Uber Eats Menu Scraper

Overview

The Uber Eats Menu Scraper is an Apify actor that extracts restaurant and menu data from Uber Eats, one of the largest food delivery platforms worldwide. It collects restaurant names, cuisines, ratings, delivery fees, delivery times, menu items with prices, descriptions, and images to help with food delivery market analysis and competitive research.

Features

• Search restaurants by location and cuisine type
• Extract restaurant ratings and review data
• Collect delivery fees and estimated delivery times
• Scrape individual menu items with prices and descriptions
• Support for all cuisine types available on Uber Eats
• Configurable result limits for focused data collection

Input Configuration

The actor accepts the following input parameters:

• location - City or address to search restaurants near (e.g., Dallas, TX or New York, NY). Defaults to Dallas, TX.
• cuisine - Cuisine type to filter by (e.g., mexican, italian, chinese, pizza). Defaults to mexican.
• maxRestaurants - Maximum number of restaurants to scrape. Defaults to 20.

Output Format

Each entry in the output dataset includes:

• restaurantName - Name of the restaurant
• cuisine - Cuisine type or category
• rating - Average customer rating
• deliveryFee - Delivery fee amount
• deliveryTime - Estimated delivery time range
• menuItem - Menu item name
• menuItemPrice - Item price
• menuItemDescription - Item description
• imageUrl - Restaurant or food image URL
• location - Search location used
• url - Source URL on Uber Eats
• scrapedAt - Data extraction timestamp

Use Cases

This scraper is valuable for food delivery market researchers comparing restaurant ecosystems across cities, restaurant owners studying their competitors on delivery platforms, food bloggers discovering trending restaurants, delivery service entrepreneurs analyzing pricing and delivery fee structures, and data scientists building food delivery datasets for analysis. The comprehensive menu data enables detailed pricing comparisons across restaurants and cuisines.

Cost and Performance

The actor runs on minimal memory (256 MB) and typically completes within minutes. Pricing follows Apify platform billing with pay-per-event at $1.50 per 1,000 results, suitable for both one-time research and ongoing monitoring of restaurant data.

Integrations

Export restaurant and menu data using Apify integrations to Google Sheets, databases, Slack, Zapier, or custom webhooks. The structured JSON output integrates easily with dashboards, spreadsheets, and business intelligence tools.

Tips and Troubleshooting

• Use specific city names with state abbreviations for the most accurate location matching
• Common cuisine types include mexican, italian, chinese, japanese, indian, pizza, burgers, and thai
• Start with a small maxRestaurants value to preview results before running larger extractions
• If no results appear, try a larger city or a more common cuisine type