Kamernet.nl Property Search Scraper: Extract Dutch Student Housing & Rental Listings

Excerpt: Automate extraction of Dutch rental property data from Kamernet.nl, the Netherlands' leading student housing platform. Capture listings with pricing, locations, availability, amenities, and property details. Ideal for housing research, market analysis, and rental opportunity tracking across Dutch cities.

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Understanding Kamernet.nl and Its Value

Kamernet.nl is the Netherlands' premier platform for student housing and room rentals, particularly dominant in cities like Amsterdam, Rotterdam, Utrecht, and Delft. The platform specializes in shared accommodations, studios, and apartments targeted at students and young professionals navigating the notoriously tight Dutch housing market.

Unlike general rental platforms, Kamernet focuses on the unique Dutch housing ecosystem—kamers (rooms), studios, anti-kraak properties, and temporary rentals. For students seeking accommodation, landlords analyzing market rates, researchers studying Dutch housing dynamics, or housing agencies monitoring competition, Kamernet data provides critical insights into this specialized market segment.

Manual collection across searches, cities, and price ranges requires endless scrolling and data copying. This scraper automates extraction, transforming search results into structured datasets for analysis and decision-making.

What This Scraper Extracts

The Kamernet.nl scraper processes search result pages—listings displayed after applying filters for location, price, size, or amenities. It captures multiple properties from search pages, enabling comprehensive dataset building across cities or rental categories.

Key Data Extracted:

Visual Assets: Thumbnail URL, full preview image URL, and resized versions provide property visualization.

Property Identification: Listing ID, street, street slug, city, city ID, and city slug enable tracking and geographic analysis.

Pricing & Economics: Total rental price and utilities inclusion status inform budget analysis and cost comparisons.

Property Specifications: Surface area (square meters) and listing type (room, studio, apartment) categorize properties.

Availability: Start and end dates indicate rental periods and temporary vs. permanent options.

Amenities: Furnishing ID indicates whether properties come furnished or unfurnished.

Marketing Status: Is top advert, is new advert, is react for free, and is favorite flags reveal promotional strategies and user engagement.

Student Housing: Student house ID and student house advert flag identify shared student accommodations.

Input Configuration

The scraper processes Kamernet search result URLs with specific filter parameters.

Example Configuration:

{
  "proxy": {
    "useApifyProxy": false
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [
    "https://kamernet.nl/huren/huurwoningen-amsterdam?pageNo=2&radius=5&minSize=0&maxRent=0&searchView=1&sort=1&hasInternet=false&isBathroomPrivate=false&isKitchenPrivate=false&isToiletPrivate=false&suitableForNumberOfPersons=0&isSmokingInsideAllowed=false&isPetsInsideAllowed=false&nwlat=54.216270703936516&nwlng=-3.267085312500001&selat=50.130263513834905&selng=12.5532271875&mapZoom=7&mapMarkerLat=0&mapMarkerLng=0"
  ]
}

Example Screenshot:

Parameter Breakdown:

urls: Kamernet search result page URLs. The example targets Amsterdam rentals (page 2) within 5km radius. URL parameters include:

• pageNo=2: Pagination for multiple pages
• radius=5: Search radius in kilometers
• minSize=0 / maxRent=0: Size and price filters (0 = no limit)
• hasInternet, isBathroomPrivate, isKitchenPrivate, isToiletPrivate: Amenity filters
• suitableForNumberOfPersons: Occupancy capacity
• isSmokingInsideAllowed, isPetsInsideAllowed: House rules filters
• Map coordinates define geographic boundaries

max_items_per_url: Controls listings extracted per URL. Set to 20 for standard pages. Kamernet typically displays 20-25 listings per page.

ignore_url_failures: When true, continues processing if some URLs fail. Essential for batch operations.

proxy: Set useApifyProxy: false by default. Enable residential proxies for large-scale scraping to avoid detection.

URL Collection Tips: Perform manual searches on Kamernet with desired filters (city, price range, amenities), then copy URLs. For comprehensive datasets, include multiple page numbers and different cities.

Output Structure and Field Meanings

The scraper returns JSON with detailed property objects. Understanding each field enables effective analysis.

Visual Assets:

• Thumbnail URL: Small preview image for quick browsing
• Full Preview Image URL: High-resolution property image
• Resized Full Preview Image URL: Optimized image version for various display sizes

Property Identification:

• Listing ID: Unique identifier for tracking specific properties and avoiding duplicates
• Street / Street Slug: Property street address and URL-friendly version
• City / City Slug: City name and URL-friendly version for geographic filtering
• City ID: Numeric city identifier for database operations

Pricing:

• Total Rental Price: Monthly rent in euros
• Utilities Included: Boolean indicating if utilities (gas, water, electricity, internet) are included in rent—critical for true cost comparison

Property Specifications:

• Surface Area: Property size in square meters for space analysis and price-per-meter calculations
• Listing Type: Property category (kamer/room, studio, apartment, house)
• Furnishing ID: Indicates furnished (1), semi-furnished (2), or unfurnished (3) status

Availability:

• Availability Start Date: When property becomes available
• Availability End Date: When rental period ends (null for indefinite rentals)—identifies temporary vs. permanent options

Marketing Indicators:

• Is Top Advert: Premium/promoted listing flag
• Is New Advert: Recently posted listing indicator
• Is React For Free: Allows free contact (vs. paid membership requirement)
• Is Favorite: User-saved status

Student Housing:

• Student House ID: Identifier for shared student houses
• Is Student House Advert: Flags properties specifically for student sharing

Sample Output:

[
  {
  "thumbnail_url": "https://resources.kamernet.nl/image/a9e8088f-5073-46a5-8e27-b94fabf08749",
  "full_preview_image_url": "https://resources.kamernet.nl/image/b65ff9fa-abcb-42f2-9946-5c929d260a30",
  "resized_full_preview_image_url": "https://resources.kamernet.nl/image/b65ff9fa-abcb-42f2-9946-5c929d260a30/resize/422-225",
  "listing_id": 2348818,
  "is_top_advert": false,
  "is_react_for_free": false,
  "furnishing_id": 4,
  "availability_start_date": "2025-12-30T00:00:00",
  "availability_end_date": null,
  "street": "Patrijspoort",
  "street_slug": "patrijspoort",
  "city": "Amstelveen",
  "city_slug": "amstelveen",
  "is_favorite": false,
  "surface_area": 16,
  "listing_type": 1,
  "total_rental_price": 1100,
  "utilities_included": true,
  "is_new_advert": true,
  "student_house_id": null,
  "is_student_house_advert": false,
  "city_id": 22,
  "from_url": "https://kamernet.nl/huren/huurwoningen-amsterdam?pageNo=2&radius=5&minSize=0&maxRent=0&searchView=1&sort=1&hasInternet=false&isBathroomPrivate=false&isKitchenPrivate=false&isToiletPrivate=false&suitableForNumberOfPersons=0&isSmokingInsideAllowed=false&isPetsInsideAllowed=false&nwlat=54.216270703936516&nwlng=-3.267085312500001&selat=50.130263513834905&selng=12.5532271875&mapZoom=7&mapMarkerLat=0&mapMarkerLng=0"
}
]

Step-by-Step Implementation

1. Define Target Rentals: Identify needed cities, price ranges, property types, and amenities. Test searches on Kamernet to verify filters.

2. Build Search URLs: Copy URLs from manual searches. For comprehensive data, create multiple URLs with different filters: various cities (Amsterdam, Rotterdam, Utrecht), price brackets, room vs. studio.

3. Configure Input: Set up JSON with URLs. Adjust max_items_per_url (20 standard, higher for thorough extraction). Enable ignore_url_failures for resilience.

4. Launch and Monitor: Start scraper and monitor progress. Typical processing: 3-5 pages with 20 items complete in 2-3 minutes.

5. Validate Data: Verify critical fields (prices, locations, availability dates) are populated correctly.

6. Export and Analyze: Export as JSON/CSV/Excel. Remove duplicates by listing ID. Filter by criteria (price range, city, utilities included).

7. Handle Pagination: For large datasets, include multiple page URLs: pageNo=1, pageNo=2, etc.

Strategic Applications

Student Housing Search: Filter by city, price range, and utilities included to identify affordable options. Track is_react_for_free to find no-membership-required listings.

Market Rate Analysis: Calculate average rent per square meter across cities and neighborhoods. Compare furnished vs. unfurnished pricing premiums.

Availability Tracking: Monitor availability_start_date to identify upcoming vacancies. Filter by availability_end_date to find permanent vs. temporary rentals.

Competitive Intelligence: Housing agencies track competitor listings, pricing strategies, and promotional tactics (top adverts, new listings).

Geographic Analysis: Aggregate by city and neighborhood (street data) to understand supply concentration and regional pricing patterns.

Investment Research: Landlords analyze market rates before setting prices. Identify high-demand areas with limited supply.

Amenity Demand: Compare pricing for properties with private bathrooms, kitchens, or internet to quantify amenity value.

Advanced Techniques

Time-Series Tracking: Scrape weekly to monitor price changes and listing turnover. Track individual properties by listing ID over time.

Supply-Demand Analysis: Count new listings vs. disappearing listings to gauge market tightness. Identify cities with housing shortages.

Student House Analysis: Filter by is_student_house_advert to analyze shared accommodation market separately. Compare student house pricing vs. individual rentals.

True Cost Calculation: For utilities_included=false listings, estimate additional costs (€100-150/month typical) for accurate budget comparison.

Availability Gap Detection: Identify properties with long availability delays (start date far in future) potentially indicating lower demand or renovation.

Best Practices

Scraping Frequency: Dutch housing market updates multiple times daily. Daily scraping captures new listings quickly. Weekly scraping suits broader market analysis.

Data Validation: Verify prices are reasonable (€300-2000 typical range), surface areas positive, dates properly formatted.

Privacy Compliance: Handle address and contact data per GDPR requirements. Use data only for legitimate purposes.

Duplicate Management: Use listing ID to deduplicate. Same property may appear in multiple searches.

Geographic Accuracy: Validate city IDs and slugs match expected cities. Check map coordinates fall within Netherlands.

Currency Standardization: All prices in euros. Note scrape dates for inflation-adjusted historical analysis.

Conclusion

The Kamernet.nl Property Search Scraper transforms the Netherlands' leading student housing platform into actionable intelligence. From pricing dynamics to availability patterns, this tool provides comprehensive insights into Dutch rental markets. Whether searching for accommodation, conducting market research, monitoring competition, or analyzing housing trends, structured Kamernet data enables informed decisions in the competitive Dutch rental landscape.