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Professional Argenprop.com Real Estate Data Extraction Solution

ArgeProp.com stands as one of Argentina's most prominent real estate platforms, connecting property seekers with sellers and rental agents across the country. The website hosts thousands of property listings ranging from apartments and houses to commercial spaces, making it a valuable resource for understanding the Argentinian real estate market. However, manually collecting data from individual property listings becomes time-consuming and inefficient when you need to analyze market trends, compare prices across neighborhoods, or build comprehensive property databases.

This is where the ArgeProp.com Property Details Scraper becomes invaluable. Whether you are a real estate agent tracking competitive listings, an investor analyzing market opportunities, a researcher studying housing trends, or a data analyst building predictive models, this scraper automates the entire data collection process. Instead of spending hours copying and pasting information from dozens or hundreds of property pages, you can extract structured data in minutes, allowing you to focus on analysis and decision-making rather than manual data entry.

What This Scraper Does and Who Benefits From It

The ArgeProp.com Property Details Scraper is designed to extract comprehensive information from property listing pages on ArgeProp.com. When you provide URLs of specific property listings, the scraper visits each page, intelligently identifies and extracts relevant data fields, and returns the information in a clean, structured format that you can immediately use for analysis or integration into your systems.

The scraper's strength lies in its ability to capture not just basic information like price and address, but also detailed property features, complete descriptions, multiple image URLs, location coordinates, and seller contact information. This comprehensive approach ensures you have all the data you need for thorough property evaluation without missing critical details that could influence investment or purchasing decisions.

This tool serves several key audiences effectively. Real estate professionals can monitor competitor listings and track market changes across different neighborhoods. Property investors benefit from rapid data collection for portfolio analysis and opportunity identification. Market researchers gain access to structured data for trend analysis and forecasting. Data scientists can build datasets for machine learning models that predict property values or identify undervalued opportunities. Even individual property buyers who want to systematically compare multiple options will find this scraper useful for making informed decisions.

Input and Output Specifications

Example url 1: https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563

Example url 2: https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17850004

Example url 3: https://www.argenprop.com/departamento-en-alquiler-en-centro--18031438

Example Screenshot of property information page:

Input Format

The scraper accepts JSON configuration with specific parameters to control the extraction process:

{
  "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
  },
  "urls": [ // Links to property information pages.
    "https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563",
    "https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17850004",
    "https://www.argenprop.com/departamento-en-alquiler-en-centro--18031438"
  ]
}

Key Input Parameters:

• max_retries_per_url: Controls the maximum number of retry attempts for each URL, ensuring reliable data extraction even if initial requests fail
• proxy configuration: Essential for avoiding bot detection and maintaining consistent access to Argenprop's servers
• urls array: Contains the specific Argenprop property detail page URLs you want to scrape

The proxy settings are particularly important as they help maintain access reliability and prevent IP blocking during data collection processes.

Output Format and Data Fields

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

[ // List of property information
  {
  "id": "17185563",
  "url": "https://www.argenprop.com/departamento-en-alquiler-en-barrio-industrial-3-ambientes--17185563",
  "title": "Alquiler en Barrio Industrial, Rosario",
  "address": "Rufino Ortega 200, Piso 05",
  "details": [
    {
      "label": "Sup. cubierta",
      "value": "47 m² Cubierta"
    },
    {
      "label": "Dormitorios",
      "value": "1 dormitorio"
    },
    {
      "label": "Antiguedad",
      "value": "54 años"
    },
    {
      "label": "Baños",
      "value": "1 baño"
    },
    {
      "label": "Ambientes",
      "value": "3 ambientes"
    }
  ],
  "price": "$ 300.000",
  "description": "<div class=\"section-description--content\">\n                Departamento en Alquiler   <br>\n    Dirección: Rufino Ortega 222 Bis   <br>\n    Ofrecemos un departamento de 1 dormitorio, idealmente ubicado para tu comodidad.   <br>\n       <br>\n    Características:   <br>\n    Living Comedor: Espacioso y luminoso.   <br>\n    Cocina Americana: Práctica y funcional.   <br>\n    Baño: Completo y en buen estado.   <br>\n    Dormitorio con Placard: Amplio y con buen espacio de almacenamiento.   <br>\n    Lavadero Independiente: Comodidad adicional.   <br>\n    Detalles Adicionales:   <br>\n       <br>\n    Este departamento es ideal para quienes buscan una vivienda cómoda y bien ubicada.   <br>\n     <br>\n   Actualización trimestral por  IPC.   <br>\n \n            </div>",
  "location": {
    "latitude": "-32,981003",
    "longitude": "-60,62751",
    "text": "Barrio Industrial, Rosario, Departamento de Rosario, Santa Fe"
  },
  "features": [
    {
      "label": "Cant. Ambientes",
      "value": "3"
    },
    {
      "label": "Cant. Dormitorios",
      "value": "1"
    },
    {
      "label": "Cant. Baños",
      "value": "1"
    },
    {
      "label": "Antiguedad",
      "value": "54"
    }
  ],
  "images": [
    "https://www.argenprop.com/static-content/36558171/a6b9b85c-95dc-4a59-af63-3c990a07b99f_u_medium.jpg",
    "https://www.argenprop.com/static-content/36558171/e154fd14-e6ed-458d-beb5-26af28308aa7_u_medium.jpg",
    "https://www.argenprop.com/static-content/36558171/794fde75-efab-4ab8-b761-f5f5dce012d7_u_medium.jpg"
  ],
  "seller": {
    "name": "PABLO ALLEGRI GESTION INMOBILIARIA Mat. 0230",
    "phone": "https://wa.me/7929933",
    "url": "https://www.argenprop.com/pablo-allegri"
  }
}, // ... Many other property details
]

The scraper extracts an extensive range of property data fields, each serving specific analytical and business purposes:

Output Fields Explained:

1. ID: A unique identifier for the property listing on ArgeProp.com. This field is crucial for:

   • Tracking specific properties over time
   • Avoiding duplicate entries in databases
   • Cross-referencing with the original website

2. URL: The original property page link. Useful for:

   • Verification of extracted data
   • Providing direct access to the listing
   • Tracking data source for compliance

3. Title: The property listing headline, typically containing key information like property type, number of rooms, and location. This helps with:

   • Quick property identification
   • Search and filtering operations
   • Initial property classification

4. Address: The complete property location. Critical for:

   • Geographic analysis and mapping
   • Neighborhood-based searches
   • Location-based pricing studies

5. Details: Structured property specifications including number of bedrooms, bathrooms, square meters, etc. This data enables:

   • Property comparison and filtering
   • Size-based price analysis
   • Feature-based categorization

6. Price: The listing price in Argentine Pesos (ARS) or other currency. Essential for:

   • Market price analysis
   • Budget-based filtering
   • Price trend monitoring
   • Investment calculations

7. Description: The full property description provided by the seller. Valuable for:

   • Understanding property condition and unique features
   • Natural language processing for trend analysis
   • Marketing content research

8. Location: Geographic coordinates or detailed location information. Enables:

   • Map visualization
   • Distance calculations
   • Geographic market segmentation

9. Features: Additional amenities like parking, pool, security, etc. Used for:

   • Premium feature identification
   • Feature-based price correlation
   • Property comparison matrices

10. Images: URLs to property photographs. Important for:

    • Visual property documentation
    • Image-based analysis
    • Marketing material collection

11. Seller: Contact and information about the listing agent or owner. Useful for:

    • Direct communication with property representatives
    • Identifying major property sellers/agencies
    • Building contact databases

Each field serves specific purposes in property analysis, from basic specifications needed for filtering and comparison to advanced features required for comprehensive market research and business intelligence applications.

How to Use: Step-by-Step Implementation

Step 1: Prepare Your URLs Collect the property detail page URLs you want to scrape. Navigate to ArgeProp.com, find properties of interest, and copy their full URLs. Ensure each URL points to a property detail page, not search results or category pages.

Step 2: Configure Your Input Create your JSON configuration file with appropriate settings. For ArgeProp.com, consider using Argentine proxies (AR) for better results. Set max_retries_per_url to 2-3 for optimal reliability without excessive delays.

Step 3: Run the Scraper Execute the scraper with your configuration. The tool will process each URL sequentially, extracting all available data fields.

Step 4: Review and Process Output Once complete, review the extracted data for completeness. The structured output can be directly imported into databases, spreadsheets, or analysis tools.

Best Practices:

• Test with a small URL set first to verify configuration
• Use residential proxies for better success rates
• Avoid scraping too many URLs simultaneously to prevent rate limiting
• Regularly update your URL list to track new properties
• Store outputs with timestamps for historical tracking

Common Issues and Solutions:

• Missing data fields: Some properties may not have all information available; the scraper handles this gracefully
• Timeout errors: Increase max_retries_per_url or check proxy configuration
• Invalid URLs: Verify URLs point to property detail pages, not search results

Benefits and Real-World Applications

Time Efficiency: Manual data collection from even 50 properties could take 3-4 hours. This scraper completes the same task in minutes, allowing you to focus on analysis rather than data entry.

Practical Applications:

Market Analysis: Real estate agencies can monitor competitor pricing, identify market trends, and adjust their strategies based on comprehensive market data.

Investment Research: Property investors can quickly build databases of available properties, analyze price-per-square-meter ratios, and identify undervalued opportunities.

Trend Monitoring: Data analysts can track how property features correlate with pricing, monitor neighborhood appreciation, and forecast market movements.

Portfolio Management: Property management companies can maintain updated databases of available rentals, benchmark their pricing, and optimize vacancy rates.

Business Value: The structured data enables advanced analytics, supports data-driven decision-making, and provides competitive intelligence that would be nearly impossible to gather manually. The consistent format allows for seamless integration with existing business intelligence tools and CRM systems.

Conclusion: Empower Your Real Estate Operations

The ArgeProp.com Property Details Scraper transforms the time-consuming process of property data collection into an efficient, automated workflow. By providing comprehensive, structured data from Argentina's leading real estate platform, it enables professionals to make faster, more informed decisions based on complete market intelligence.

Whether you're analyzing market trends, building property databases, or conducting competitive research, this scraper provides the data foundation you need. Start automating your property data collection today and gain the competitive advantage that comes from having complete, current market information at your fingertips.

Related Actors

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

Your feedback

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