We extract designer furniture collections, material configurations, technical specifications, and regional pricing from Cassina. 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 Master objects from cassina.com. All fields typed and schema-versioned.
"sku": "004-LC4", "title": "4 Chaise longue à reglage continu", "designer": "Le Corbusier, Pierre Jeanneret, Charlotte Perriand", "collection": "Cassina iMaestri Collection", "year_designed": 1928, "base_price": 5400.0, "currency": "EUR", "category": "Armchairs and Lounge Chairs"
| # | sku | title | designer | collection | year_designed | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Material & Finishes objects from cassina.com. All fields typed and schema-versioned.
"sku": "004-LC4", "variant_id": "LC4-PEL-NERO", "material_category": "Leather", "material_name": "Scozia", "colour_code": "13X201", "colour_name": "Nero", "finish_type": "Chrome-plated frame", "price_modifier": 0.0
| # | sku | variant_id | material_category | material_name | colour_code | colour_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Specs objects from cassina.com. All fields typed and schema-versioned.
"sku": "004-LC4", "width_cm": 160.0, "depth_cm": 56.4, "height_cm": 69.0, "seat_height_cm": 27.0, "weight_kg": 24.5, "indoor_outdoor": "Indoor", "assembly_required": false
| # | sku | width_cm | depth_cm | height_cm | seat_height_cm | weight_kg |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Designer Data objects from cassina.com. All fields typed and schema-versioned.
"designer_name": "Charlotte Perriand", "designer_slug": "charlotte-perriand", "active_years": "1927-1999", "products_count": 42, "portrait_url": "https://cassina.com/images/designers/perriand.jpg", "profile_url": "https://cassina.com/en/designers/charlotte-perriand"
| # | designer_name | designer_slug | biography_snippet | active_years | products_count | awards |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locator objects from cassina.com. All fields typed and schema-versioned.
"store_id": "CAS-MIL-01", "store_name": "Cassina Store Milano", "store_type": "Flagship Store", "address": "Via Durini, 16", "city": "Milano", "country": "Italy", "latitude": 45.4654, "longitude": 9.1966
| # | store_id | store_name | store_type | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Cassina's digital catalogue relies heavily on interactive 3D configurators, dynamic material selectors, and embedded technical PDFs. Our pipeline extracts structured data across all presentation layers.
Extract product hierarchy, linking individual SKUs to master collections (e.g., iMaestri) and specific designer profiles.
Parse JavaScript variables to extract all available upholstery, frame finishes, and marble top options for every configuration.
Capture width, depth, height, and seat height metrics directly from technical accordions and normalise them into numeric fields.
Simulate geographic locations to extract region-specific retail pricing in EUR, USD, GBP, and other supported currencies.
Identify and download technical specification PDFs attached to product pages for downstream CAD or architectural reference.
Extract URLs for uncompressed gallery images, lifestyle shots, and specific material swatches.
Generate a complete matrix of all possible product variations, mapping specific material combinations to their respective SKUs.
Extract the complete global directory of Cassina flagship stores, authorised dealers, and trade showrooms.
Run weekly pipelines to detect new product launches, discontinued items, or changes in material availability.
Brief in. Clean data out.
Specify the target collections, geographic regions for pricing, and required data fields. We map the extraction schema.
We configure Playwright to handle the dynamic configurators and Scrapy to traverse the catalogue hierarchy.
Schema validation ensures dimension fields are numeric and material combinations reflect actual stock availability.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
High-end furniture sites prioritise visual experience over simple DOM structures. Here is how we extract structured data from highly interactive interfaces.
Cassina product pages use client-side rendering to update images and prices when users select different fabrics or frame finishes. We intercept the underlying JSON payloads and API responses to extract the full matrix of variants without clicking every combination.
Pricing and availability on Cassina vary strictly by region, enforced by IP geolocation and cookies. We utilise region-specific residential proxies and strict session management to ensure we extract the correct catalogue for your target market.
Dimensions are often presented as raw text strings (e.g., 'W 160 x D 56.4 x H 69 cm'). Our parsing logic uses regular expressions to split these strings into strict numeric fields for width, depth, and height, ensuring database compatibility.
When extracting thousands of material variants, mapping the correct swatch image and product render to the specific SKU configuration is critical. We trace the image URL generation logic to ensure accurate asset mapping.
Luxury brands frequently overhaul their websites for new collections or design weeks. We use semantic targeting and JSON-LD extraction where possible to maintain pipeline stability during major frontend redesigns.
Platforms aggregate designer furniture specifications and dimensions to build comprehensive libraries for architectural planning.
High-end furniture manufacturers track pricing strategies across classic collections to position their own premium offerings.
Visualisation studios index available designer products, extracting technical dimensions to create accurate 3D models for rendering.
Industry analysts track the introduction of new fabrics, sustainable materials, and colour palettes across seasonal collections.
Real estate and retail analysts extract store locator data to map the global footprint of luxury furniture distribution.
Brand protection agencies use official specification data and pricing baselines to identify unauthorised replicas on third-party marketplaces.
"Cassina's catalogue represents the pinnacle of modern design history, but extracting structured material variants and technical dimensions from a highly visual front-end requires specialised infrastructure."
Most extraction tools fail on luxury furniture sites because the data is buried in WebGL configurators, dynamic material selectors, and unstructured PDF specification sheets. DataFlirt parses these complex front-ends and normalises the output into standard database schemas, so your engineering team can focus on ingestion rather than maintenance.
Everything supported by our cassina.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 execution, allowing us to interact with complex product configurators and extract dynamic state.
We utilise ISP-grade residential proxies to simulate traffic from specific European, North American, or Asian markets, ensuring accurate regional pricing extraction.
Pipelines run on AWS infrastructure managed by Kubernetes. Airflow schedules extraction runs, handles retries, and triggers downstream delivery to your data warehouse.
Data delivered to where your team already works — no new tooling required.
About cassina.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We parse the frontend configuration logic to extract the complete matrix of available fabrics, leathers, and finishes for a given SKU, including any specific price modifiers attached to premium materials.
Our parsing engine uses regular expressions to identify dimension strings. We normalise these into strict numeric fields (width_cm, depth_cm, height_cm) regardless of how they are formatted on the frontend.
Yes. By routing our extraction through region-specific residential proxies, we simulate traffic from your target market to capture the correct localised pricing and currency.
No. Cassina gates its CAD, 3D, and BIM files behind a professional registration wall. We extract the metadata indicating that these files exist, but we do not bypass authentication to download them.
For a catalogue of Cassina's size, we typically recommend weekly or monthly runs to capture new product launches and pricing updates. Daily runs are possible if required for specific monitoring use cases.
We deliver structured data in JSON, CSV, or Parquet formats. We can push this directly to your AWS S3 bucket, Google Cloud Storage, or ingest it into a relational database like PostgreSQL.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually copying dimensions from PDFs. We build and maintain the pipeline to deliver structured Cassina product data directly to your database.
