Food delivery analysts
Market coverage
Favorable to scraping
Compare restaurant categories, ratings, price ranges, and menu depth across a city sample or delivery zone.
Food Delivery$50Free
Uber Eats Restaurant Details Scraper
This Uber Eats restaurant details scraper exports public store pages into a structured CSV with restaurant metadata, ratings, address fields, menu categories, dish names, prices, and descriptions. Import the workflow into the UScraper local desktop app when you need to scrape Uber Eats restaurant pages for market research without building a browser automation from scratch.
Output
CSV
Columns
19
Input mode
Multi-URL
Source
Store pages
Template
Free import
At a glance
Export Uber Eats restaurant details and menu data
Restaurant context on every dish row
Each menu item keeps the restaurant name, URL, cuisine, address, coordinates, rating, and review count beside the dish fields. That makes the Uber Eats data extractor useful for spreadsheet analysis, price tracking, and local market comparisons.
Built for prepared store URLs
Add Uber Eats restaurant detail pages to the Navigate block and the workflow loops through them one by one. This avoids relying on search pages that may require an address before listings appear.
Handles dynamic menu rendering
The automation waits, scrolls, runs preprocessing JavaScript, creates hidden export rows, and then lets Structured Export read stable fields instead of brittle visual cards.
Local desktop execution
The browser run and CSV export happen in the desktop app. The supplied graph does not send your URL list or output file through a hosted actor queue.
Who this is for
Who needs to export Uber Eats restaurants to CSV
Restaurant operators
Menu audits
Favorable to scraping
Review public competitor menus, dish naming, price points, and category structure from a controlled list of store pages.
Agencies and researchers
Lead enrichment
Nuanced outcome
Export restaurant details, then enrich discovered sites with the Website Contact Details Scraper.
Use this details scraper after discovery workflows such as the Uber Eats Restaurant Listing Scraper, Google SERP Scraper, or DuckDuckGo Search Results Scraper. Browse the UScraper template library when you need sibling extractors for contacts, search results, or restaurant directories.
How to use
From Uber Eats store URLs to a structured export
2
Add restaurant detail URLs
Replace the starter Navigate URLs with the Uber Eats store pages for your target restaurants, merchant sample, or delivery-market research set.
3
Confirm waits and export path
Keep the page-load wait, short sleep, and element wait in place for dynamic menu rendering. Set the Structured Export save folder before running a batch.
4
Run the loop
UScraper navigates to each URL, waits, scrolls menu content, prepares .uscraper-menu-row records, exports rows, and advances to the next URL.
5
Review the CSV
Open the finished file in Excel, Sheets, or BI tools. Spot-check empty price or error_message rows before using the export for reporting.
Output preview
What the Uber Eats menu scraper exports
The CSV is designed for one row per detected dish, with restaurant-level fields repeated on each row. If a page is blocked, needs address selection, or no menu cards are detected, the workflow can still append a row with an Error_message so failed URLs are visible during QA.
| Restaurant | Restaurant_URL | Cuisine_type | Locality | Rating | Review_count | Dish_category | Dish_name | Price | Description |
|---|---|---|---|---|---|---|---|---|---|
| Alessandro's Place | https://www.ubereats.com/store/alessandros-place/xmUZ1Uj1QDi_9ZCWsn8BAg | Italian | Los Angeles | 4.7 | 120+ | Pasta | Chicken Alfredo | $16.95 | Cream sauce, grilled chicken, and parmesan |
| Carl's Jr. | https://www.ubereats.com/store/carls-jr-501s-western/bUNN3fkNShSK4KLHZbs7LQ | Burgers | Los Angeles | 4.5 | 500+ | Combos | Famous Star Combo | $12.49 | Burger combo with fries and drink |
uber-eats-restaurant-details-scraper.csvColumn
Restaurant
Restaurant or store name from page metadata or visible heading.
Column
Restaurant_URL
Final Uber Eats store URL captured from the browser location.
Column
Cuisine_type
Cuisine data exposed by the page when available.
Column
Price_range
Restaurant-level price range when metadata includes it.
Column
Locality
City or locality parsed from structured page metadata.
Column
Region
State, province, or region.
Column
Postal_code
Postal code when available.
Column
Country
Country value from restaurant address metadata.
Column
Street
Street address when exposed.
Column
Latitude
Latitude from page geo metadata.
Column
Longitude
Longitude from page geo metadata.
Column
Telephone
Telephone value when present in structured data.
Column
Rating
Restaurant rating detected from structured data or page text.
Column
Review_count
Review or rating count detected from metadata or visible copy.
Column
Error_message
Failure note when menu cards are not detected.
Column
Dish_category
Nearest menu section heading above the dish card.
Column
Dish_name
Detected menu item title after noise filtering.
Column
Price
Visible dish price.
Column
Description
Short menu item description when present.
Headers included - additional store URLs append restaurant and dish rows into one file
Frequently asked questions
Scraping Uber Eats can involve platform terms, robots guidance, copyright in menu content, privacy rules, and local law. Use this template only for permitted research, avoid bypassing access controls, keep request volume conservative, and get legal review before commercial reuse or resale.
Before you scale
Practical limits for Uber Eats restaurant scraping
Limitations worth checking before larger runs
Prompts
Some sessions may ask for address, cookies, or verification
Resolve blocking prompts manually and rerun a small sample. The template does not bypass account walls, CAPTCHA, or location gates.
Pacing
Keep batches modest and observable
High-frequency runs can trigger throttling or partial pages. Start with 3-5 restaurant URLs, inspect the CSV, then increase gradually.
Selectors
Dynamic menu layouts can change
Empty dish rows, repeated headers, or missing prices usually mean Uber Eats changed rendered markup or the page did not finish loading.
Download the JSON template, install the desktop app from UScraper download, and use this workflow when you need to export Uber Eats menu and restaurant details into a local CSV.
Get Started
Download and use this template instantly
$50Free
What's Included
- Template JSON file ready to import
- Pre-configured scraping nodes
- Works with UScraper desktop app
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