We extract product listings, regional pricing, size-level inventory, and lookbook styling from Stradivarius. 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 stradivarius.com. All fields typed and schema-versioned.
"product_id": "04561234", "reference_number": "4561/234", "name": "Faux leather biker jacket", "category_path": "Clothing > Jackets > Biker", "description": "Long sleeve faux leather jacket with lapel collar. Front zip pockets.", "model_height": "177 cm", "image_urls": "['https://static.stradivarius.net/5/photos3/2026/I/0/1/p/4561/234/001/4561234001_1_1_1.jpg']"
| # | product_id | reference_number | name | category_path | description | composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Variants objects from stradivarius.com. All fields typed and schema-versioned.
"product_id": "04561234", "reference_number": "4561/234", "colour_name": "Black", "colour_code": "001", "price": 39.99, "original_price": 49.99, "currency": "EUR", "discount_pct": 20, "is_new_collection": false, "region": "ES"
| # | product_id | reference_number | colour_name | colour_code | price | original_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Sizing objects from stradivarius.com. All fields typed and schema-versioned.
"product_id": "04561234", "sku": "0456123400102", "size_label": "M", "in_stock": true, "low_stock_warning": true, "coming_soon": false, "store_availability_flag": true
| # | product_id | sku | size_label | in_stock | low_stock_warning | coming_soon |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Lookbook & Styling objects from stradivarius.com. All fields typed and schema-versioned.
"look_id": "L-2026-AW-045", "title": "Urban Grunge Autumn", "season": "AW26", "gender": "Women", "primary_image_url": "https://static.stradivarius.net/lookbooks/aw26/urban_045.jpg", "associated_product_ids": "['04561234', '07894561']", "collection_name": "Trafaluc Core", "style_tags": "['grunge', 'biker', 'autumn']"
| # | look_id | title | season | gender | primary_image_url | associated_product_ids |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locations objects from stradivarius.com. All fields typed and schema-versioned.
"store_id": "S-1045", "name": "Stradivarius Oxford Street", "address": "309 Oxford St", "city": "London", "postal_code": "W1C 2HW", "country": "UK", "latitude": 51.5144, "longitude": -0.1444, "click_and_collect": true
| # | store_id | name | address | city | postal_code | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Stradivarius scraper navigates the SPA architecture, extracting deeply nested variant data, regional pricing, and high-resolution lookbook assets with full JavaScript execution.
Extract reference numbers, composition, care instructions, model dimensions, and detailed descriptions directly from the frontend state.
Capture pricing across different European, Asian, and American storefronts. Track currency variations and regional markdowns.
Monitor stock status per size (XS to XL), capturing low-stock warnings and 'coming soon' flags to gauge demand velocity.
Map parent products to all available colour codes, extracting specific hex values and individual variant pricing.
Scrape primary product shots, detail angles, and model photography at maximum available resolution.
Extract editorial lookbooks and map them back to individual purchasable SKUs for styling and collection analysis.
Extract global store directories, opening hours, and click-and-collect availability data.
Identify markdown events, calculate discount percentages, and track 'Special Price' category additions in real time.
Run daily or hourly inventory checks. We maintain a hash state and only deliver records where stock or price has changed.
Brief in. Clean data out.
Specify target regions, categories, or specific reference numbers. We configure the extraction schema to match your requirements.
We deploy Playwright crawlers with residential proxies to bypass edge protection and render Stradivarius's SPA content.
We test for null-rates on critical fields like price and stock, ensuring all colour and size variants are mapped correctly.
Clean, normalised data is pushed to your S3 bucket, Snowflake stage, or via Webhook on your defined schedule.
Fast-fashion sites use aggressive caching and edge protection. Here is how we maintain steady extraction rates.
Inditex brands employ strict bot mitigation at the edge. We use residential ISP proxies combined with TLS fingerprint spoofing to ensure requests appear as legitimate consumer traffic.
Stradivarius relies heavily on client-side rendering. We intercept the raw JSON state hydrating the React frontend, extracting product matrices without parsing complex DOM structures.
Pricing and stock vary drastically by country. We route requests through region-specific proxy pools and manage locale cookies to ensure you get accurate local data, not default fallback pricing.
A single jacket might have 5 colours and 6 sizes. Our pipeline normalises this 30-SKU matrix into flat, queryable records, ensuring no variant is missed during extraction.
Stock levels change hourly. We run high-frequency checks against specific reference numbers, delivering only state changes to minimise your processing overhead.
Fashion retailers track Stradivarius pricing across regions to optimise their own markdown strategies and entry-level price points.
Merchandising teams analyse category depth, colour prevalence, and material composition to inform their own seasonal buying decisions.
Agencies monitor new arrivals and 'Special Price' velocity to identify which micro-trends are gaining traction or being liquidated.
Analysts track out-of-stock rates across sizes to estimate sales velocity and production run sizes for specific categories.
Computer vision teams use the extensive, high-quality lookbook and product imagery to train garment recognition and styling models.
Consultancies aggregate data across Inditex brands to map global supply chain shifts and regional market penetration.
"Fast fashion moves on daily cycles. If your competitor intelligence is weekly, you are already trading on expired signals."
Extracting data from Inditex brands requires handling aggressive edge protection, complex JavaScript hydration, and massive variant matrices. DataFlirt manages the residential proxy rotation and session states so your analysts get clean, normalised inventory data every morning. No maintenance required.
Everything supported by our stradivarius.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 executes JavaScript to extract deeply nested React state objects containing variant data.
We route requests through ISP-grade residential proxies in the target country, ensuring accurate regional pricing and avoiding datacentre IP bans.
Airflow manages scheduling and dependency chains. Pipelines execute on AWS ECS, with state stored in PostgreSQL for accurate change detection.
Data delivered to where your team already works — no new tooling required.
About stradivarius.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure pipelines to target specific regional subdirectories (e.g., /es/en/ or /gb/en/) and route traffic through corresponding local proxy pools to ensure accurate pricing and stock data.
Stradivarius products often feature extensive variant matrices. We extract the raw JSON state from the frontend and normalise it into flat records, ensuring every size/colour combination is captured with its specific SKU, price, and stock status.
We intercept the public, undocumented JSON endpoints used by the Stradivarius frontend. This provides cleaner, more structured data than parsing HTML, while remaining resilient to minor layout changes.
For targeted SKU lists, we can run hourly pipelines. Full catalogue sweeps are typically scheduled daily. We recommend using our change-detection feature to only receive diffs, reducing your ingestion overhead.
Yes. We capture the highest resolution assets available on the CDN and map them back to the reference numbers of the garments featured in the look.
Scraping publicly available product and pricing data is generally permissible. We do not bypass authentication walls, extract personal user data, or interact with checkout systems. Clients should consult their legal counsel regarding specific commercial use cases.
20-minute scoping call. Pilot dataset within the week. Production within two. From single-region pricing audits to daily global inventory tracking across the entire catalogue. Tell us your requirements, and we will scope the pipeline.
