Scrape restaurant listings, full menus, pricing, delivery fees, ratings, and availability from DoorDash, Uber Eats, Zomato, Swiggy, Grubhub, and 200+ platforms. Structured, hourly-refreshed food delivery data for analytics, research, and competitive intelligence teams.
Food delivery data scraping is the automated collection of structured restaurant and menu data from online food delivery platforms. These platforms β Zomato, Swiggy, DoorDash, Uber Eats, Deliveroo, Just Eat, and hundreds of regional equivalents β publish vast amounts of publicly accessible data: restaurant listings, complete menus with descriptions and prices, customer ratings, delivery times, service areas, and promotional offers. Scraping this data systematically gives businesses a comprehensive, up-to-date view of the food delivery landscape in any city or region.
The food delivery market is one of the most dynamic sectors in consumer technology. Menus change daily, restaurants update prices frequently, delivery fees fluctuate with demand, ratings shift as new reviews arrive, and promotional offers rotate constantly. Manual monitoring is impractical at any meaningful scale. A programmatic scraping pipeline captures all of this flux automatically, giving you a continuously updated dataset that reflects real market conditions.
DataFlirt's food delivery scrapers are engineered to handle the specific technical challenges these platforms present: JavaScript-heavy single-page applications, session-based authentication flows for geo-targeted menus, pagination across large restaurant catalogs, and dynamic pricing that varies by time of day or user location. We handle all of this using headless browser automation, location spoofing, and smart crawl scheduling so you receive clean, normalised data without the engineering overhead.
Our coverage spans the global food delivery ecosystem. Whether you need Zomato and Swiggy data for the Indian market, Meituan for China, Talabat for the Middle East, or DoorDash and Uber Eats for North America, DataFlirt can collect and normalise across these diverse platforms into a unified output schema that makes cross-market analysis straightforward.
Comprehensive extraction built for reliability, accuracy, and scale.
Extract complete menus including item names, descriptions, prices, sizes, modifiers, customisation options, and availability status.
Track menu price changes, delivery fee fluctuations, and minimum order threshold changes across platforms over time.
Collect restaurant ratings, review counts, customer sentiment text, and rating trajectory to understand brand perception.
Capture estimated delivery times, service area polygons, minimum order values, packaging fees, and surge pricing signals.
Extract restaurant addresses, operational hours, service radius coverage maps, and location-level contact data.
Monitor active discount codes, buy-one-get-one offers, featured placements, sponsored positions, and promotional bundle details.
Every field you need, structured and ready to use downstream.
A proven process that turns any source into clean structured data β reliably.
{ "status": "success", "platform": "zomato", "city": "Bengaluru", "restaurant": { "id": "zmt_blr_2048", "name": "Burma Burma", "cuisine": ["Burmese", "Asian"], "rating": 4.6, "review_count": 2840, "delivery_time_min": 35, "delivery_fee": 39 }, "menu_sample": [ { "item": "Khao Suey", "category": "Mains", "price": 485, "available": true, "is_veg": true } ], "active_promo": "20% off orders above βΉ500" }
Built on proven open-source tools and cloud infrastructure β no vendor lock-in.
Location spoofing at postal code level ensures we retrieve the exact menus, fees, and availability your target users see.
Playwright automation handles React-based food delivery UIs including lazy-loaded menus and infinite scroll restaurant lists.
Platform-specific proxy strategies prevent detection across major food delivery apps during high-frequency hourly refreshes.
Intelligent change detection flags new menu items, price changes, and new restaurants without full re-crawls β saving cost and time.
Data organised by city, neighbourhood, and postal code with GeoJSON service area polygons for spatial analysis.
Unified output schema regardless of source platform β compare Zomato and Swiggy data in the same format.
From solo analysts to enterprise data teams β here's how organizations use this data.
With millions of restaurants competing for delivery orders, intelligence is the difference between visibility and obscurity. DataFlirt gives restaurant groups, aggregator builders, and market researchers a complete, structured view of the food delivery landscape β updated hourly, covering 500+ cities and 200+ platforms, and delivered in formats your analytics stack can consume directly.
Start free and scale as your data needs grow.
For small teams and projects getting started with data.
For growing teams with serious data requirements.
For large organizations with custom requirements.
Everything you need to know before getting started.
Join data teams worldwide using DataFlirt to power products, research, and operations with reliable, structured web data.
