We extract restaurant listings, menu items, delivery fees, customer reviews, and hygiene ratings from Just Eat. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Restaurant Listings objects from justeat.com. All fields typed and schema-versioned.
"restaurant_id": "194827", "name": "Pizza Express", "cuisine_types": "['Italian', 'Pizza']", "rating": 4.6, "review_count": 1204, "postcode": "E1 6AN", "hygiene_rating": 5, "is_open": true
| # | restaurant_id | name | url | cuisine_types | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Menu Items objects from justeat.com. All fields typed and schema-versioned.
"item_id": "M-849302", "restaurant_id": "194827", "category": "Mains", "name": "Margherita Pizza", "price": 12.95, "popular_flag": true, "calories": 850, "dietary_labels": "['Vegetarian']"
| # | item_id | restaurant_id | category | name | description | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews objects from justeat.com. All fields typed and schema-versioned.
"review_id": "REV-99201", "restaurant_id": "194827", "rating": 5, "text": "Food arrived hot and on time.", "date": "2026-05-10T19:30:00Z", "author": "James T.", "reply_text": "Thanks for the great feedback!", "reply_date": "2026-05-11T09:15:00Z"
| # | review_id | restaurant_id | author | rating | text | date |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Delivery & Fees objects from justeat.com. All fields typed and schema-versioned.
"restaurant_id": "194827", "postcode": "E1 6AN", "delivery_fee": 2.5, "service_fee": 0.5, "min_order": 15.0, "estimated_time_min": 30, "estimated_time_max": 45, "free_delivery_threshold": 30.0
| # | restaurant_id | postcode | delivery_fee | service_fee | min_order | estimated_time_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Promotions & Offers objects from justeat.com. All fields typed and schema-versioned.
"promo_id": "PRM-102", "restaurant_id": "194827", "title": "20% off over £20", "discount_pct": 20, "min_spend": 20.0, "valid_until": "2026-12-31T23:59:59Z", "description": "Get 20% off when you spend £20 or more on selected items."
| # | promo_id | restaurant_id | title | description | discount_pct | discount_abs |
|---|---|---|---|---|---|---|
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Our Just Eat scraper handles every layer of the platform: restaurant listings, dynamic pricing, delivery fees, and the review corpus, with session management and anti-bot circumvention built in.
Name, address, cuisines, ratings, and hygiene scores across all UK and European postcodes.
Item names, descriptions, prices, modifier groups, and dietary labels mapped to parent restaurants.
Capture variable delivery fees, service charges, and minimum order values based on target postcodes.
Extract customer text reviews, star ratings, and restaurant replies for sentiment analysis.
Monitor active discounts, free item offers, and percentage drops across competitive zones.
Capture FSA hygiene ratings and inspection dates displayed on restaurant profiles.
Extract daily opening and closing schedules, including holiday exceptions and split shifts.
Capture exact latitude and longitude coordinates for spatial analysis and density mapping.
Run daily postcode sweeps or continuous pipelines with change-detection diffing.
Brief in. Clean data out.
Provide postcode lists, city names, or specific restaurant URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for justeat.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Food delivery platforms invest heavily in scraping detection and dynamic content. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
Just Eat uses rate limiting and TLS fingerprinting. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing, trained on real user behaviour.
Extracting accurate delivery fees requires simulating user sessions with specific postcodes. We maintain isolated cookie jars per postcode to capture hyper-local pricing.
Just Eat relies heavily on React. We run full Playwright browser sessions to hydrate menu modifiers and dynamic pricing widgets that headless HTTP clients miss entirely.
Food delivery platforms iterate their frontend frequently. Our selector strategy uses multiple fallback chains so layout changes do not break the pipeline.
For large menu catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs, reducing downstream processing load.
Dark kitchens and restaurant chains track local pricing and delivery fees to optimise their own menus.
Ghost kitchen operators map restaurant density and cuisine gaps by postcode to identify lucrative new zones.
Delivery platforms benchmark their own restaurant coverage and fee structures against Just Eat.
Beverage and wholesale food brands identify high-volume independent restaurants for direct B2B sales.
Operators aggregate multi-location reviews to track brand health and franchise performance.
Analysts use restaurant density and delivery radius data to model commercial property values.
"Just Eat holds the ground truth for local restaurant density and delivery economics, but extracting it requires simulating thousands of hyper-local user sessions."
Most teams underestimate the investment required: reliable Just Eat scraping requires residential proxies, postcode session simulation, full JavaScript rendering, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our justeat.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering and session flows.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions for postcode mapping.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About justeat.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Just Eat is generally permissible under applicable law. DataFlirt targets only public, non-authenticated restaurant, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We simulate user sessions with specific postcodes to capture hyper-local delivery fees and menu variations.
We support justeat.co.uk, justeat.ie, justeat.it, justeat.es, and other Takeaway.com subsidiary domains.
Daily postcode sweeps complete within a 6-12 hour window. High-priority zones can be tracked hourly.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per restaurant.
Our smallest packages start at a defined postcode list with weekly delivery. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off restaurant catalogue dump or a continuous price-monitoring feed across 10,000 postcodes, we scope, build, and operate the pipeline. Tell us what you need.
