We extract property listings, price per square metre, energy certificates, and agent metadata from ImmoScout24. 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 Residential Rent objects from immobilienscout24.de. All fields typed and schema-versioned.
"expose_id": "142958312", "title": "Modernes Apartment im Herzen von Berlin-Mitte", "cold_rent": 1250.0, "warm_rent": 1480.0, "rooms": 2.5, "living_space_sqm": 78.5, "energy_class": "B", "location_city": "Berlin", "location_zip": "10115"
| # | expose_id | title | cold_rent | warm_rent | rooms | living_space_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Residential Buy objects from immobilienscout24.de. All fields typed and schema-versioned.
"expose_id": "139482711", "title": "Helle Eigentumswohnung mit Südbalkon", "purchase_price": 450000.0, "price_per_sqm": 5625.0, "rooms": 3.0, "living_space_sqm": 80.0, "commission_pct": 3.57, "built_year": 2018, "location_city": "Munich"
| # | expose_id | title | purchase_price | price_per_sqm | rooms | living_space_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Commercial Properties objects from immobilienscout24.de. All fields typed and schema-versioned.
"expose_id": "140293847", "title": "Repräsentative Bürofläche in der HafenCity", "lease_rate": 4500.0, "total_area_sqm": 250.0, "property_type": "Office", "location_city": "Hamburg", "agent_company": "Engel & Völkers Commercial", "parking_spaces": 4
| # | expose_id | title | lease_rate | total_area_sqm | office_area_sqm | property_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agent Profiles objects from immobilienscout24.de. All fields typed and schema-versioned.
"agent_id": "A-849201", "name": "Thomas Müller", "company_name": "Müller Immobilien GmbH", "active_listings_count": 42, "average_rating": 4.8, "review_count": 156, "member_since": "2015-04-12", "profile_url": "https://www.immobilienscout24.de/anbieter/mueller-immobilien"
| # | agent_id | name | company_name | phone | mobile | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Energy & Building Specs objects from immobilienscout24.de. All fields typed and schema-versioned.
"expose_id": "142958312", "energy_class": "A+", "energy_consumption_kwh": 28.4, "heating_type": "Zentralheizung", "firing_type": "Fernwärme", "condition": "Neuwertig", "built_year": 2021, "elevator": true
| # | expose_id | energy_class | energy_consumption_kwh | heating_type | firing_type | condition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our ImmoScout24 scraper handles every layer of the platform: residential listings, commercial spaces, dynamic pricing, and agent intelligence - with Datadome circumvention built in.
Title, description, pricing, square metres, rooms, and amenities - scraped at expose level with high fidelity.
Capture cold rent, warm rent, purchase price, ancillary costs, and broker commission - timestamped per crawl.
Extract energy efficiency class, consumption metrics, heating type, construction year, and building condition.
City, ZIP code, neighbourhood, and geocoded coordinates extracted directly from map objects.
Broker name, agency, contact details, and active listing count - mapped to every property expose.
Office space, retail, industrial properties, and lease rates - segregated from residential data.
Pagination traversal and map-based coordinate searches to bypass standard 1,000-result list limits.
Track listing price drops, duration on market, and delisting events across target postcodes.
Datadome and Cloudflare circumvention via German residential proxies and token solving.
Brief in. Clean data out.
Provide postcodes, cities, property types, or agent IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and Datadome handling for immobilienscout24.de.
Schema validation, null-rate checks, price-outlier detection, and coordinate mapping before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
ImmoScout24 employs aggressive Datadome protection and complex map-based pagination. Here's how we stay resilient.
ImmoScout24 uses Datadome to block automated traffic. Our crawlers use German residential ISP proxies with realistic browser fingerprints, solving Datadome challenges natively to maintain continuous access.
ImmoScout24 search results and map interfaces rely heavily on JavaScript. We run full Playwright browser sessions to trigger lazy-loaded properties and extract precise coordinate data.
ImmoScout24 updates its DOM structure frequently. Our selector strategy uses multiple fallback chains per field, including raw JSON state extraction from the page source, ensuring pipeline stability.
For large city catalogues, we maintain a hash index of last-seen values per expose. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, Datadome block rates, and coverage drops, responding before you notice.
Automated Valuation Models (AVMs) ingest recent transaction prices, rent levels, and property specs to train pricing algorithms.
Institutional investors track gross yields by correlating purchase prices with local cold rent averages across micro-locations.
Analysts track rent index movements, time-on-market metrics, and supply volume across top German cities.
Real estate agencies monitor competitor listings, commission rates, and market share within specific postcodes.
Municipalities and researchers analyse housing supply, affordability ratios, and spatial distribution of available properties.
Consultancies track the distribution of energy efficiency classes and heating types to model retrofitting demand.
"ImmoScout24 holds the definitive pulse of the German housing market - but extracting it requires bypassing enterprise-grade bot protection."
Most teams underestimate the investment required: reliable ImmoScout24 scraping requires German residential proxies, Datadome token solving, full JavaScript rendering, and map-based pagination handling. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our immobilienscout24.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across DE regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About immobilienscout24.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property data is generally permissible for analytical purposes. DataFlirt targets only public, non-authenticated listings. We do not extract personal data of private tenants or circumvent authentication walls like MieterPlus. Clients should review ImmoScout24's ToS and consult legal counsel for specific use cases.
We use German residential ISP proxies combined with full Playwright browser sessions that mimic human interaction patterns. This allows us to solve Datadome challenges natively and maintain high extraction throughput without triggering blocks.
Yes. While ImmoScout24 obscures some exact addresses, we extract the precise latitude and longitude coordinates exposed to the map interface, allowing for accurate spatial analysis.
For targeted city or postcode searches, pipelines can run hourly. Full national refreshes typically complete within a 12-24 hour window depending on total active listing volume.
Yes. Every pipeline run produces timestamped snapshots. If a property's purchase price or cold rent changes, we record the diff, allowing you to track price reductions over time.
Yes. ImmoScout24 caps standard list results. We bypass this by segmenting searches using dynamic map bounding boxes and granular filters, ensuring 100% capture of available inventory in a region.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off city export or a continuous national feed across 400K listings - we scope, build, and operate the pipeline. Tell us what you need.
