🍴 Uber Eats Scraper [PPR]
Pricing
from $4.99 / 1,000 results
🍴 Uber Eats Scraper [PPR]
🍴 Uber Eats Scraper [PPR] pulls restaurant and menu data from Uber Eats with precision. 🚀 Great for lead gen, market research, and competitive analysis. ⚡ Fast, reliable, and SEO-ready data—automate insights today!
Pricing
from $4.99 / 1,000 results
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Scraper Engine
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Fast, cost-effective Uber Eats scraper that turns a search query + location — or a list of store URLs — into clean, structured store and menu data. Built for scale, with an automatic anti-block proxy ladder and pay-per-result pricing, so you only pay for stores you actually get.
✨ Why Choose Us?
- 🎯 Two ways to scrape — search by address (+ optional query) or paste store URLs directly.
- 🛡️ Self-healing connection — starts direct (cheapest), and only escalates to datacenter → residential proxies when Uber Eats blocks. No fiddly config.
- 🍕 Deep menu data — full menu sections, items, prices, images, and optional customizations (modifiers / add-ons).
- ⚡ Live results — every store is saved the instant it's collected; a crash never loses progress.
- 💸 Pay per result — billed per store, not per minute.
🔑 Key Features
| Feature | Description |
|---|---|
| 📍 Address search | Find stores near any address, optionally filtered by query |
| 🏪 Store verticals | Restaurants, grocery, convenience, pharmacy, alcohol, retail & more |
| 🔗 URL mode | Scrape specific Uber Eats store pages in bulk |
| 🍔 Menu extraction | Sections, items, prices, availability, tags, images |
| 🧩 Customizations | Optional full modifier/add-on trees per item |
| ⭐ Reviews & ratings | Store rating, review count, featured reviews |
| 🛡️ Proxy fallback | Direct → Datacenter → Residential, sticky once escalated |
| 🌐 55+ locales | Scrape Uber Eats across the US, EU, LATAM, APAC and more |
📥 Input
Choose one mode. If urls is provided, address and query are ignored.
{"locale": "en-US","address": "1600 Pennsylvania Avenue, Washington DC","query": "Pizza","storeType": "RESTAURANTS","maxRows": 10,"urls": [],"getMenuCustomizations": false,"proxyConfiguration": { "useApifyProxy": true },"concurrency": 5,"maxRetries": 3}
| Field | Type | Description |
|---|---|---|
locale | string | Uber Eats locale, e.g. en-US, fr-FR. Applies to both modes. |
address | string | Delivery address to search around (search mode). |
query | string | Optional search term (cuisine, brand, dish). |
storeType | string | Vertical tab: ALL, RESTAURANTS, GROCERY, PHARMACY, … |
maxRows | integer | Max stores in search mode (0 = all). |
urls | array | Uber Eats store URLs to scrape directly (bulk). |
getMenuCustomizations | boolean | Fetch full customization trees per item. |
proxyConfiguration | object | Apify Proxy used for the datacenter → residential fallback. |
concurrency | integer | Stores scraped in parallel (1–20). |
maxRetries | integer | Retries per blocked request (1–10). |
📤 Output
Each dataset item is one store:
{"title": "District Detroit Pizza","sanitizedTitle": "District Detroit Pizza","phoneNumber": "+12025551234","emails": [],"cuisineList": ["Pizza"],"location": { "address": "…", "city": "Washington", "country": "US", "latitude": 38.9, "longitude": -77.0 },"currencyCode": "USD","rating": { "ratingValue": 4.8, "reviewCount": "260+" },"storeAvailablityStatus": "AVAILABLE","isOpen": true,"etaRange": "Delivered in 20 to 30 min","hours": [ … ],"categories": ["$", "Pizza"],"categoriesLink": [ … ],"menu": [ { "catalogName": "Pizzas", "catalogItems": [ … ] } ],"logoImageUrl": "https://…","heroImageUrl": "https://…","uuid": "…","url": "https://ubereats.com/store/…","merchantType": "MERCHANT_TYPE_RESTAURANT","distance": { "text": "2.2 mi", "accessibilityText": "2.2 miles" },"supportedDiningModes": [ … ],"storeReviews": [ … ],"featuredReviews": [ … ]}
🚀 How to Use (Apify Console)
- Log in at console.apify.com → Actors.
- Open 🍴 Uber Eats Scraper [PPR].
- Either enter an address (and optional query + store type), or paste store URLs.
- Click Start.
- Watch stores stream into the Output tab in real time.
- Export to JSON / CSV / XLSX / Excel when the run completes.
🤖 Use via API
curl -X POST "https://api.apify.com/v2/acts/<ACTOR_ID>/run-sync-get-dataset-items?token=$APIFY_TOKEN" \-H "Content-Type: application/json" \-d '{"address":"1600 Pennsylvania Avenue, Washington DC","query":"Pizza","storeType":"RESTAURANTS","maxRows":10}'
🎯 Best Use Cases
- 📊 Competitor menu & price monitoring
- 🍽️ Restaurant & store discovery / market research
- 📈 Lead lists of local merchants by category and area
- 🗺️ Delivery coverage and ETA analysis across locations
💰 Pricing
Pay per result — you are billed a flat price for each store written to the dataset (the apify-default-dataset-item event). No charge for stores that fail to collect. Failed targets never cost you anything; partial runs still return everything collected so far.
❓ FAQ
Do I need a proxy? No. The scraper starts direct and only uses Apify Proxy if Uber Eats blocks it.
Search returns fewer than maxRows? Uber Eats only lists so many stores for a given area/query — that's the ceiling, not a bug.
Why are some menus empty? Some stores (e.g. certain alcohol/convenience listings) expose no public catalog; the store record is still returned.
Which countries are supported? Anywhere Uber Eats operates — pick the matching locale (55+ supported).
🛟 Support & Feedback
Open an issue on the Actor's Issues tab in Apify Console with your run ID and input, and we'll take a look.
Data is collected only from publicly available Uber Eats pages. You are responsible for compliance with applicable laws and Uber's Terms of Service.