Just Eat Restaurant Scraper 🍽️

Just Eat Restaurant Scraper 🍽️

🍽️ Powerful Just Eat restaurant scraper that extracts comprehensive data including restaurant details, ratings, delivery info, and deals. Perfect for market research, food delivery analysis, and competitor monitoring. Supports custom search URLs and proxy configuration.

ECOMMERCEINTEGRATIONSLEAD_GENERATIONApify

Extract detailed restaurant information from Just Eat's platform with this powerful scraper. Get comprehensive data about restaurants, their ratings, delivery times, deals, and more - all in structured JSON format.

Features ✨

  • Extract restaurant names, addresses, and contact details
  • Get detailed rating information and review counts
  • Collect delivery fees, minimum order amounts, and ETA
  • Capture restaurant deals and promotional offers
  • Extract cuisine types and restaurant tags
  • Monitor restaurant availability and operating hours
  • Support for custom search URLs
  • Configurable maximum items limit
  • Optional proxy support for enhanced reliability

Output Data 📊

The actor provides rich restaurant data including:

  • Restaurant ID and unique identifiers
  • Complete address with geo-coordinates
  • Rating statistics and review counts
  • Delivery/collection availability status
  • Opening hours and delivery times
  • Current deals and promotions
  • Cuisine categories
  • Delivery fee structure
  • Logo URLs and branding assets

Use Cases 💡

  • Market research and competitor analysis
  • Food delivery platform comparison
  • Restaurant availability monitoring
  • Price and promotion tracking
  • Cuisine distribution analysis
  • Delivery coverage mapping
  • Customer sentiment analysis

Input Example

A full explanation of an input example in JSON.

1{
2    "searchUrl": "https://www.just-eat.co.uk/area/wc2-coventgarden",
3    "maxItems": 100
4}

Output sample

The results will be wrapped into a dataset which you can always find in the Storage tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

1[
2    {
3        "id": "215",
4        "name": "Pizza GoGo - Clapham",
5        "uniqueName": "pizzagogosw8",
6        "address": {
7            "city": "Wandsworth",
8            "firstLine": "703 Wandsworth Road",
9            "postalCode": "SW8 3JF",
10            "location": {
11                "type": "Point",
12                "coordinates": [
13                    -0.14528,
14                    51.46749
15                ]
16            }
17        },
18        "rating": {
19            "count": 1528,
20            "starRating": 4
21        },
22        "isNew": false,
23        "driveDistanceMeters": 5175,
24        "openingTimeLocal": "2025-03-30T11:35:00",
25        "deliveryOpeningTimeLocal": "2025-03-30T11:35:00",
26        "deliveryEtaMinutes": {
27            "rangeLower": 35,
28            "rangeUpper": 50
29        },
30        "isCollection": false,
31        "isDelivery": true,
32        "isOpenNowForCollection": false,
33        "isOpenNowForDelivery": false,
34        "isOpenNowForPreorder": true,
35        "isTemporarilyOffline": false,
36        "defaultDisplayRank": 1249,
37        "isTemporaryBoost": false,
38        "isPremier": false,
39        "logoUrl": "https://d30v2pzvrfyzpo.cloudfront.net/uk/images/restaurants/215.gif",
40        "isTestRestaurant": false,
41        "deals": [
42            {
43                "description": "50% off selected items",
44                "offerType": "ItemLevelDiscount"
45            }
46        ],
47        "tags": [],
48        "cuisines": [
49            {
50                "name": "Pizza",
51                "uniqueName": "pizza"
52            },
53            {
54                "name": "American",
55                "uniqueName": "american"
56            },
57            {
58                "name": "Deals",
59                "uniqueName": "deals"
60            }
61        ],
62        "availability": {
63            "delivery": {
64                "isOpen": false,
65                "canPreOrder": true,
66                "isTemporarilyOffline": false,
67                "nextAvailability": {
68                    "from": "2025-03-30T11:35:00"
69                },
70                "etaMinutes": {
71                    "rangeLower": 35,
72                    "rangeUpper": 50
73                }
74            }
75        },
76        "deliveryFees": {
77            "byMinFee": {
78                "minimumAmount": 1499,
79                "fee": 199
80            },
81            "byMaxFee": {
82                "minimumAmount": 1499,
83                "fee": 199
84            },
85            "byMinOrder": {
86                "minimumAmount": 1499,
87                "fee": 199
88            },
89            "byMaxOrder": {
90                "minimumAmount": 1499,
91                "fee": 199
92            },
93            "numBands": 1
94        }
95    },
96    ...
97]

Here are some other useful actors for e-commerce and business data extraction:

Frequently Asked Questions

Is it legal to scrape job listings or public data?

Yes, if you're scraping publicly available data for personal or internal use. Always review Websute's Terms of Service before large-scale use or redistribution.

Do I need to code to use this scraper?

No. This is a no-code tool — just enter a job title, location, and run the scraper directly from your dashboard or Apify actor page.

What data does it extract?

It extracts job titles, companies, salaries (if available), descriptions, locations, and post dates. You can export all of it to Excel or JSON.

Can I scrape multiple pages or filter by location?

Yes, you can scrape multiple pages and refine by job title, location, keyword, or more depending on the input settings you use.

How do I get started?

You can use the Try Now button on this page to go to the scraper. You’ll be guided to input a search term and get structured results. No setup needed!