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Powered by E-commerce Scraping Tool. Need data from other stores too? The E-commerce Scraping Tool gets you data from UberEats, Amazon, eBay, and any other e-commerce site.

Uber Eats Reviews Scraper

Scrape customer reviews from Uber Eats restaurant pages - reviewer name, date, review text, plus the restaurant's rating, total ratings, review count, and address - with no Uber Eats API required.

What does Uber Eats Reviews Scraper do?

Uber Eats Reviews Scraper collects customer reviews from restaurant and store pages on Uber Eats, the global food-delivery marketplace operating in 11,000+ cities worldwide. On a delivery platform, a restaurant's star rating and recent reviews drive nearly every order decision, so this Actor turns that feedback into structured data you can analyze in bulk. Paste Uber Eats store URLs, set how many reviews you want per place, and export to JSON, CSV, or Excel. No Uber Eats API or login required.

• ⭐ Full review data - reviewer name, date, and review text
• 🍔 Restaurant context - name, rating, total ratings, and review count on every record
• 📍 Location included - the restaurant's address travels with each review
• 🔁 Bulk by place - feed many store URLs and cap reviews per place
• 📊 Clean output - structured records ready for analysis

What data can you extract from Uber Eats reviews?

Can I scrape reviews for multiple Uber Eats restaurants at once?

Yes. Add as many Uber Eats store URLs as you like to startUrls and set maxReviewsPerPlace to cap how many reviews the Actor pulls from each restaurant. That makes it easy to benchmark a whole neighborhood of competitors, or every location of a chain, in a single run.

How does Uber Eats Reviews Scraper work?

1. Add one or more Uber Eats store page URLs to startUrls
2. Set maxReviewsPerPlace to control how many reviews to pull per restaurant
3. Click Start and the Actor visits each place page in turn
4. Results stream to a dataset you can preview or export as JSON, CSV, or Excel

How to use Uber Eats Reviews Scraper

1. Create a free Apify account
2. Paste Uber Eats store page URLs
3. Set how many reviews to collect per restaurant
4. Click Start
5. Download your data from the Dataset tab

Input example

{
"startUrls":[
{"url":"https://www.ubereats.com/store/a-place/acbd123456789"}
],
"maxReviewsPerPlace":10
}

What does the output look like?

Each review is one structured record, with the restaurant's details nested under placeInfo:

{
"authorName":"Jon Doe",
"date":"12/31/23",
"text":"Great!",
"placeInfo":{
"id":"acbd123456789",
"url":"https://www.ubereats.com/store/a-place/acbd123456789",
"name":"The Place",
"rating":4.7,
"numberOfRatings":24,
"numberOfReviews":14,
"address":"This Way, 13, That City"
}
}

Why use Uber Eats Reviews Scraper?

What can you do with Uber Eats review data?

• Restaurant reputation monitoring - restaurant owners and franchise groups track how each location is rated on Uber Eats and catch negative trends early
• Delivery competitor benchmarking - compare your ratings and review volume against rival restaurants delivering in the same neighborhood
• Ghost kitchen and brand audits - operators running multiple virtual brands from one kitchen check sentiment per Uber Eats listing
• Menu and service feedback mining - read review text in bulk to spot recurring complaints about a dish, packaging, or delivery time
• Aggregator market research - food-delivery analysts study rating distributions and review counts across a city's restaurants

For ongoing monitoring, schedule the Actor daily for busy restaurants or weekly for steadier listings.

How much does Uber Eats Reviews Scraper cost?

Uber Eats Reviews Scraper uses Apify's pay-per-event pricing: a small fee each time a run starts, plus a per-result fee of $0.30 per 1,000 reviews. That per-review rate is the same on every plan, and higher plans lower only the per-run start fee. Apify gives you $5 in free usage credits every month on the free plan, enough to collect thousands of reviews at no cost. See the Actor's Pricing tab for the current rates.

How do I run Uber Eats Reviews Scraper via the Apify API?

curl-X POST "https://api.apify.com/v2/acts/e-commerce~ubereats-reviews-scraper/runs?token=YOUR_API_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "startUrls": [{ "url": "https://www.ubereats.com/store/a-place/acbd123456789" }],
 "maxReviewsPerPlace": 10
 }'

What can I integrate Uber Eats Reviews Scraper with?

The Actor runs on the Apify platform, so its data flows into the tools your team already uses:

• Google Sheets and Excel - build a restaurant review dashboard
• Make, Zapier, and n8n - kick off a workflow whenever new reviews appear
• Slack - get pinged when a location's rating drops
• LangChain and MCP - pipe Uber Eats reviews into AI agents and apps
• Apify API and webhooks - load reviews straight into your data warehouse

Limitations

• Collects only publicly visible reviews shown on Uber Eats store pages; it does not access private or account-only data.
• Reviewer names are first-name handles as shown by Uber Eats, so full identities are never available.
• Targets Uber Eats store page URLs; coverage depends on the current page structure and on what the platform displays in your region.

FAQ

Which Uber Eats pages do I give it?

Paste store page URLs - the page for an individual restaurant or shop on ubereats.com. The Actor reads the reviews shown on each of those pages.

Can I collect reviews for several restaurants in one run?

Yes. Add multiple store URLs to startUrls and set maxReviewsPerPlace to cap reviews per restaurant, so you can sweep a whole area or a full chain in a single run.

Does each review include the restaurant's rating?

Yes. Every record carries a placeInfo block with the restaurant's name, overall rating, numberOfRatings, numberOfReviews, and address, so review text always arrives with its context.

How many reviews can I get per restaurant?

You decide with maxReviewsPerPlace. Raise it to pull more history from a place, or keep it low for a quick sentiment sample.

Is there an API for Uber Eats Reviews Scraper?

Yes. Run it programmatically over the Apify REST API - start and schedule runs and pull results as JSON - with apify-client packages for Node.js and Python.

Can I use it with MCP and AI agents?

Yes. Expose the Actor through the Apify MCP server so your AI agents can fetch Uber Eats reviews on demand.

Is it legal to scrape Uber Eats reviews?

Uber Eats Reviews Scraper collects only publicly visible reviews and the first-name handles Uber Eats displays, never private personal data. Scraping public data is generally lawful, but keep your use case compliant and, if it touches personal data, mind GDPR and similar rules. Read is web scraping legal? if you are unsure.

Related Actors

• 🛒 E-commerce Scraping Tool - get product data from UberEats, Amazon, eBay, and any other e-commerce site
• 🍽️ DoorDash Reviews Scraper - collect customer reviews from another major food-delivery marketplace

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