We extract product configurations, material specs, designer attributions, and dynamic pricing from Vitra. 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 Core objects from vitra.com. All fields typed and schema-versioned.
"sku": "21003000", "title": "Eames Lounge Chair", "designer": "Charles & Ray Eames", "design_year": 1956, "category": "Lounge Chairs", "base_price": 6450.0, "currency": "EUR", "collection_name": "Vitra Classics"
| # | sku | title | designer | design_year | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Materials & Finishes objects from vitra.com. All fields typed and schema-versioned.
"sku": "21003000", "component_name": "Seat Shell", "material_type": "Moulded Plywood", "colour_name": "Santos Palisander", "finish_type": "Veneer", "swatch_url": "https://www.vitra.com/swatches/santos_palisander.jpg", "sustainability_cert": "FSC Certified"
| # | sku | component_name | material_type | colour_name | colour_hex | finish_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Dimensions & Specs objects from vitra.com. All fields typed and schema-versioned.
"sku": "21003000", "width_mm": 840, "height_mm": 890, "depth_mm": 850, "seat_height_mm": 380, "weight_kg": 32.5, "assembly_required": false, "max_load_kg": 120
| # | sku | width_mm | height_mm | depth_mm | seat_height_mm | armrest_height_mm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Designers objects from vitra.com. All fields typed and schema-versioned.
"designer_id": "D-042", "name": "Jean Prouvé", "birth_year": 1901, "death_year": 1984, "bio": "French metal worker, self-taught architect and designer.", "collaborations": "['Standard Chair', 'EM Table', 'Antony']", "profile_url": "https://www.vitra.com/en-un/about-vitra/designers/jean-prouve"
| # | designer_id | name | bio | birth_year | death_year | active_years |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Dealer Network objects from vitra.com. All fields typed and schema-versioned.
"store_id": "LOC-8821", "name": "VitraHaus", "type": "Flagship Store", "city": "Weil am Rhein", "country": "Germany", "latitude": 47.6025, "longitude": 7.6186, "phone": "+49 7621 702 3500"
| # | store_id | name | type | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Vitra scraper navigates complex product configurators, material matrices, and dimensional schematics. We extract high-fidelity catalogue data using full browser rendering to capture state-dependent pricing and imagery.
Parse Vitra's interactive product configurator. We capture pricing, imagery, and SKUs across all possible combinations of base, shell, fabric, and glide options.
Extract precise millimetre measurements for width, height, depth, and seat height, alongside links to publicly available 2D/3D planning files.
Index fabric collections (e.g., Hopsak, Laser, Twill), leather grades, and wood veneers with their respective colour codes and high-resolution swatch URLs.
Map products to their creators. Extract designer biographies, historical timelines, and cross-reference entire collections by Charles & Ray Eames, Jean Prouvé, or Jasper Morrison.
Capture region-specific pricing and availability across Vitra's global storefronts, normalising currencies and tax inclusions per locale.
Extract deep links to lifestyle photography, isolated product shots, and detail views without compression artifacts.
Scrape environmental certifications, recycled content percentages, and specific care instructions for distinct material combinations.
Extract the global network of Vitra retail partners, flagship stores, and certified dealers with geocoding, contact details, and store types.
Track changes in catalogue additions, discontinued variants, and price adjustments with hash-based diffing to reduce downstream processing.
Brief in. Clean data out.
Provide target categories, designer profiles, or specific product lines. We map the extraction schema to your data model.
We configure Playwright crawlers to handle Vitra's configurator states, dynamic asset loading, and region-specific routing.
Schema validation, null-rate checks on material matrices, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from high-end design brands requires navigating complex front-end frameworks and nested variant logic.
Vitra's product pages rely on heavy JavaScript to render variant combinations (e.g., an Eames chair with different woods, leathers, and bases). We use Playwright to systematically iterate through configurator states, capturing the dynamic SKU, price, and image for every permutation.
Design data relies on visual fidelity. We intercept network requests to extract the original, uncompressed CDN links for product imagery, material swatches, and dimensional line drawings.
Vitra automatically redirects users based on IP. We use region-specific residential proxies to enforce consistent locale targeting, ensuring pricing and availability data matches your target market accurately.
Furniture specifications are often unstructured text. We parse HTML tables and description blocks into strict JSON schemas, separating dimensions, weights, and material compositions into queryable numerical and categorical fields.
We maintain state across runs to detect when new designer collections launch, when specific material finishes are discontinued, or when base prices update, delivering only the delta to your warehouse.
Aggregators and design platforms ingest Vitra's catalogue to populate their own 3D planning tools and specification databases.
High-end furniture manufacturers track Vitra's pricing strategies across different regions and material tiers to position their own portfolios.
Design forecasters analyse the introduction and discontinuation of specific fabrics, colours, and finishes to identify macro trends in commercial and residential interiors.
Legal and brand teams map the official dealer network against third-party sellers to identify unauthorised distributors and counterfeiters.
Procurement teams extract sustainability certifications and material origins to benchmark against ESG requirements for commercial office fit-outs.
BIM and CAD library maintainers automate the extraction of 2D/3D planning files and dimensional specs to keep their architectural software plugins updated.
"Vitra's catalogue is a masterclass in modular design. Extracting it requires a pipeline that understands complex variant matrices, not just flat HTML pages."
Scraping a standard eCommerce site is trivial. Scraping a configurator that generates thousands of unique permutations based on base type, shell material, upholstery grade, and glide options requires sophisticated state management. DataFlirt builds pipelines that traverse these logic trees automatically, outputting clean, normalised variant data.
Everything supported by our vitra.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 the complex JavaScript execution required by Vitra's product configurators.
We use EU and US residential proxies to bypass region-based redirects, ensuring we extract the correct localised catalogue and pricing data.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. All state and diff histories are stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About vitra.com scraping, legality, and pipeline operations.
Ask us directly →We use Playwright to programmatically interact with the configurator UI. Our scripts map the dependency logic (e.g., certain fabrics are only available with specific base finishes) and iterate through all valid combinations, capturing the dynamic SKU, price, and image for each state.
We extract links to publicly available 2D and 3D planning files found on the standard product pages. We do not extract proprietary BIM/CAD assets that require a registered Vitra Professionals account.
Scraping publicly available factual data — such as dimensions, materials, and retail pricing — is generally permissible. We do not bypass authentication walls or extract proprietary trade-secret data. Clients should ensure their use of the data complies with relevant copyright and intellectual property laws regarding imagery and design patents.
For furniture catalogues, daily or weekly runs are standard. Vitra's pricing and catalogue do not fluctuate intraday like commodity eCommerce, making daily delta runs the most cost-effective and practical cadence.
Yes. We can configure the pipeline to target vitra.com from specific geographic endpoints (e.g., Germany, UK, USA) using residential proxies, ensuring we capture the correct regional pricing, currency, and availability.
Yes. We provide a sample extraction of a specific product family (e.g., the Eames Plastic Chair collection) so you can validate our handling of variant matrices and material fields before committing to a full pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue extraction for an interior design platform or continuous price monitoring across regions — we scope, build, and operate the pipeline. Tell us what you need.
