ImmobilienScout24 Scraper - Real Estate Germany

Pricing

$19.00/month + usage

ImmobilienScout24 Scraper - Real Estate Germany

Scrape ImmoScout24 listings in Germany for buy and rent. Filter by location, property type, price, rooms, size, energy class and more. Export clean JSON or CSV for market research, analytics, lead generation, and real estate monitoring.

Pricing

$19.00/month + usage

Rating

0.0

(0)

Developer

Iñigo Garcia Olaizola

Maintained by Community

Actor stats

Bookmarked

Total users

Monthly active users

2 days ago

Last modified

Immobilienscout24 Scraper – Germany Real Estate Listings

✅ What does this actor do?

The Immobilienscout24 Scraper extracts property listings in Germany from immobilienscout24.de and delivers clean JSON or CSV data for buy and rent markets. It is ideal for market research, price tracking, lead generation, and competitive analysis.

You can search by city, district, postcode, or geopath and filter by property type, price, rooms, living space, plot size, energy class, and more. Enable fetchDetails to add a full listing detail payload per property.

🏠 Use cases

Track apartment prices across German cities
Monitor new listings by property type (house, apartment, plot, garage)
Build datasets for investment analysis or valuation models
Generate lead lists for agents and brokers

🚀 How to use

Set a location (e.g., Berlin, Stuttgart, or /de/baden-wuerttemberg/freiburg-im-breisgau).
Choose an operation: buy or rent.
Select a propertyType (as shown in the Immobilienscout24 app UI).
Add filters if needed and run the actor.

🧾 Input parameters

Parameter	Type	Default	Description
`maxItems`	integer	`10`	Maximum number of listings to scrape.
`location`	string		Required. City, district, postcode, or geopath (e.g. `/de/baden-wuerttemberg/freiburg-im-breisgau`).
`operation`	string	`buy`	`buy` or `rent`.
`propertyType`	string	`house`	Buy: `apartment`, `house`, `plot`, `garage`, `solid-prefab`. Rent: `apartment`, `house`, `plot`, `temporary-living`, `shared-flat`, `garage`.
`sortBy`	string	`standard`	Sorting value used by the source.
`fetchDetails`	boolean	`false`	Fetches the expose detail for each listing and stores it under `_details` (slower).
`apartmentTypes`	array		Apartment filters (e.g. `loft`, `penthouse`, `groundfloor`).
`buildingTypes`	array		Building filters (e.g. `villa`, `bungalow`, `terracehouse`).
`minRooms` / `maxRooms`	number		Room range.
`minPrice` / `maxPrice`	integer		Price range.
`minLivingSpace` / `maxLivingSpace`	integer		Living space range in m2.
`minGround` / `maxGround`	integer		Plot/ground size range in m2.
`minConstructionYear` / `maxConstructionYear`	integer		Construction year range.
`energyEfficiencyClasses`	array		Energy classes (e.g. `a_plus`, `a`, `b`).
`equipment`	array		Equipment filters (e.g. `parking`, `balcony`).
`publishedAfter`	string		Date (`YYYY-MM-DD`) to return newer listings only.
`includeRented`	boolean	`false`	Include already rented listings.
`proxyConfiguration`	object	Apify proxy	Proxy settings.

Example input

{
  "maxItems": 60,
  "location": "Berlin",
  "operation": "buy",
  "propertyType": "apartment",
  "minRooms": 2,
  "maxRooms": 5,
  "minPrice": 250000,
  "maxPrice": 900000,
  "minLivingSpace": 60,
  "energyEfficiencyClasses": ["a_plus", "a", "b"],
  "equipment": ["balcony"],
  "fetchDetails": false,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

📊 Output

Each dataset item is a listing object with the most relevant fields exposed at the root. Typical fields include:

id, title, realEstateType
address.line and coordinates (lat, lon)
titlePicture and pictures
price, livingSpace, rooms (parsed from listing attributes)
energyEfficiencyClass, fairPrice, tags, realtor

If fetchDetails: true, each item also contains _details with the full expose response.

⚠️ Notes

fetchDetails adds 1 extra request per listing, making runs slower and more expensive.
Use a proxy for larger runs to avoid rate limits.

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