We extract product listings, pricing signals, fabric compositions, and inventory matrices from cos.com. 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 Product Listings objects from cos.com. All fields typed and schema-versioned.
"product_id": "1182374001", "name": "Oversized Tailored Wool Coat", "category": "Women > Coats & Jackets", "colour": "Black", "fit_type": "Oversized", "fabric_composition": "100% RWS Wool", "sustainability_label": "Responsible Wool Standard", "care_instructions": "Dry clean only"
| # | product_id | style_code | name | category | sub_category | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Markdowns objects from cos.com. All fields typed and schema-versioned.
"product_id": "1182374001", "sku": "1182374001-001", "region": "UK", "currency": "GBP", "current_price": 250.0, "original_price": 250.0, "discount_pct": 0, "sale_badge": false, "price_timestamp": "2026-05-12T10:15:00Z"
| # | product_id | sku | region | currency | current_price | original_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Sizing objects from cos.com. All fields typed and schema-versioned.
"product_id": "1182374001", "sku": "1182374001-001-M", "colour": "Black", "size": "M", "in_stock": true, "low_stock_warning": true, "stock_quantity": 3, "region": "UK", "scraped_at": "2026-05-12T10:15:22Z"
| # | product_id | sku | colour | size | in_stock | low_stock_warning |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our COS scraper handles dynamic inventory matrices, localized pricing, and complex variant structures — parsing fabric composition and care data directly into queryable fields.
Title, description, style codes, categories, and fit details — scraped across all departments and collections.
Parent-child relationships resolved across all size and colour combinations. We map the SKU grid precisely as it exists in the backend.
Extract material breakdowns, sustainability certifications (e.g., RWS Wool, Organic Cotton), and precise care instructions.
Capture region-specific pricing, original price, markdown percentages, and promotional flags — timestamped per crawl.
Monitor stock availability, low-stock warnings, and exact quantity indicators for every size variant.
Capture clean URLs for all product gallery images, model shots, and detail crops.
Target cos.com/en_gb, en_us, en_eu, and other regional subdirectories to compare global assortment and pricing.
Brief in. Clean data out.
Provide target regions, categories, or specific style codes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and variant resolution logic for cos.com.
Schema validation, null-rate checks, price-outlier detection, and variant completeness before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern apparel sites rely heavily on dynamic loading and regional routing. Here's how we stay resilient.
Retail sites block datacentre IPs aggressively. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management — preventing IP bans and regional redirects.
COS heavily utilises JavaScript for inventory loading and variant switching. We run full Playwright browser sessions to trigger dynamic hydration, capturing stock availability that headless HTTP clients miss entirely.
Apparel SKUs are multidimensional. We map the parent style code to every child variant, ensuring size-level inventory and colour-specific pricing are accurately linked and normalised.
For large catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice. SLA uptime is contractual, not aspirational.
Fashion brands monitor COS's pricing architecture and promotional cadence to optimise their own markdown strategies.
Merchandising teams analyse category depth, colour prevalence, and fit trends across new arrivals.
Supply chain analysts track material composition shifts and sustainability certification adoption across the catalogue.
ML teams ingest high-res images, descriptions, and fabric data to train visual recommendation engines and auto-tagging models.
Analysts track size-level stockout rates and restock velocity to estimate demand and production volumes.
Researchers aggregate sustainability labels and material percentages to audit brand claims against ESG targets.
"COS offers a masterclass in minimalist design and premium materials — but tracking their pricing, fabric composition, and stock depth across regions requires dedicated scraping infrastructure."
Most teams underestimate the investment required: reliable COS scraping requires residential proxies, full JavaScript rendering for dynamic inventory, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our cos.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, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 cos.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from cos.com is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and inventory data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes don't break the pipeline.
We support all regional subdirectories of cos.com, including UK, US, EU, and Asia-Pacific markets. We handle the necessary geolocated proxies to prevent unwanted regional redirects.
Yes. We map the parent product to every child size/colour variant, capturing specific in-stock status and low-stock warnings for each combination.
Full catalogue refreshes typically run at a daily cadence. For specific high-priority categories or styles, we can configure hourly pipelines to track rapid inventory depletion or flash sales.
Our smallest packages start at defined category tracking with weekly delivery. For full global catalogue monitoring, we price based on volume, region count, and delivery frequency.
Yes. We parse the material breakdown into structured percentages and capture distinct sustainability certifications associated with the garment.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous inventory monitoring across regions — we scope, build, and operate the pipeline. Tell us what you need.
