We extract product listings, pricing signals, size availability, and material specifications from goertz.de. 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 goertz.de. All fields typed and schema-versioned.
"sku": "GZ-849201", "title": "Classic Leather Chelsea Boots", "brand": "Vagabond", "price": 129.95, "currency": "EUR", "colour": "Black", "upper_material": "Leather", "heel_height": "3 cm"
| # | sku | ean | title | brand | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Size & Availability objects from goertz.de. All fields typed and schema-versioned.
"sku": "GZ-849201", "size_eu": "42", "in_stock": true, "stock_level": "low", "delivery_time": "2-3 days", "store_availability": false, "timestamp": "2026-05-12T10:15:00Z"
| # | sku | size_eu | size_uk | in_stock | stock_level | delivery_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from goertz.de. All fields typed and schema-versioned.
"sku": "GZ-849201", "current_price": 99.95, "list_price": 129.95, "discount_pct": 23, "sale_badge": true, "voucher_eligible": false, "price_timestamp": "2026-05-12T10:15:00Z"
| # | sku | current_price | list_price | discount_pct | campaign_name | voucher_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Brand & Category objects from goertz.de. All fields typed and schema-versioned.
"brand_name": "Vagabond", "category_path": "Men > Shoes > Boots > Chelsea Boots", "gender": "Men", "season": "AW26", "total_products": 342, "brand_url": "https://www.goertz.de/marken/vagabond/"
| # | brand_id | brand_name | category_path | gender | season | collection |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from goertz.de. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "GZ-849201", "rating": 4.5, "title": "Great fit and quality", "date": "2026-04-10", "verified_purchase": true, "helpful_votes": 12
| # | review_id | sku | rating | title | text | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our goertz.de scraper handles dynamic size grids, regional pricing, and complex variant mappings to deliver clean product intelligence.
Extract titles, descriptions, images, and material specifications across all categories and brands.
Monitor stock status at the individual size level (EU/UK) to track sell-through rates and inventory depth.
Capture current price, original price, discount percentages, and promotional campaign flags.
Extract structured data for upper material, inner lining, sole composition, and heel height.
Link parent products to colour and size variants to maintain a relational catalogue structure.
Map the full site taxonomy from gender and primary categories down to specific sub-categories.
Identify products included in seasonal sales, clearance events, and brand-specific promotions.
Extract click-and-collect availability signals for specific postal codes and store locations.
Run extractions at daily, weekly, or custom intervals to maintain fresh pricing and stock data.
Brief in. Clean data out.
Provide category URLs, brand names, or specific SKUs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for goertz.de.
Schema validation, null-rate checks, and data typing verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Extracting retail data requires navigating dynamic frontend frameworks and anti-bot systems. Here is how we ensure reliable delivery.
Retail sites employ perimeter defense to block datacenter IPs. We route requests through German residential proxies with realistic browser fingerprints to maintain access.
Size availability and pricing often load via asynchronous JavaScript requests. We use Playwright to execute page scripts and capture the final rendered state.
Frontend layouts change frequently during seasonal updates. Our extraction logic relies on multiple fallback selectors and structured data (JSON-LD) to prevent pipeline failures.
For large catalogues, we hash field values and only emit records when prices or stock levels change, reducing your downstream processing compute.
Every run emits structured logs to our observability stack. We detect schema drift and null-rate spikes automatically, resolving issues before delivery.
Footwear retailers monitor goertz.de pricing and discount strategies to adjust their own market positioning.
Merchandising teams analyse brand coverage and category depth to identify missing product lines in their own catalogues.
Footwear brands audit retail listings to ensure compliance with Minimum Advertised Price agreements.
Supply chain analysts track size-level stockouts to estimate consumer demand for specific styles and colours.
Retail strategists compare promotional frequency and seasonal markdown timing against goertz.de.
Machine learning teams use structured product descriptions and material specs to train retail classification models.
"Goertz.de holds a critical cross-section of the European footwear market, but the data is locked behind dynamic size grids and regional stock indicators."
Extracting footwear data at scale requires handling complex variant matrices, dynamic pricing, and continuous availability checks. DataFlirt manages the proxy rotation, JavaScript rendering, and schema maintenance so your data engineering team receives structured, warehouse-ready records without the operational overhead.
Everything supported by our goertz.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 deduplication. Playwright handles JavaScript rendering and dynamic interaction flows.
We route requests through region-specific residential proxies to bypass retail bot protection and rate limiting.
Pipelines run on AWS infrastructure managed by Apache Airflow, ensuring reliable scheduling and delivery.
Data delivered to where your team already works — no new tooling required.
About goertz.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product and pricing information is generally permissible under EU law, provided it does not extract personal data or breach authentication barriers. DataFlirt targets only public catalogue data. Clients should consult legal counsel regarding their specific commercial use cases.
We utilise German residential proxies, TLS fingerprint spoofing, and request timing modelled on human behaviour to navigate perimeter defenses without triggering blocks.
Yes. Our extraction logic iterates through available size options on the product page to capture the specific availability status for each EU or UK size.
Pipelines can be configured for daily or weekly runs depending on your requirements. Price and stock updates are processed within hours of pipeline execution.
Yes. We parse the product detail sections to extract structured fields for upper materials, inner linings, sole types, and heel heights where available.
We require a defined scope, typically starting at specific brand categories or a minimum SKU count. Contact us with your target list for a detailed proposal.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full catalogue extraction or daily price monitoring for specific brands, we build and operate the infrastructure. Tell us your requirements.
