Food Delivery App Scraping for Menus, Prices & Restaurant Signals
Extract structured menu, pricing, fee, rating, and restaurant data from food delivery apps such as DoorDash, Uber Eats, Grubhub, Deliveroo, and Swiggy. Use Nenodata feeds for competitive intelligence, product enrichment, and multi-market analytics.
What this service covers
This page is for multi-app food delivery extraction and comparison. For US restaurant and chain-focused monitoring, see food delivery data scraping for US restaurants and chains.
Menu and item extraction
Collect item names, descriptions, categories, modifiers, allergens, and availability signals across delivery apps.
Price and fee monitoring
Track menu prices, delivery fees, service fees, promotions, and minimum order thresholds by market and time window.
Delivery coverage signals
Capture delivery zones, ETA ranges, and fulfillment status where publicly available for competitive analysis.
Ratings and reputation
Extract ratings, review volume, and cuisine metadata to support restaurant and marketplace benchmarking.
Location context
Normalize restaurant location, city, and market identifiers so multi-app datasets remain comparable.
Platforms commonly scoped
Final coverage depends on source access, geography, and project requirements.
- DoorDash
- Uber Eats
- Grubhub
- Deliveroo
- Swiggy
- Other agreed public delivery marketplaces
Related platform pages: DoorDash USA scraping, Deliveroo data scraping, and restaurant menu data scraping.
Food-delivery hub vs other delivery pages
Use this hub for multi-app, multi-country marketplace programs. Use DoorDash USA for DoorDash-only US feeds, or the US-chains page for multi-app US restaurant menus.
| Source | Best for | Learn more |
|---|---|---|
| Food-delivery hub | Multi-app, multi-country menus, fees, ratings, and restaurant signals | This service |
| DoorDash USA | DoorDash-only US restaurant, menu, and fee feeds | DoorDash USA |
| US restaurants & chains | Multi-app US chain menus, USD prices, ZIP, and fees | US restaurants & chains |
Illustrative multi-app sample
Hub extracts keep country, currency, and marketplace in the row so a London Deliveroo item is not mixed with a Chicago DoorDash item. This sample is illustrative only.
{
"source_name": "deliveroo.co.uk",
"restaurant_name": "Dishoom - Shoreditch",
"city": "London",
"country": "GB",
"menu_category": "Breakfast",
"item_name": "Bacon Naan Roll",
"item_price": "8.90",
"currency": "GBP",
"delivery_fee": "2.49",
"estimated_delivery_time": "25-40 min",
"availability_status": "available",
"rating": "4.7",
"source_url": "https://deliveroo.co.uk/menu/london/shoreditch/dishoom-shoreditch",
"collected_at": "2026-08-12T18:22:11Z"
}When to use this hub instead of a single-app page
Choose this hub when the same schema must cover more than one aggregator and more than one country. A typical program tracks menu price, delivery fee, service fee, ETA, and rating for the same cuisine or chain across DoorDash, Uber Eats, Grubhub, Deliveroo, or Swiggy, then writes one CSV or JSON feed.
Do not use this page for a DoorDash-only US job — that belongs on DoorDash USA scraping. Do not use it for US chain menus with ZIP and USD as the only market — that belongs on US restaurants and chains. Grocery SKUs, pack size, and stock belong on grocery delivery app scraping, not this restaurant-menu hub.
Fields that usually differ by app include modifier trees, promo badges, and fee labels. Scoping confirms which of those stay in the shared schema and which stay app-specific so downstream models do not treat a Deliveroo service fee as a DoorDash dashpass discount.
Use cases
Multi-app competitive pricing
Compare menu and fee structures across platforms in the same city to identify positioning gaps.
Menu trend research
Track emerging items, cuisine shifts, and promo patterns across aggregator ecosystems.
Marketplace and aggregator builds
Seed structured restaurant and menu catalogs for product, analytics, or enrichment workflows.
How it works
Scope apps and markets
Confirm platforms, geographies, fields, cadence, and compliance boundaries.
Extract and normalize
Collect approved public listing data and map it into a stable schema.
Validate and deliver
QA critical fields, then deliver CSV, JSON, API, or scheduled feeds.
- Stable schema mapping across apps and markets
- Validation on pricing, availability, and location fields
- CSV, JSON, API, and scheduled feed delivery
FAQ
Ready to scope food delivery app data?
Share target apps, cities, and fields. Nenodata will propose a scoped sample and delivery plan.
Contact NenodataReady to automate your data?
Tell us what you need. We'll build a custom scraping solution and deliver a free proof-of-concept within 48 hours.