We extract marketplace listings, FMCG pricing, seller intelligence, and availability from kaufland.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 FMCG & Groceries objects from kaufland.de. All fields typed and schema-versioned.
"ean": "4000400085115", "title": "K-Classic Apfelsaft naturtrüb 1l", "brand": "K-Classic", "price": 0.99, "base_price": 0.99, "base_unit": "1 l", "pfand_amount": 0.25, "nutri_score": "C", "stock_status": "in_stock"
| # | product_id | ean | title | brand | category_path | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Marketplace Listings objects from kaufland.de. All fields typed and schema-versioned.
"item_id": "314829104", "title": "Bosch Serie 6 Waschmaschine", "manufacturer": "Bosch", "buybox_price": 499.0, "buybox_seller": "ElektroWelt24", "shipping_cost": 39.9, "delivery_time_min": 2, "delivery_time_max": 4, "energy_label": "A"
| # | item_id | title | manufacturer | mpn | condition | buybox_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Data objects from kaufland.de. All fields typed and schema-versioned.
"seller_id": "84921", "seller_name": "ElektroWelt24", "company_name": "ElektroWelt24 GmbH", "vat_id": "DE123456789", "rating_percentage": 98.4, "rating_count": 4192, "active_offers": 1450, "joined_date": "2019-11-04"
| # | seller_id | seller_name | company_name | legal_address | vat_id | return_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from kaufland.de. All fields typed and schema-versioned.
"item_id": "314829104", "seller_id": "84921", "price": 499.0, "shipping_fee": 39.9, "total_price": 538.9, "is_buybox_winner": true, "discount_pct": 15, "scraped_at": "2026-05-12T10:15:00Z"
| # | item_id | ean | seller_id | price | list_price | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from kaufland.de. All fields typed and schema-versioned.
"keyword": "kaffeemaschine", "position": 3, "item_id": "8192041", "is_sponsored": true, "price": 129.99, "rating": 4.6, "review_count": 312, "seller_name": "Kaufland", "scraped_at": "2026-05-12T10:16:22Z"
| # | keyword | position | item_id | title | price | is_sponsored |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our infrastructure handles location-based grocery pricing, third-party marketplace offers, and complex variant structures. We manage the session states and bot mitigation required for reliable extraction.
Capture base prices, Pfand amounts, ingredients, allergens, and Nutri-Score ratings for the direct retail catalogue.
Monitor third-party sellers, buybox ownership, shipping costs, and delivery windows across millions of SKUs.
Simulate specific PLZ (zip code) sessions to extract regional availability and localized pricing differences.
Extract exact product identifiers to match Kaufland inventory against competitor catalogues and internal databases.
Aggregate seller ratings, legal imprint data, VAT IDs, and total active assortment sizes for market research.
Identify standard prices versus loyalty card discounts and track weekly promotional flyers (Prospekte) digitally.
Track organic search rankings and identify sponsored product placements for retail media auditing.
Extract EU energy efficiency labels, hazard warnings, and mandatory compliance documentation links.
Run delta extractions that only deliver records where price, stock, or buybox status has changed.
Brief in. Clean data out.
Provide EANs, category URLs, or search terms. We define the extraction schema and PLZ targeting together.
We configure Scrapy crawlers, session management, and proxy rotation to handle Kaufland's bot protection.
Schema validation, null-rate checks, and price-outlier detection run on sample data before launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on schedule.
Extracting data from a hybrid grocery and marketplace platform requires handling complex session states and aggressive bot mitigation.
Grocery availability and delivery windows on Kaufland.de depend heavily on the user's postal code. We maintain stateful browser sessions injected with specific PLZ cookies to extract accurate regional data.
Kaufland employs strict bot protection. We route requests through German residential proxies and utilise Playwright to generate valid browser fingerprints, solving challenges before they block the pipeline.
Third-party seller lists and shipping calculations are loaded asynchronously via JavaScript. Our infrastructure executes the necessary scripts to capture the complete offer stack, not just the buybox winner.
Kaufland's DOM structure differs significantly between fresh groceries and electronics. We normalise these disparate layouts into a single, predictable schema for your data warehouse.
To monitor marketplace pricing across millions of SKUs, we use hash-based diffing. The pipeline only emits records when a price, stock status, or buybox owner changes, reducing your ingest costs.
Brands track retail prices, promotional discounts, and Kaufland Card offers to ensure pricing parity across German supermarkets.
Marketplace merchants monitor competitor buybox win rates, shipping fees, and stock levels to optimise their own repricing algorithms.
Manufacturers audit third-party sellers on the Kaufland marketplace for Minimum Advertised Price violations.
Retail analysts map category depth, brand presence, and private label penetration (e.g., K-Classic) within specific segments.
Agencies track sponsored product placements and organic search share of voice for targeted keywords.
Supply chain teams ingest delivery window estimates and stock status changes to model marketplace demand velocity.
"Kaufland.de merges a massive grocery operation with a sprawling third-party marketplace, creating a highly complex but valuable pricing dataset."
Extracting data from Kaufland requires handling location-specific sessions, dynamic shipping logic, and aggressive bot mitigation. DataFlirt manages the residential proxy routing and JavaScript execution, ensuring you receive clean, normalised records without maintaining infrastructure.
Everything supported by our kaufland.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 manages orchestration and deduplication. Playwright handles JavaScript execution and stateful PLZ sessions.
German ISP proxies route requests to bypass bot protection and maintain realistic geographic profiles.
Pipelines execute on AWS Lambda and ECS, orchestrated by Airflow for strict SLA adherence.
Data delivered to where your team already works — no new tooling required.
About kaufland.de scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure our crawlers to initiate sessions using specific PLZ (postal codes) to capture accurate regional pricing, grocery availability, and delivery estimates.
We extract the complete list of offers for every SKU. This includes the buybox winner as well as all alternative third-party sellers, their pricing, shipping costs, and condition notes.
We utilize German residential proxy pools and full Playwright browser sessions to generate valid TLS fingerprints and solve challenges dynamically, ensuring uninterrupted extraction.
Yes. Our schema normalises pricing by explicitly separating the base item price, the mandatory Pfand amount for beverages, and the calculated base price per unit.
We extract publicly visible Kaufland Card discount prices displayed on product pages and digital flyers. However, we do not support scraping personalised offers that require account authentication.
We configure pipelines based on your requirements. Critical SKU lists can be tracked hourly for repricing algorithms, while full category sweeps typically run daily or weekly.
Yes. When exposed in the DOM or structured metadata, we extract exact product identifiers (EAN/GTIN) to facilitate matching against Amazon, eBay, or your internal catalogue.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily FMCG price monitoring or continuous marketplace seller tracking, we build and maintain the pipeline. Specify your requirements.
