We extract complex furniture configurations, designer metadata, material specifications, and global pricing from Fritz Hansen. Delivered as clean JSON, CSV, or Parquet.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Specifications objects from fritzhansen.com. All fields typed and schema-versioned.
"name": "Egg Chair", "designer": "Arne Jacobsen", "category": "Lounge Chairs", "materials": "Leather, Aluminum", "height_cm": 107.0, "width_cm": 86.0, "depth_cm": 79.0
| # | product_id | name | designer | category | collection | materials |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants & Pricing objects from fritzhansen.com. All fields typed and schema-versioned.
"sku": "3316-WALNUT-ESSENTIAL", "upholstery_type": "Essential Leather", "base_finish": "Polished Aluminum", "colour_name": "Walnut", "price": 12450.0, "currency": "EUR", "lead_time_weeks": 6
| # | sku | parent_id | upholstery_type | colour_code | colour_name | base_finish |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Media & Assets objects from fritzhansen.com. All fields typed and schema-versioned.
"sku": "3316-WALNUT-ESSENTIAL", "image_urls": "['img1.jpg', 'img2.jpg']", "cad_3d_url": "egg_chair.dwg", "assembly_manual_url": "manual.pdf", "care_guide_url": "leather_care.pdf", "bim_object_url": "egg.rfa"
| # | sku | image_urls | lifestyle_images | cad_2d_url | cad_3d_url | bim_object_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Dealer Network objects from fritzhansen.com. All fields typed and schema-versioned.
"name": "Republic of Fritz Hansen Store", "store_type": "Flagship", "city": "Copenhagen", "country": "Denmark", "latitude": 55.6761, "longitude": 12.5683, "phone": "+45 33 14 43 46"
| # | dealer_id | name | store_type | address_line1 | city | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sustainability Data objects from fritzhansen.com. All fields typed and schema-versioned.
"fsc_certified": true, "eu_ecolabel": false, "carbon_footprint_kg": 45.2, "warranty_years": 10, "material_composition": "Shell: Polyurethane, Base: Steel", "designer_bio": "Arne Jacobsen (1902-1971) was a Danish architect..."
| # | sku | fsc_certified | eu_ecolabel | carbon_footprint_kg | recycled_content_pct | material_composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scrapers handle complex product configurators, dynamic material loading, and nested designer metadata to deliver highly structured furniture datasets.
Extract all possible upholstery, base, and colour combinations for complex pieces like the Series 7 or Egg chair.
Capture biographical data, collection associations, and historical context for pieces by Arne Jacobsen, Poul Kjærholm, and Cecilie Manz.
Extract detailed material compositions, leather grades (Essential, Aura, Grace), and wood veneer types.
Map the entire physical retail network, including flagship stores, authorised dealers, and contract partners.
Collect direct links to 2D/3D CAD files, BIM objects, high-resolution lifestyle imagery, and product tear sheets.
Standardise height, width, depth, and seat height measurements across metric and imperial systems.
Extract FSC certification status, carbon footprint data, and material recycling percentages where listed.
Capture localised pricing and currency data across European, North American, and Asian storefronts.
Execute complex frontend logic to reveal dynamic pricing and lead times based on user-selected configurations.
Brief in. Clean data out.
Specify target collections, designers, or regional pricing requirements. We design the extraction schema.
We configure Playwright spiders to navigate Fritz Hansen's product configurators and handle region selectors.
Schema validation, unit normalisation, and variant completeness checks before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on your defined cadence.
Extracting data from luxury design brands requires navigating highly dynamic frontends and complex variant matrices.
Fritz Hansen uses complex JavaScript configurators for upholstery and finishes. We programmatically iterate through all valid combinations to extract accurate pricing and SKUs.
Pricing changes significantly by region. We route requests through geographically specific residential proxies to capture accurate local MSRPs.
Architects and designers need 3D files. We parse the underlying API responses to extract direct download URLs for DWG, 3DS, and Revit files.
Measurements are often embedded in text or images. Our pipeline parses and normalises dimensions into structured height, width, and depth fields.
We use fallback chains combining CSS selectors and JSON-LD extraction to ensure pipeline stability when the site layout changes.
Aggregators and design software providers ingest 3D models, dimensions, and materials for space planning tools.
Premium furniture brands monitor pricing strategies across different upholstery grades and regional markets.
B2B procurement teams track lead times, dealer locations, and sustainability certifications for large-scale projects.
Brand protection agencies monitor unauthorised dealers and cross-reference official pricing to identify potential fakes.
Analysts track the introduction of new materials, designer collaborations, and category expansion in the luxury furniture sector.
Real estate and retail strategists analyse the geographic distribution of authorised Fritz Hansen dealers.
"Fritz Hansen's catalogue represents a masterclass in Danish design, but extracting the underlying configuration matrix requires deep frontend execution."
Luxury furniture sites are built for visual impact, not data extraction. Capturing the full matrix of upholstery grades, base finishes, and regional pricing requires full JavaScript rendering and programmatic interaction with complex product configurators. We handle this infrastructure so you can focus on market analysis.
Everything supported by our fritzhansen.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.
We use headless browsers to interact with complex Vue/React configurators, ensuring every variant is loaded and captured.
Residential IPs allow us to view the catalogue exactly as a local customer would, capturing accurate regional pricing.
Pipelines run on Kubernetes, managed by Apache Airflow, ensuring reliable scheduling and delivery of catalogue updates.
Data delivered to where your team already works — no new tooling required.
About fritzhansen.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and dealer information is generally permissible under applicable law. We do not bypass authentication walls or extract proprietary B2B portal data.
We use Playwright to fully render the page and programmatically select every valid combination of upholstery, finish, and base to extract the corresponding SKU and price.
Yes. We extract the direct download URLs for DWG, 3DS, Revit, and other architectural files provided on the product pages.
We can only extract data currently visible on the live site. However, once a pipeline is running, we maintain a historical record of products even if they are later removed.
We route requests through geographically specific residential proxies (e.g., Denmark, US, Japan) to capture the correct local currency and pricing.
Yes. We can scrape the store locator to provide a complete dataset of flagship stores, authorised dealers, and contract partners, including geospatial coordinates.
For a catalogue of this size, weekly or monthly cadences are most common, though daily runs can be configured for strict price monitoring.
20-minute scoping call. Pilot dataset within the week. Production within two. From complete catalogue extraction to continuous price monitoring across regions. Tell us your data requirements and we will design the schema.
