Can you scrape modifier prices (add-ons and customizations)?
Yes! We extract the complete customization tree for each menu item, including nested modifiers like 'Extra Cheese +$1.50', 'Gluten-Free Crust +$3.00', or 'Large Size +$2.50'. This is crucial for understanding total order value and upsell strategies. We capture all conditional pricing (e.g., 'Free topping with combo purchase').
How do you handle location-based pricing differences?
We use GPS-spoofed proxies with precise latitude/longitude coordinates to simulate users in specific neighborhoods or zip codes. This ensures you get the exact pricing and availability a customer in that area would see. We can scrape the same restaurant across multiple locations to identify pricing variations (e.g., downtown vs. suburbs).
Can you identify ghost kitchens and virtual brands?
Yes! We cross-reference physical addresses, phone numbers, and business registration data across multiple restaurant names to identify virtual brands operating from the same kitchen. For example, if 5 different restaurant brands (MrBeast Burger, Guy Fieri's Kitchen, etc.) all share the same address, we flag them as ghost kitchen operations. We can also cluster brands by commissary kitchen operators.
Which food delivery platforms can you scrape?
We scrape all major platforms: UberEats (US, UK, EU, Asia), DoorDash (US, Canada, Australia), Grubhub/Seamless (US), Postmates (merged with Uber), Deliveroo (UK, EU, Asia), Just Eat (UK, EU), SkipTheDishes (Canada), Rappi (LatAm), and regional players like Swiggy/Zomato (India), Meituan (China). We can also scrape direct ordering systems for large chains (Domino's, Pizza Hut apps).
Can you track promotional offers and discounts?
Absolutely! We capture all active promotions including: Buy 1 Get 1 Free offers, Free delivery thresholds (e.g., 'Free delivery on orders $15+'), Platform-wide discounts (e.g., '$10 off first order'), Restaurant-specific deals, Limited-time offers with expiration dates, and Loyalty program rewards. We track when promotions start/end and calculate effective discount percentages.
How do you handle menu changes and updates?
For Standard and Premium packages, we set up scheduled scraping (daily, weekly, or custom intervals) to track: New menu items added, Discontinued items, Price changes (increases or decreases), Modified descriptions or ingredients, and Seasonal menu rotations. We provide change logs showing exactly what changed between scrape runs, helping you identify pricing trends or new competitive launches.
Can you calculate delivery radius and service area coverage?
Yes! For Premium packages, we conduct geospatial analysis by testing delivery availability across hundreds of GPS coordinates in your target area. We generate coverage maps showing: Exact delivery radius boundaries, Areas with limited or no service, Overlap zones where multiple ghost kitchens compete, and Optimal locations for new ghost kitchen openings based on coverage gaps.
Do you capture customer reviews and ratings?
Yes, we can scrape restaurant ratings (overall score, number of reviews), individual review text and star ratings, review dates and timestamps, and platform-specific badges (e.g., 'Top Rated', 'Most Popular'). For Premium clients, we also perform sentiment analysis on review text to identify common complaints or praise themes (e.g., 'food arrived cold', 'generous portions').
Is it legal to scrape food delivery platform data?
Scraping publicly available menu data (prices, items, restaurant names) that users can access without logging in is generally legal under the hiQ Labs v. LinkedIn precedent. However, we adhere to ethical standards: We respect rate limits to avoid disrupting platform services, We don't access user accounts or personal data, We decline projects targeting non-public restaurant sales data or customer information. We recommend consulting legal counsel for compliance with specific use cases.
Can you compare pricing across different delivery platforms?
Yes! This is a common use case for restaurant operators. We scrape the same restaurant's menu from UberEats, DoorDash, and Grubhub simultaneously to identify: Which platform has the highest/lowest menu prices, Platform-specific fees and commissions reflected in pricing, Items that appear on one platform but not others, and Promotion strategies that differ by platform. We deliver side-by-side comparison reports showing where your competitors are charging more or less.
What's your pricing structure for large-scale market analysis (e.g., 10,000+ restaurants)?
For enterprise-scale projects (10,000+ restaurants), we offer custom pricing starting at $0.30-$0.50 per restaurant depending on: Data depth (basic menu vs. full modifiers + reviews), Geographic coverage (single city vs. nationwide), Update frequency (one-time vs. daily monitoring), and Delivery method (batch file vs. API integration). Volume discounts apply for monthly retainers. Contact us for a detailed quote based on your research scope.
How fast can you deliver data for a specific city or region?
Delivery times vary by scope: 500 restaurants (single platform, basic menu): 2-3 days, 2,000 restaurants (cross-platform, with modifiers): 5-7 days, 10,000+ restaurants (enterprise analysis): 10-14 days. Rush delivery (50% surcharge) is available for urgent competitive intelligence needs requiring <48 hour turnaround for up to 1,000 restaurants.
