrape supermarkets and convenience stores with storeType: "GROCERY" or "CONVENIENCE".
• Data-Driven Marketing: Efficiently collect restaurant data for targeted marketing campaigns (storeType: "RESTAURANTS").
• Research & Development: Accelerate product innovation by analyzing food trends and popularity insights.

💡 Tips

• Set "storeType": "RESTAURANTS" when you use a query and only want restaurants (legacy default behavior).
• maxRows counts stores successfully saved to your dataset, not pages scanned—useful when many listings are filtered out by type.
• Browse-only types (PHARMACY, RETAIL, etc.) work best without a query; the scraper loads that category’s feed for your address.
• urls mode ignores storeType—each URL is scraped as given.

💬 Support & Feedback

Need help or have questions? Please /issues for dedicated support.

🚀 Start scraping effortlessly with Uber Eats Scraper today!