We extract auto parts listings, tyre specifications, workshop service pricing, and branch-level inventory from atu.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 Auto Parts objects from atu.de. All fields typed and schema-versioned.
"article_id": "ATU123456", "name": "Bremsscheibe belueftet", "brand": "Brembo", "oem_number": "1K0615301AA", "price": 54.99, "category": "Bremsen", "stock_status": "in_stock", "delivery_time": "1-2 Werktage"
| # | article_id | name | brand | oem_number | price | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Tyres objects from atu.de. All fields typed and schema-versioned.
"article_id": "TYR98765", "brand": "Michelin", "model": "CrossClimate 2", "width": 205, "profile": 55, "diameter": 16, "season": "Allwetter", "price": 112.5, "eu_label_fuel": "C"
| # | article_id | brand | model | width | profile | diameter |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Workshop Services objects from atu.de. All fields typed and schema-versioned.
"service_id": "SRV102", "name": "Oelwechsel inkl. Filter", "category": "Inspektion", "base_price": 99.0, "duration_mins": 45, "vehicle_type": "PKW", "branch_availability": true, "description": "Fachgerechter Oelwechsel nach Herstellervorgabe."
| # | service_id | name | category | base_price | duration_mins | vehicle_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Branch Data objects from atu.de. All fields typed and schema-versioned.
"branch_id": "B045", "name": "ATU Muenchen-Pasing", "city": "Muenchen", "postcode": "81241", "phone": "+49 89 1234567", "latitude": 48.1462, "longitude": 11.4589, "services_offered": "['Werkstatt', 'Reifenservice', 'Shop']"
| # | branch_id | name | address | city | postcode | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Pricing objects from atu.de. All fields typed and schema-versioned.
"article_id": "ATU123456", "branch_id": "B045", "price": 54.99, "original_price": 64.99, "discount_pct": 15, "stock_level": 4, "pickup_available": true, "last_updated": "2026-05-12T08:30:00Z"
| # | article_id | branch_id | price | original_price | discount_pct | stock_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our ATU scraper navigates complex vehicle selection flows, branch specific pricing, and dynamic inventory states to deliver structured aftermarket intelligence.
Automated navigation through the KBA (Kraftfahrt-Bundesamt) vehicle selection flow to extract fitment specific part availability.
Extract manufacturer part numbers and OEM equivalents linked to aftermarket replacements within the ATU catalogue.
Structured extraction of width, profile, diameter, speed index, load index, and EU tyre label metrics.
Simulate local branch selection via cookie manipulation to capture store specific stock levels and click and collect availability.
Extract flat rate service costs, inspection fees, and tyre fitting charges across different vehicle classes.
Track base prices, promotional discounts, and ATU Card member pricing variations timestamped per run.
Full extraction of branch addresses, coordinates, operating hours, and contact details across Germany and Austria.
Track real time availability signals including exact stock counts, low stock warnings, and estimated delivery windows.
Maintain a hash index of previously scraped items to emit only changed records, optimising warehouse storage and compute.
Brief in. Clean data out.
Provide target categories, HSN/TSN lists, or specific branch IDs. We define the extraction schema and frequency.
We configure Playwright crawlers to handle branch cookies, vehicle selection modals, and pagination on atu.de.
Schema validation, price outlier detection, and fitment mapping checks before the production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or via Webhook on your defined cadence.
Extracting accurate data from atu.de requires managing stateful sessions, dynamic branch contexts, and complex vehicle selection flows.
Pricing and availability on atu.de change based on the selected branch. We manage stateful browser contexts, injecting specific branch cookies to extract localised data without manual navigation steps.
Part compatibility requires an active vehicle session. Our crawlers programmatically submit KBA numbers (HSN/TSN) to establish the correct session state before scraping category pages.
Stock levels and delivery estimates are often loaded asynchronously via XHR after the initial page load. We use Playwright to intercept these network requests and parse the raw JSON responses directly.
To prevent geo blocking and rate limiting, all requests are routed through German residential proxies, ensuring consistent access to regional pricing and branch data.
Auto parts data is notoriously unstructured. We apply regex and NLP parsing to extract clean dimensions, voltages, and thread sizes from raw description text blocks.
Independent Aftermarket retailers track ATU pricing on fast moving parts like brakes and filters to adjust their own pricing strategies.
Tyre manufacturers and distributors monitor retail prices, stock availability, and seasonal discount campaigns across the ATU network.
Independent garages and franchise networks extract flat rate service pricing to benchmark their inspection and repair costs.
Supply chain analysts monitor branch level stock depletion rates for specific OEM parts to model regional demand patterns.
Automotive brands audit atu.de to ensure their products are represented correctly, tracking MAP compliance and product descriptions.
Cataloguing teams extract HSN/TSN to part number relationships to enrich their own vehicle compatibility databases.
"In the German aftermarket, knowing the price is useless without knowing the exact vehicle fitment and the branch level availability."
Scraping atu.de requires more than simple HTTP requests. You have to maintain state, simulate KBA vehicle selections, and iterate through hundreds of branch contexts to get a complete picture of the market. DataFlirt manages this stateful complexity so your team receives clean, normalised parts data ready for analysis.
Everything supported by our atu.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 the crawl frontier while Playwright handles the complex state requirements for vehicle selection and branch contexts on atu.de.
We utilise high quality German residential proxies to ensure consistent access and avoid bot mitigation blocks based on ASN reputation.
Pipelines are scheduled via Apache Airflow on Kubernetes, providing strict SLA adherence and automatic retries for failed branch queries.
Data delivered to where your team already works — no new tooling required.
About atu.de scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure the pipeline to iterate through specific branch IDs, setting the appropriate session cookies to extract localised pricing and stock availability.
We programmatically submit HSN/TSN (KBA numbers) to the atu.de vehicle selector. The crawler then maintains this session state while scraping the relevant category pages to ensure accurate fitment data.
Yes. Where ATU lists OEM equivalent numbers for aftermarket parts, we extract and normalise this data into structured arrays linked to the primary article ID.
For targeted lists of fast moving parts, we can configure hourly extraction pipelines. Full catalogue refreshes are typically scheduled on a daily or weekly cadence.
Yes. We extract all available EU label metrics including fuel efficiency class, wet grip class, and external rolling noise decibel values.
Yes. We extract flat rate pricing for standard services like oil changes, inspections, and tyre fitting, noting any variations based on vehicle class.
Yes. We run a sample extraction of up to 500 parts or a specific category to validate the schema and ensure all required fitment and pricing fields are captured accurately.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily tyre pricing updates or a complete export of aftermarket parts mapped to HSN/TSN codes, we build and maintain the infrastructure. Contact us to define your schema.
