We extract grocery listings, member pricing signals, dietary profiles, and stock availability from coop.co.uk. 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 coop.co.uk. All fields typed and schema-versioned.
"sku": "1002345", "title": "Co-op Irresistible Margherita Pizza", "brand": "Co-op Irresistible", "price": 5.5, "member_price": 4.5, "unit_price": "1.17 per 100g", "weight_volume": "470g", "dietary_flags": "['Vegetarian']"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promos objects from coop.co.uk. All fields typed and schema-versioned.
"sku": "1002345", "price": 5.5, "member_price": 4.5, "promo_type": "MEMBER_DISCOUNT", "meal_deal_eligible": true, "multi_buy_text": "2 for 8.00", "currency": "GBP", "price_timestamp": "2026-05-12T08:12:00Z"
| # | sku | price | member_price | promo_type | meal_deal_eligible | multi_buy_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Nutritional Info objects from coop.co.uk. All fields typed and schema-versioned.
"sku": "1002345", "energy_kcal": 254, "fat_g": 8.5, "saturates_g": 4.2, "sugars_g": 3.1, "salt_g": 1.1, "traffic_light_colours": "Amber"
| # | sku | energy_kcal | energy_kj | fat_g | saturates_g | sugars_g |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store Locator objects from coop.co.uk. All fields typed and schema-versioned.
"store_id": "4521", "name": "Co-op Food - Manchester - High Street", "postcode": "M4 1HQ", "latitude": 53.4831, "longitude": -2.2389, "facilities": "['Bakery', 'Paypoint', 'Amazon Lockers']", "phone_number": "0161 839 2145"
| # | store_id | name | address_line_1 | postcode | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Categories objects from coop.co.uk. All fields typed and schema-versioned.
"category_id": "cat_102", "name": "Fresh Meat & Poultry", "parent_category": "Fresh Food", "url_slug": "/category/fresh-food/meat-poultry", "product_count": 142, "active_status": true
| # | category_id | name | parent_category | url_slug | product_count | breadcrumb_path |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Coop scraper handles the entire grocery platform: product listings, Member Prices, nutritional tables, and store locators. Built with regional IP routing and session management.
Title, brand, weight, description, and images scraped at SKU level across all food and drink categories.
Capture standard retail price alongside exclusive Member Prices and unit price calculations.
Extract full macro-nutritional tables, dietary flags (Vegan, Gluten-Free), and allergen warnings.
Geospatial data for all Coop branches including opening hours, facilities, and contact details.
Track multi-buy offers, meal deal inclusions, and temporary promotional discounts.
Monitor stock status by postcode to map regional availability for specific product lines.
Map the full site hierarchy to understand how products are grouped and merchandised.
Identify Fairtrade certifications and origin country data for fresh produce.
Run daily or weekly pipelines to capture price changes and new product introductions.
Brief in. Clean data out.
Provide categories, postcodes, or specific SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for coop.co.uk.
Schema validation, null-rate checks, and price anomaly detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Grocery platforms use regional pricing and complex promotional structures. Here is how we maintain data integrity.
Grocery pricing and availability depend on the delivery postcode. We manage cookie sessions tied to specific UK postcodes to extract accurate local pricing and stock levels.
Coop relies on JavaScript for price updates and nutritional table hydration. We use full browser rendering to capture elements that static HTML parsers miss.
We route requests through UK-based residential IPs to prevent geo-blocking and rate-limiting, ensuring consistent extraction across the entire catalogue.
Supermarket site layouts change frequently. Our extraction logic uses multiple fallback selectors for prices and nutritional data to prevent pipeline failures.
Weight formats, unit prices, and promotional text are often inconsistent. We normalise these fields into strict numeric types and structured arrays before delivery.
Supermarkets and convenience chains track Coop Member Prices and standard rates to inform their own pricing strategies.
Food and beverage brands monitor their product placement, promotional frequency, and category share of shelf.
Health apps and dietary researchers extract macro-nutritional data and allergen flags to build consumer databases.
Property analysts use store locator data to map convenience retail density and identify expansion opportunities.
Economic researchers track basket prices over time to measure grocery inflation in the convenience sector.
Suppliers monitor out-of-stock indicators across regional postcodes to optimise distribution and forecasting.
"Coop UK holds critical pricing and nutritional data for the convenience grocery sector, but extracting it requires navigating dynamic regional pricing."
Grocery scraping requires handling localised pricing, complex promotional structures like meal deals, and deep nutritional tables. DataFlirt manages proxy rotation, session handling, and schema parsing so your data team receives clean, normalised tables ready for analysis.
Everything supported by our coop.co.uk 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 and postcode-specific cookie sessions.
We maintain pools of UK residential ISP proxies to ensure consistent access and prevent geo-blocking during large-scale extraction.
Pipelines run on AWS infrastructure with Airflow handling scheduling. All state and historical pricing stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About coop.co.uk scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline extracts both the standard retail price and the exclusive Member Price for every relevant SKU, along with any associated multi-buy or meal deal promotional logic.
We configure extraction runs based on target postcodes. The crawler injects the specified postcode into the session, ensuring the prices and availability reflect that specific geographic area.
Yes. We parse the nutritional tables to extract calories, fat, saturates, sugars, salt, fibre, and protein, alongside dietary flags like Vegan or Gluten-Free.
We support daily, weekly, or custom schedules. For full catalogue sweeps, daily extraction is standard practice to capture overnight price adjustments.
We maintain a time-series record from the moment your pipeline is commissioned, allowing you to track price inflation and promotional cycles over time.
Yes. We can extract the complete list of Coop branches, including coordinates, opening hours, and available facilities like bakeries or parcel lockers.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily catalogue dump or continuous price monitoring across all postcodes, we scope, build, and operate the pipeline. Tell us what you need.
