We extract wine catalogues, pricing signals, vintage details, tasting notes, and expert ratings from Hawesko. 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 Wine Listings objects from hawesko.de. All fields typed and schema-versioned.
"sku": "1234567", "name": "Chateau Ripeau Grand Cru Classe", "vintage": "2018", "winery": "Chateau Ripeau", "region": "Bordeaux", "country": "France", "price": 45.9, "price_per_litre": 61.2
| # | sku | name | vintage | winery | region | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Expert Ratings objects from hawesko.de. All fields typed and schema-versioned.
"sku": "1234567", "rater_name": "Robert Parker", "score": 94, "max_score": 100, "drinking_window_start": 2024, "drinking_window_end": 2038, "rating_date": "2021-04-15"
| # | sku | rater_name | score | max_score | tasting_note | drinking_window_start |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from hawesko.de. All fields typed and schema-versioned.
"sku": "1234567", "current_price": 45.9, "original_price": 55.0, "discount_pct": 16.5, "stock_status": "in_stock", "delivery_time_days": "2-3", "currency": "EUR"
| # | sku | current_price | original_price | discount_pct | bulk_discount_available | package_deal_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Product Details objects from hawesko.de. All fields typed and schema-versioned.
"sku": "1234567", "alcohol_pct": 14.5, "sweetness": "dry", "acidity": 5.2, "allergens": "contains sulfites", "drinking_temperature": "16-18", "closure_type": "natural cork"
| # | sku | alcohol_pct | sweetness | acidity | allergens | drinking_temperature |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Customer Reviews objects from hawesko.de. All fields typed and schema-versioned.
"review_id": "REV-98213", "sku": "1234567", "rating": 5, "author": "WeinLiebhaber88", "review_date": "2023-11-12", "title": "Excellent Bordeaux", "body": "Deep ruby colour, complex nose of dark berries and cedar."
| # | review_id | sku | rating | author | review_date | title |
|---|---|---|---|---|---|---|
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Our Hawesko scraper handles the entire catalogue, capturing vintage rollovers, dynamic pricing, expert ratings, and tasting notes with full anti-bot circumvention built in.
Extract SKUs, names, vintages, and bottle sizes across all categories including red, white, rose, and sparkling wines.
Capture base price, per-litre price, promotional discounts, and bulk purchase pricing across the entire assortment.
Parse scores and tasting notes from Falstaff, Luca Maroni, Robert Parker, and James Suckling directly from product pages.
Extract structured data for terroir, appellation, country of origin, and specific grape variety blend percentages.
Capture sommelier descriptions, flavour profiles, sweetness levels, acidity, and recommended food pairings.
Monitor stock availability flags, low-stock warnings, and estimated shipping times for inventory planning.
Map multi-bottle bundles and tasting packages back to their individual component SKUs for accurate value comparison.
Extract customer star ratings, review text, author names, and publication dates across all products.
Track vintage rollovers and price changes over time with daily or weekly differential exports.
Brief in. Clean data out.
Provide categories, search terms, or specific winery URLs. We design the extraction schema together.
We configure Scrapy crawlers, German proxy rotation, session management, and CAPTCHA handling for hawesko.de.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
European eCommerce sites employ strict rate limiting and dynamic rendering. Here is how we maintain reliable extraction.
Hawesko employs geo-blocking and strict rate limits. Our crawlers use German residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass perimeter defenses.
Category pages and search filters rely on dynamic hydration. We run full Playwright browser sessions to trigger infinite scrolls and capture data that basic HTTP clients miss.
Marketing campaigns frequently alter Hawesko's DOM structure. Our strategy uses multiple fallback chains per field, including structured JSON-LD data extraction, ensuring consistent output.
Wine catalogues change constantly as vintages sell out. We maintain a hash index of last-seen values per SKU, emitting clean diffs when prices change or new vintages arrive.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or coverage drops, resolving issues before they impact your downstream analytics.
European wine retailers track Hawesko pricing, discounts, and package deals to optimise their own pricing strategies.
Analysts monitor shifts in grape varieties, regional popularity, and average price points to identify consumer trends.
Beverage distributors analyze the catalogue to identify gaps in their own portfolios and source new wineries.
eCommerce teams feed competitor price points into dynamic repricing engines to maintain market positioning.
Machine learning teams use structured tasting notes, grape blends, and food pairings to train recommendation algorithms.
Wineries monitor their product representation, ensuring accurate tasting notes, correct vintages, and MAP compliance.
"Hawesko holds the most structured dataset of European wine pricing and expert ratings, but accessing it requires navigating dynamic DOMs and strict rate limits."
Most teams underestimate the complexity of scraping European eCommerce targets. Reliable Hawesko extraction requires German residential proxies, Playwright for dynamic hydration, and strict schema validation to handle vintage rollovers. DataFlirt manages the infrastructure so your team can focus on market analysis.
Everything supported by our hawesko.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 manages JavaScript rendering and category pagination.
We maintain pools of German residential ISP proxies. Rotation happens per-request to prevent IP bans and rate limiting.
Pipelines run on AWS infrastructure. Airflow handles scheduling and dependency management, ensuring reliable delivery.
Data delivered to where your team already works — no new tooling required.
About hawesko.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and catalogue information is generally permissible under applicable European law. DataFlirt extracts only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
We use German residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. This prevents IP bans and ensures consistent access to the catalogue.
Yes. Every pipeline run produces timestamped snapshots. We track vintage fields specifically and emit differential updates when a SKU transitions to a new year.
Yes. We parse structured scores and tasting notes from recognized critics like Robert Parker, Falstaff, and Luca Maroni directly from the product detail pages.
Full catalogue refreshes at a daily cadence complete within a 2-4 hour window. We can configure specific category pipelines for higher frequency monitoring if required.
Absolutely. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring across thousands of wines, we scope, build, and operate the pipeline. Tell us what you need.
