DoorDash Restaurant, Business & Menu Scraper

Scrape DoorDash restaurant listings with full menu data, prices, ratings, delivery fees, and reviews. Extract structured restaurant intelligence for market research, price comparison, and lead generation.

Main Use Cases

• Restaurant market research and competitive intelligence
• Menu price monitoring and comparison across locations
• Lead generation for food delivery analytics and restaurant directories
• Cuisine trend analysis and promotional badge tracking
• Delivery time and fee monitoring for logistics insights
• Review sentiment analysis and reputation tracking

How It Works

The Actor uses a Playwright-based crawler with proxy rotation to access DoorDash's JavaScript-heavy pages. It first queries DoorDash's internal search API to discover restaurants, then optionally deep-scrapes each restaurant's menu and reviews. Results are structured into two datasets: restaurant/menu data and individual reviews.

Input Parameters

Field	Type	Required	Default	Notes
searchQuery	string	Yes	"New York, NY"	Location or search term (e.g. "pizza", "Los Angeles, CA")
maxRestaurants	integer	No	10	Maximum number of restaurants to scrape
scrapeMenu	boolean	No	true	Fetch full menu categories and items for each restaurant
maxItemsPerRestaurant	integer	No	20	Max menu items per restaurant (only if scrapeMenu is enabled)
scrapeReviews	boolean	No	false	Fetch reviews for each restaurant
maxReviewsPerRestaurant	integer	No	10	Max reviews per restaurant (only if scrapeReviews is enabled)
proxyConfiguration	object	No	Apify Proxy	Default datacenter; switch to RESIDENTIAL if blocked

Output

The Actor produces two datasets:

Default dataset (restaurants):

• id — DoorDash store ID
• name — Restaurant name
• description — Restaurant description
• cuisine — Array of cuisine/promo tags
• rating — Average rating (1-5)
• reviewCount — Total number of ratings
• deliveryTime — Estimated delivery time
• deliveryFee — Delivery fee
• address — Restaurant address
• imageUrl — Cover image URL
• isDashpass — DashPass partner flag
• priceRange — Price range display
• storeUrl — DoorDash store URL
• menuCategories — Nested menu with categories, items, prices, descriptions, calories

Reviews dataset:

• restaurantId, restaurantName — Parent restaurant reference
• rating — Review rating (1-5)
• text — Review text
• author — Review author name
• date — Review date
• isVerified — Whether the review is verified

Example Input

{
  "searchQuery": "pizza New York, NY",
  "maxRestaurants": 20,
  "scrapeMenu": true,
  "maxItemsPerRestaurant": 30,
  "scrapeReviews": true,
  "maxReviewsPerRestaurant": 15
}

Example Output

{
  "id": "A1B2C3D4E5",
  "name": "Joe's Pizza",
  "description": "Classic New York pizza since 1975",
  "cuisine": ["Pizza", "Italian"],
  "rating": 4.5,
  "reviewCount": "2,340",
  "deliveryTime": "25-35 min",
  "deliveryFee": "$2.99",
  "address": "7 Carmine St, New York, NY 10014",
  "imageUrl": "https://img.doordash.com/...",
  "isDashpass": true,
  "priceRange": "$$",
  "storeUrl": "https://www.doordash.com/store/joes-pizza-12345/",
  "menuCategories": [
    {
      "name": "Popular Items",
      "items": [
        {
          "name": "Cheese Slice",
          "price": "$3.50",
          "description": "Classic cheese pizza slice",
          "tags": ["Bestseller"]
        }
      ]
    }
  ],
  "reviews": [
    {
      "rating": 5,
      "text": "Best pizza in the city!",
      "author": "John D.",
      "date": "2026-08-15",
      "isVerified": true
    }
  ]
}

Integrations & Automation

• Google Sheets — Export restaurant/menu data for collaborative analysis
• HubSpot / Salesforce — Feed restaurant leads into CRM pipelines
• Slack — Get notifications when new restaurants match your search
• Zapier / Make — Automate workflows between DoorDash data and your tools
• Scheduling — Run daily/weekly to monitor price changes and new openings

Related Actors

• DoorDash Reviews Scraper — This actor with reviews enabled
• UberEats Scraper — Cross-platform delivery comparison
• GrubHub Scraper — Additional delivery platform data
• Google Maps Scraper — Location and review enrichment

SEO Keywords

doordash scraper, doordash data, doordash menu scraper, doordash restaurant data, doordash API alternative, food delivery data, restaurant menu scraping, doordash price monitoring, doordash reviews scraper, delivery fee data, restaurant intelligence, doordash extraction, food delivery market research, doordash crawl, restaurant directory data, menu item prices, doordash lead generation, food delivery analytics, doordash dataset, restaurant scraping tool

For AI Agents & LLM Apps

This Actor is callable via the Apify MCP server and Apify API.

Purpose: Extract DoorDash restaurant listings with menus, prices, ratings, delivery fees, and reviews.

Minimal working input:

{ "searchQuery": "pizza New York, NY" }

Variant — full scrape with reviews:

{
  "searchQuery": "sushi Los Angeles, CA",
  "maxRestaurants": 50,
  "scrapeMenu": true,
  "scrapeReviews": true,
  "maxItemsPerRestaurant": 30,
  "maxReviewsPerRestaurant": 15
}

Output fields: id, name, description, cuisine, rating, reviewCount, deliveryTime, deliveryFee, address, imageUrl, isDashpass, priceRange, storeUrl, menuCategories, reviews

Behaviors:

• searchQuery is the only required field — accepts location names, zip codes, or cuisine + location combos
• scrapeMenu defaults to true — set false to skip menu extraction and save time
• scrapeReviews defaults to false — must be explicitly enabled
• Menu item count controlled by maxItemsPerRestaurant (default 20)
• Review count controlled by maxReviewsPerRestaurant (default 10)
• Proxy configuration recommended: RESIDENTIAL for high-volume scraping

Billing: Pay-per-result: $0.0006/restaurant, $0.0003/menu item, $0.0005/review, $0.00005/run start.

Legal & Compliance Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by DoorDash, Inc.

This Actor only accesses publicly available pages and does not bypass authentication, login requirements, or CAPTCHA challenges.

Users are solely responsible for ensuring their use of this Actor complies with DoorDash's Terms of Service and all applicable data-protection laws and regulations.

FAQ

Why use this Actor instead of building my own scraper?

Building and maintaining a web scraper for DoorDash requires handling anti-bot detection, proxy rotation, JavaScript rendering, and ongoing maintenance as the site changes. This Actor provides all of that out of the box with reliable, tested extraction.

What data format does this Actor return?

The Actor returns structured JSON data stored in two Apify datasets: one for restaurant/menu data and one for individual reviews. Both can be exported as JSON, CSV, XML, or Excel.

Can I use this Actor with scheduling?

Yes. Create a task and schedule it to run daily or weekly for monitoring price changes, new restaurant openings, or review trends.

Is there a way to filter by cuisine or price range?

Use the searchQuery field with cuisine-specific terms (e.g. "sushi", "vegan", "pizza") to filter results by cuisine type.

What happens if the Actor encounters a blocked page?

The Actor uses proxy rotation and retry logic. If blocked, switch the proxyConfiguration to RESIDENTIAL proxies for better success rates.