We extract supermarket listings, Rollback pricing, nutritional data, stock availability, and George at Asda catalogues. 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 Grocery Listings objects from asda.com. All fields typed and schema-versioned.
"sku": "100028374", "title": "Asda Extra Special British Beef Mince", "brand": "Asda", "price": 4.5, "unit_price": "9.00/kg", "in_stock": true, "category": "Meat & Poultry", "weight_volume": "500g"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Promotions & Rollbacks objects from asda.com. All fields typed and schema-versioned.
"sku": "100028374", "current_price": 4.5, "previous_price": 5.25, "rollback_badge": true, "promotion_text": "Rollback", "multi_buy_deal": "None", "asda_rewards_price": "None", "scraped_at": "2026-08-14T10:12:00Z"
| # | sku | current_price | previous_price | rollback_badge | promotion_text | multi_buy_deal |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Nutritional Data objects from asda.com. All fields typed and schema-versioned.
"sku": "100028374", "energy_kcal": 124, "fat_g": 4.5, "saturates_g": 2.1, "sugars_g": 0.0, "salt_g": 0.15, "traffic_light_colours": "Green, Amber, Green, Green"
| # | sku | serving_size | energy_kcal | energy_kj | fat_g | saturates_g |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for George Apparel objects from asda.com. All fields typed and schema-versioned.
"product_id": "GEM837291", "title": "Navy Blue Check Pattern Shirt", "department": "Men", "colour": "Navy Blue", "size_options": "['S', 'M', 'L', 'XL']", "price": 14.0, "rating": 4.6, "review_count": 82
| # | product_id | title | department | colour | size_options | material_composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store & Availability objects from asda.com. All fields typed and schema-versioned.
"store_id": "4192", "store_name": "Asda Clapham Junction", "postcode": "SW11 1JG", "click_and_collect": true, "pharmacy_available": true, "stock_status": "In Stock", "latitude": 51.4632
| # | store_id | store_name | postcode | latitude | longitude | opening_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Asda scraper navigates the grocery ecosystem: complex promotional pricing, precise nutritional profiles, store-specific stock levels, and the George apparel catalogue, handling dynamic frontend rendering and postal code session states.
Title, weight, brand, ingredients, allergens, and dietary flags extracted at the SKU level across all supermarket aisles.
Capture base price, unit price, Rollback badges, multi-buy offers (e.g., 3 for 2), and Asda Rewards member pricing.
Extract full macro-nutrient tables per 100g and per serving, including traffic light colour coding for HFSS analysis.
Prices and availability vary by location. We set specific delivery postcodes or store IDs to capture localised data.
Extract the complete clothing and home catalogue, mapping size variants, colour options, and material compositions.
Monitor shelf gaps and out-of-stock rates for specific products at designated local superstores.
Reconstruct Asda's exact category tree to understand product placement and digital shelf hierarchy.
Capture vegan, vegetarian, gluten-free, and halal certifications directly from product metadata.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, search terms, or specific store postcodes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and postcode session management for asda.com.
Schema validation, null-rate checks, price-outlier detection, and promotional logic testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Supermarket sites rely on complex session states for store selection and heavily dynamic frontends for pricing. Here is how we maintain data integrity.
Asda requires a delivery postcode or store selection to display accurate pricing and stock. We manage persistent browser sessions and cookie states to ensure the crawler extracts data for your specific target locations.
Supermarket promotions are rarely simple numbers. We parse complex text strings like '2 for £4' or 'Save 50p' into structured, queryable numeric fields so your analysts do not have to write regex.
High-frequency scraping triggers rate limits and WAF blocks. We route requests through UK-based residential ISP proxies with realistic request timing to maintain uninterrupted extraction.
Asda's frontend relies on React and lazy-loading for product grids and pricing widgets. We run full Playwright browser sessions to trigger network requests and capture data that headless HTTP clients miss entirely.
For large grocery catalogues, we maintain a hash index of last-seen values per field. Subsequent daily runs only push price or stock diffs, reducing downstream processing load.
Brands and competitor supermarkets monitor pricing, unit costs, and Rollback frequency to optimise their own pricing strategies.
Supply chain teams monitor shelf gaps and out-of-stock rates to understand distribution issues at the local store level.
Health researchers and compliance teams aggregate macro-nutrient and HFSS data to track public health initiatives.
FMCG brands audit the digital shelf to ensure their negotiated multi-buy deals and Asda Rewards promotions run on schedule.
Economists and analysts track basket costs over time to build proprietary grocery price indices and measure consumer inflation.
Agencies correlate organic search placement with sponsored slots to optimise retail media spend on the Asda platform.
"Supermarket pricing is fiercely competitive. You cannot optimise FMCG strategy without structured visibility into Asda's digital shelves."
Extracting grocery data requires precise handling of local store sessions, complex promotional mathematics, and deep nutritional taxonomies. DataFlirt manages the underlying infrastructure, proxy rotation, and schema mapping so your team can focus on market analysis.
Everything supported by our asda.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 and deduplication. Playwright handles JavaScript rendering, store location cookies, and interaction flows.
We maintain pools of UK residential ISP proxies. Rotation happens per-request with sticky sessions required for location-based pricing.
Pipelines run on AWS Lambda and ECS. 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 asda.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, nutritional, and stock data from Asda is generally permissible under UK law. DataFlirt targets only public, non-authenticated grocery data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for their specific use cases.
Yes. We configure the crawler to inject specific postcodes or select specific store IDs, ensuring the extracted prices and stock levels reflect local availability.
Yes. We extract the standard price, Rollback price, multi-buy offers, and exclusive Asda Rewards member pricing as distinct structured fields.
We extract the exact promotional text and map it to a structured promotion schema, allowing your analysts to calculate the true unit cost without writing complex regex.
Yes. We support the entire George at Asda catalogue, including complex variant mapping for sizes, colours, and material compositions.
We typically run full catalogue refreshes on a daily cadence, completing within a 4-8 hour window. High-priority categories can be tracked at a higher frequency.
Yes. We capture the complete macro-nutrient table, ingredients list, dietary flags, and allergen warnings directly from the product detail page.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily FMCG price index or a complete catalogue extraction for nutritional analysis, we scope, build, and operate the pipeline. Tell us what you need.
