We extract restaurant listings, menu items, delivery fees, preparation times, and customer ratings from Talabat. 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 talabat.com. All fields typed and schema-versioned.
"restaurant_id": "94812", "name": "KFC", "cuisine_tags": "['Fast Food', 'American']", "rating": 4.2, "delivery_time_mins": 35, "delivery_fee": 5.0, "status": "open"
| # | restaurant_id | name | chain_name | cuisine_tags | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Menu Items objects from talabat.com. All fields typed and schema-versioned.
"item_id": "491023", "category_name": "Signature Burgers", "item_name": "Spicy Zinger", "price": 24.5, "discount_pct": 0, "popular_flag": true, "available": true
| # | item_id | restaurant_id | category_name | item_name | description | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Delivery & Fees objects from talabat.com. All fields typed and schema-versioned.
"restaurant_id": "94812", "zone_id": "DXB_04", "base_delivery_fee": 7.0, "service_fee": 2.5, "estimated_time": "30-45", "distance_km": 3.2, "surge_fee": 0.0
| # | restaurant_id | zone_id | user_location | base_delivery_fee | surge_fee | service_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Promotions & Offers objects from talabat.com. All fields typed and schema-versioned.
"offer_id": "PROMO_881", "restaurant_id": "94812", "offer_type": "percentage", "title": "20% Off Entire Menu", "discount_amount": 20, "min_basket_value": 50.0, "talabat_pro_eligible": true
| # | offer_id | restaurant_id | offer_type | title | description | discount_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Talabat Mart objects from talabat.com. All fields typed and schema-versioned.
"store_id": "TMART_DXB_1", "product_id": "GROC_992", "product_name": "Al Ain Bottled Water", "price": 1.5, "stock_status": "in_stock", "weight_volume": "1.5L", "category": "Beverages"
| # | store_id | product_id | brand | product_name | category | weight_volume |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Talabat scraper handles every layer of the platform: restaurant discovery, dynamic delivery fees, complex menu modifiers, and Talabat Mart inventory — with precise coordinate spoofing built in.
Item names, descriptions, prices, categories, and nutritional information scraped per restaurant branch.
Capture base fees, service charges, and surge pricing based on specific geocoordinates.
Identify restaurants and items eligible for Talabat Pro free delivery and exclusive discounts.
Track real-time store status (open, busy, closed) and exact operational schedules.
Extract grocery SKUs, pricing, and stock availability across dark stores in the region.
Monitor discount campaigns, percentage drops, and minimum order requirements per vendor.
Extract latitude and longitude coordinates for branches to map coverage density.
Capture aggregate star ratings and review counts to track vendor performance over time.
Extract data across UAE, Saudi Arabia, Kuwait, Egypt, Qatar, Bahrain, Oman, and Jordan.
Brief in. Clean data out.
Provide coordinates, city names, or restaurant chains. We design the extraction schema together.
We configure Scrapy crawlers, MENA proxy rotation, session management, and coordinate spoofing.
Schema validation, null-rate checks, and location-accuracy verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Food delivery platforms rely on strict geolocation controls and dynamic APIs. Here is how we maintain reliable extraction.
Talabat restricts visibility based on user location. We inject precise latitude and longitude headers into API requests to map exact delivery radiuses and zone-specific pricing.
Datacenter IPs are quickly blocked. We route requests through residential proxy pools specific to UAE, KSA, Egypt, and Kuwait to maintain high success rates and avoid rate limits.
Delivery fees and item prices fluctuate based on demand and time. Our schedulers run high-frequency polling during peak lunch and dinner hours to capture surge pricing models.
Web scraping is slow. We target Talabat mobile API endpoints directly, handling token generation and payload signing to extract structured JSON faster and more reliably.
Restaurant items have complex modifiers (size, add-ons, crust type). Our schema flattens these nested arrays into queryable relational structures for easy downstream analysis.
Cloud kitchens and restaurant chains monitor competitor menu pricing and promotional strategies across specific delivery zones.
Aggregators analyse Talabat delivery fee structures, service charges, and surge thresholds to optimise their own pricing models.
F&B brands map restaurant density and cuisine gaps in specific neighbourhoods to decide where to open new physical or dark kitchens.
Brands monitor their product availability, pricing, and category placement within Talabat Mart dark stores.
Investors and analysts track review velocity and rating trends to evaluate the performance of major franchise operators.
Marketing teams track the frequency and depth of discounts offered by competitors during major sporting events or holidays.
"Food delivery economics are hyper-local. A menu price in Downtown Dubai differs from Marina, and you cannot analyse the market without coordinate-level precision."
Extracting data from Talabat requires more than basic HTTP requests. It demands precise coordinate spoofing, regional proxy routing, and handling complex nested modifier arrays for every menu item. DataFlirt manages this infrastructure so your analysts can focus on pricing strategy.
Everything supported by our talabat.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.
We intercept and replicate Talabat mobile app traffic, bypassing web-layer captchas and extracting clean JSON payloads directly from backend endpoints.
We maintain dedicated pools of residential ISP proxies across the MENA region. Requests are routed locally to ensure accurate pricing and avoid geo-blocking.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About talabat.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available restaurant and pricing information is generally permissible under applicable laws. DataFlirt extracts only public, non-authenticated data such as menus and delivery fees. We do not extract personal user data or bypass authentication walls.
Talabat alters delivery fees and restaurant availability based on the user location. We inject specific latitude and longitude coordinates into the request headers to simulate users in exact delivery zones.
We support all regions where Talabat operates, including UAE, Saudi Arabia, Kuwait, Egypt, Qatar, Bahrain, Oman, Iraq, and Jordan. Our schema normalizes currencies and local data structures.
Yes. We track grocery inventory, SKU-level pricing, promotional discounts, and stock availability across Talabat Mart dark stores.
Restaurant menus often have nested options (e.g., crust type, extra toppings, size). Our parsers flatten these nested JSON structures into relational tables or structured arrays, ensuring every price variation is captured.
For delivery fee monitoring, we can configure high-frequency polling every 15 minutes during peak hours. Full menu refreshes across a city typically run on a daily or weekly cadence.
We maintain time-series records from the moment your pipeline is commissioned. You can track menu price inflation and delivery fee changes over time.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a city-wide restaurant census or high-frequency delivery fee tracking — we scope, build, and operate the pipeline. Tell us what you need.
