We extract furniture listings, material specifications, local inventory levels, and pricing signals from XXXlutz.de. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 xxxlutz.de. All fields typed and schema-versioned.
"sku": "0024680101", "title": "Ecksofa Stoff Grau", "brand": "Dieter Knoll", "price": 1299.0, "material": "Textil", "width_cm": 285, "height_cm": 85, "depth_cm": 170, "assembly_required": true
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Variants & Options objects from xxxlutz.de. All fields typed and schema-versioned.
"sku": "0024680102", "parent_sku": "0024680000", "colour": "Anthrazit", "fabric_type": "Mikrofaser", "orientation": "Ottomane rechts", "price_diff": 150.0, "availability_status": "Auf Bestellung", "delivery_weeks": 8
| # | sku | parent_sku | colour | fabric_type | wood_type | orientation |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Local Inventory objects from xxxlutz.de. All fields typed and schema-versioned.
"sku": "0024680101", "store_id": "AT01", "store_name": "XXXLutz Wien", "zip_code": "1030", "stock_status": "Auf Lager", "quantity_available": 4, "click_and_collect_eligible": true, "floor_model_available": false
| # | sku | store_id | store_name | zip_code | city | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promotions objects from xxxlutz.de. All fields typed and schema-versioned.
"sku": "0024680101", "base_price": 1599.0, "current_price": 1299.0, "discount_pct": 18, "premium_card_price": 1199.0, "promotion_label": "Sommer Sale", "shipping_cost": 49.9, "assembly_cost": 99.0
| # | sku | base_price | current_price | discount_pct | premium_card_price | promotion_label |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from xxxlutz.de. All fields typed and schema-versioned.
"review_id": "REV-98765", "sku": "0024680101", "rating": 4, "author_name": "Klaus M.", "review_date": "2026-03-14", "review_title": "Bequem und stilvoll", "review_text": "Gutes Sofa, aber die Lieferung hat sich verzögert.", "verified_purchase": true
| # | review_id | sku | rating | author_name | review_date | review_title |
|---|---|---|---|---|---|---|
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Our XXXlutz scraper handles every layer of the catalogue: complex furniture configurations, physical store inventory checks, delivery lead times, and promotional pricing - with full JavaScript rendering built in.
Extract dimensions, materials, care instructions, and energy efficiency ratings for every item on the platform.
Query stock levels across physical XXXlutz branches. Track click-and-collect eligibility and floor model availability.
Capture every combination of fabric, wood type, colour, and orientation with associated price adjustments.
Track base prices, current discounts, and exclusive Premium Card pricing tiers timestamped per crawl.
Extract freight costs, parcel delivery availability, estimated lead times, and professional assembly service fees.
Filter and extract specific assortments from brands like Dieter Knoll, Xora, Boxxx, and Celina Home.
Extract URLs for PDF assembly instructions, warranty sheets, and technical data sheets.
Extract star ratings, customer text, and helpful votes to gauge product sentiment and quality.
Run daily diffs on stock and price to keep your internal systems synchronised with the live site.
Brief in. Clean data out.
Provide category URLs, target brands, or specific SKUs. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, and session management for xxxlutz.de.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Modern retail sites rely on dynamic rendering and complex variant structures. Here is how we ensure reliable extraction.
Retailers block repetitive datacenter IPs. Our crawlers use residential ISP proxies from Germany and Austria with realistic browser fingerprints to blend in with regular consumer traffic.
XXXlutz relies heavily on JavaScript for variant selection and local store stock checks. We run full Playwright browser sessions to trigger these dynamic XHR requests and capture the resulting data.
Product page layouts vary between simple decor items and complex modular sofas. We use multiple fallback chains per field to ensure consistent data extraction despite DOM variations.
To extract accurate branch stock levels, our pipeline simulates user location data and interacts with the store-selector API precisely as a human browser would.
We maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs for price or stock changes, reducing downstream processing load.
Furniture retailers monitor competitor pricing on identical brands and similar private-label items to optimise their own pricing strategy.
Category managers analyse product depth, material trends, and brand coverage to identify gaps in their own catalogues.
Logistics teams track delivery lead times across different furniture categories to benchmark their own supply chain performance.
Analysts track the introduction of new materials, colours, and designs to quantify shifting consumer preferences in the home and living sector.
Consultants analyse click-and-collect availability and store stock distribution to evaluate retail omnichannel maturity.
Computer vision teams extract high-resolution product images and dimension metadata to train visual search and room-planning models.
"XXXlutz holds the most comprehensive structured data on the European furniture market, but extracting variant-level stock across 48 physical stores requires serious infrastructure."
Scraping modern retail sites requires more than simple HTTP GET requests. Gathering precise dimensions, material composites, and branch-specific inventory from XXXlutz.de demands full JavaScript rendering, proxy rotation, and session management. DataFlirt handles the extraction logic so your engineers can focus on building data models.
Everything supported by our xxxlutz.de 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 retry logic. Playwright handles JavaScript rendering, store-selector interaction, and variant hydration.
We maintain pools of residential ISP proxies across DE and AT regions. Rotation happens per-request to prevent IP bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About xxxlutz.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and store data is generally permissible. DataFlirt targets only public, non-authenticated catalog data. We do not extract personal user data or circumvent authentication walls.
We use residential ISP proxies from Germany and Austria, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to ensure uninterrupted extraction.
Yes. We simulate location contexts to query the internal APIs that populate the store availability widgets, extracting stock status for any specified branch.
Yes. Furniture pricing often changes based on fabric grade or orientation. Our pipeline iterates through variant combinations to capture the exact price and lead time for each specific configuration.
We can configure pipelines to run daily or hourly diffs on specific high-priority SKUs to keep your inventory models updated with minimal latency.
Our packages typically start at a defined category list or a set of target brands with weekly delivery. Contact us with your specific volume requirements for a scoped quote.
Yes. We provide a sample run of up to 200 products including variant and store data during the scoping process, allowing your engineering team to validate the schema.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across thousands of SKUs - we scope, build, and operate the pipeline. Tell us what you need.
