Funda.nl Property Search Scraper avatar
Funda.nl Property Search Scraper

Pricing

$20.00/month + usage

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Funda.nl Property Search Scraper

Funda.nl Property Search Scraper

Developed by

ecomscrape

ecomscrape

Maintained by Community

The Funda.nl Property Search Scraper extracts property information from Funda.nl. Capture data such as price, address, description and more by providing Property Search Query URLs.

0.0 (0)

Pricing

$20.00/month + usage

0

Total users

8

Monthly users

5

Runs succeeded

>99%

Issues response

6.4 days

Last modified

19 hours ago

Contact

If you encounter any issues or need to exchange information, please feel free to contact us through the following link: My profile

Professional Funda.nl Real Estate Data Extraction Solution

Introduction

Funda.nl stands as the Netherlands' premier real estate platform, offering the largest selection of houses for sale and rent across the country, attracting over 29 million monthly visits. As the digital gateway to Dutch property markets, Funda hosts millions of listings ranging from urban apartments to rural homes, making it an invaluable data source for real estate professionals, investors, researchers, and market analysts.

The challenge lies in manually collecting and analyzing the vast amount of property information scattered across thousands of listings. Traditional browsing methods prove time-consuming and inefficient when dealing with comprehensive market research, competitive analysis, or investment opportunity identification. This is where automated data extraction becomes essential for accessing actionable real estate intelligence.

Overview of the Funda.nl Property Scraper

The Funda.nl Property Search Scraper is a sophisticated data extraction tool designed to automate the collection of detailed property information from Funda's extensive database. This scraper efficiently processes property search result pages, extracting crucial data points that form the foundation of real estate analysis and decision-making.

Key strengths of this scraper include:

  • Comprehensive data extraction: Captures all essential property details including pricing, location, specifications, and seller information
  • Flexible input handling: Accepts various search URLs with different filtering criteria and geographical parameters
  • Scalable processing: Handles multiple URLs simultaneously with configurable item limits per page
  • Robust error handling: Features retry mechanisms and proxy support to ensure reliable data collection
  • Structured output: Delivers clean, organized data ready for analysis and integration

Target users typically include real estate agents, property investors, market researchers, appraisers, developers, and data analysts who require systematic access to Dutch property market information for competitive intelligence, investment analysis, or market trend studies.

Input and Output Details

Example url 1: https://www.funda.nl/zoeken/koop/?selected_area=[%22gemeente-lochem%22]

Example url 2: https://www.funda.nl/en/zoeken/koop?selected_area=[%22loenen%22]

Example url 3: https://www.funda.nl/en/zoeken/koop

Example Screenshot of property list by query page:

Input Format

The scraper accepts a JSON configuration that defines extraction parameters and data collection settings:

{
"max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
"proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
},
"max_items_per_url": 20,
"urls": [ // Links to property list by query pages.
"https://www.funda.nl/zoeken/koop/?selected_area=[%22gemeente-lochem%22]",
"https://www.funda.nl/en/zoeken/koop?selected_area=[%22loenen%22]",
"https://www.funda.nl/zoeken/koop"
]
}

Configuration parameters explained:

  • max_retries_per_url: Controls persistence when encountering access issues, typically set to 2-3 for optimal balance between reliability and speed
  • proxy: Essential for avoiding bot detection, with residential proxies from relevant countries (like Singapore for international access) providing best results
  • max_items_per_url: Limits extraction volume per search page, useful for controlled data sampling or testing
  • urls: Array of Funda search result URLs with specific criteria, area filters, or property type selections

Output Format

You get the output from the Funda.nl Property Search Scraper stored in a tab. The following is an example of the Information Fields collected after running the Actor.

[ // List of property information
{
"id": "43860189",
"url": "https://www.funda.nl/detail/koop/lochem/huis-badhuisweg-1/43860189/",
"name": "Badhuisweg 1",
"image_urls": [
"https://cloud.funda.nl/valentina_media/203/477/468_180x120.jpg 180w, https://cloud.funda.nl/valentina_media/203/477/468_360x240.jpg 360w, https://cloud.funda.nl/valentina_media/203/477/468_720x480.jpg 720w",
"https://cloud.funda.nl/valentina_media/203/213/388_180x120.jpg 180w, https://cloud.funda.nl/valentina_media/203/213/388_360x240.jpg 360w, https://cloud.funda.nl/valentina_media/203/213/388_720x480.jpg 720w",
"https://cloud.funda.nl/valentina_media/203/213/393_180x120.jpg 180w, https://cloud.funda.nl/valentina_media/203/213/393_360x240.jpg 360w, https://cloud.funda.nl/valentina_media/203/213/393_720x480.jpg 720w",
"https://cloud.funda.nl/valentina_media/186/784/277_180x180.jpg 180w, https://cloud.funda.nl/valentina_media/186/784/277_360x360.jpg 360w, https://cloud.funda.nl/valentina_media/186/784/277_720x720.jpg 720w",
"https://cloud.funda.nl/valentina_media/186/784/277_180x180.jpg 180w, https://cloud.funda.nl/valentina_media/186/784/277_360x360.jpg 360w, https://cloud.funda.nl/valentina_media/186/784/277_720x720.jpg 720w"
],
"address": "7241DD Lochem",
"price": 1200000.0,
"currency": "€",
"details": {
"floor_area": "459 m²",
"plot_area": "1.369 m²",
"bedrooms": "5",
"energy_label": "A+"
},
"description": "Geheel gerenoveerd koetshuis, omsloten door een heerlijke tuin",
"seller": {
"name": "De Haan Schippers Makelaars | Baerz & Co",
"url": "https://www.funda.nl/makelaar/3147-de-haan-schippers-makelaars-baerz-en-co/"
},
"category": "in Gemeente Lochem"
}, // ... Many other property details
]

Field explanations and applications:

  • ID: Unique Funda property identifier, essential for tracking listings over time and avoiding duplicates in databases
  • URL: Direct link to detailed property page, enabling deeper analysis or user navigation to full listing information
  • Name: Property title/headline as displayed on Funda, useful for marketing analysis and listing categorization
  • Image URLs: Array of property photo links, valuable for visual analysis, automated property assessments, or marketing materials
  • Address: Complete property location, critical for geographical analysis, proximity studies, and location-based valuations
  • Price: Listed asking price with currency, fundamental for market analysis, price tracking, and investment calculations
  • Details: Condensed property specifications (rooms, size, year built), enabling quick filtering and comparison across listings
  • Description: Full property description text, useful for sentiment analysis, feature extraction, and automated property categorization
  • Seller: Real estate agent or agency information, valuable for market share analysis and agent performance tracking
  • Category: Property type classification, essential for segmented market analysis and targeted research

Usage Instructions

Step-by-step implementation:

  1. Prepare search URLs: Navigate to Funda.nl, apply desired filters (location, price range, property type), and copy the resulting search page URLs
  2. Configure extraction parameters: Set appropriate retry limits (2-3 recommended), enable proxy settings for your target region, and define item limits based on data needs
  3. Execute scraping process: Input the configuration and monitor extraction progress, typically processing 10-20 items per minute depending on proxy performance
  4. Validate output data: Check extracted records for completeness and accuracy, particularly price formatting and address consistency

Best practices for optimal results:

  • Use residential proxies from European locations to minimize detection risk
  • Implement reasonable delays between requests (1-2 seconds) to avoid overwhelming Funda's servers
  • Start with smaller batches (5-10 URLs) to test configuration before scaling up
  • Regularly update search URLs as Funda may modify their URL structure over time

Common troubleshooting scenarios:

  • Empty results: Verify URL format and ensure search pages contain visible listings
  • Access errors: Check proxy configuration and consider rotating proxy locations
  • Incomplete data: Some fields may be optional on certain listings; implement data validation to handle missing information gracefully

Benefits and Applications

Time efficiency gains: Manual collection of equivalent data would require hours of browsing and copying, while automated extraction processes hundreds of listings in minutes. This efficiency enables regular market monitoring and comprehensive competitive analysis that would otherwise be impractical.

Real-world applications span numerous use cases:

  • Market research: Track pricing trends, analyze supply patterns, and identify emerging neighborhood developments
  • Investment analysis: Screen properties meeting specific criteria, compare yields across regions, and identify undervalued opportunities
  • Competitive intelligence: Monitor competitor listings, analyze pricing strategies, and track market positioning
  • Academic research: Study housing market dynamics, urban development patterns, and socioeconomic correlations

Business value creation includes enhanced decision-making through data-driven insights, reduced research costs through automation, improved market timing through regular monitoring, and competitive advantages through comprehensive market intelligence that manual methods cannot match.

Conclusion

The Funda.nl Property Search Scraper transforms time-consuming manual property research into efficient, systematic data collection. By automating access to Netherlands' most comprehensive real estate database, this tool empowers users with the market intelligence necessary for informed decision-making in Dutch property markets.

Ready to streamline your real estate data collection? Start extracting valuable property insights from Funda.nl today and gain the competitive edge that comprehensive market data provides.

Related Actors

  • Funda.nl Property Details Scraper: A specialized data extraction tool engineered to harvest detailed property information from Funda's dominant Dutch real estate marketplace.

Your feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about Funda.nl Property Search Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.