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LoopNet Property Details Scraper: Extract Commercial Real Estate Data for Investment Analysis

Introduction

LoopNet.com stands as North America's premier online marketplace for commercial real estate, hosting millions of property listings including office buildings, retail spaces, industrial facilities, land parcels, and multifamily properties. As the industry's most comprehensive platform, LoopNet connects buyers, sellers, tenants, and brokers with detailed property information, market data, and transaction opportunities across the United States and Canada.

For commercial real estate investors, brokers, developers, and analysts, accessing detailed property data is essential for investment decisions, market analysis, and competitive intelligence. However, manually collecting property information across multiple listings is time-consuming and inefficient, particularly when conducting large-scale market research or portfolio analysis.

The LoopNet Property Details Scraper automates this data extraction process, enabling systematic collection of property specifications, pricing information, location details, and listing metadata. Whether you're analyzing investment opportunities, tracking market trends, building comp databases, or monitoring competitor portfolios, this scraper transforms hours of manual research into minutes of automated data collection.

Scraper Overview

The LoopNet Property Details Scraper is a specialized data extraction tool designed to systematically collect comprehensive property information from individual LoopNet listing pages. This scraper leverages advanced web automation to navigate property detail pages and extract structured data efficiently and accurately.

The tool offers residential proxy support for reliable data collection from US-based servers, configurable retry mechanisms for handling network issues, and flexible URL-based extraction for targeting specific properties. It's particularly valuable for commercial real estate investors conducting due diligence, brokers building market comp databases, developers researching acquisition targets, and analysts tracking property market dynamics.

The scraper maintains high data accuracy while implementing best practices for ethical web scraping, including proper rate limiting and error handling to ensure stable, long-term data collection capabilities.

Input and Output Details

Input and Output Specifications

Example url 1: https://www.loopnet.com/Listing/132-Sion-St-Manchester/38449703/

Example url 2: https://www.loopnet.com/Listing/9-11-Schofield-St-Manchester/38433545/

Example url 3: https://www.loopnet.com/Listing/Lilford-Rd-London/33769868/

Example Screenshot of property information page:

Input Format

The scraper accepts a JSON configuration for precise control over the extraction process:

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  },
  "urls": [
    "https://www.loopnet.com/Listing/Lilford-Rd-London/33769868/",
    "https://www.loopnet.com/Listing/132-Sion-St-Manchester/38449703/"
  ],
  "max_retries_per_url": 2,
  "ignore_url_failures": true
}

The urls parameter: Add the URLs of specific property detail pages you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. Each URL should be a complete LoopNet property listing page (e.g., https://www.loopnet.com/Listing/[Property-Address]/[ID]/).

The max_retries_per_url parameter: Limit the number of retries for each URL if the scrape is detected as a bot or the page fails to load. The default value is 2, balancing thoroughness with efficiency.

The ignore_url_failures parameter: If set to true, the scraper continues running even if some URLs fail after maximum retries. This ensures one problematic property listing doesn't stop your entire data collection job.

The proxy parameter: Proxy configuration is essential for avoiding bot detection. For LoopNet, use US residential proxies (apifyProxyCountry: "US") for optimal access and reliability, as the platform primarily serves North American properties.

Output Format

Example ouput:

[
  {
  "offers": [
    {
      "price": "Upon Request",
      "price_currency": "USD",
      "price_specification": {
        "price": "Upon Request",
        "price_currency": "USD",
        "@type": "PriceSpecification"
      },
      "availability": "https://schema.org/InStock",
      "@type": "Offer",
      "name": "Rental Rate ($/SF/YR)"
    }
  ],
  "provider": [
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/iolo-morgan/ehcvw2nb/33769868#RealEstateAgent",
      "name": "Iolo Morgan",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/xRpJIjop6O7AB-j3_FhBgiwHU1et_WFrMgNBkEgSzrg/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/xRpJIjop6O7AB-j3_FhBgiwHU1et_WFrMgNBkEgSzrg/106/image.jpg"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/tessa-english/5f1s7fmb/33769868#RealEstateAgent",
      "name": "Tessa English",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/RAD3rCrj0bOjlFvqDqYE8Ku9-Bbmw-fdeSW0P5_yVS0/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/RAD3rCrj0bOjlFvqDqYE8Ku9-Bbmw-fdeSW0P5_yVS0/106/image.jpg"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/nick-steens/963wrz4b/33769868#RealEstateAgent",
      "name": "Nick Steens",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/x7f4UVdSVsw0O9TYtdjtCbFEGDFtzc-FucZoxKqC3I4/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/x7f4UVdSVsw0O9TYtdjtCbFEGDFtzc-FucZoxKqC3I4/106/image.jpg"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/bridget-outtrim/4514xvkb/33769868#RealEstateAgent",
      "name": "Bridget Outtrim",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/Cf5PRd2kITBfBwRQimf1TG1CoGwaVwFLwYGSVqbOjwc/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/Cf5PRd2kITBfBwRQimf1TG1CoGwaVwFLwYGSVqbOjwc/106/image.jpg"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/annabel-dalby/js59hl7b/33769868#RealEstateAgent",
      "name": "Annabel Dalby",
      "image": {
        "@type": "ImageObject",
        "@id": "/content/images/user/no-broker-photo.png?v=8a41cc887b28f0c6fd88e1322ee17b08#primaryImage",
        "url": "/content/images/user/no-broker-photo.png?v=8a41cc887b28f0c6fd88e1322ee17b08"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/james-coggle/8g7e461b/33769868#RealEstateAgent",
      "name": "James Coggle",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/ZjRoR-LcppW1D-La2qcZSNoVud6gOzVaKUHIHOHJ8CA/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/ZjRoR-LcppW1D-La2qcZSNoVud6gOzVaKUHIHOHJ8CA/106/image.jpg"
      }
    },
    {
      "address": {
        "address_locality": "London",
        "address_region": "LND",
        "@type": "PostalAddress"
      },
      "member_of": {
        "@type": "Organization",
        "name": "BNP"
      },
      "@type": "RealEstateAgent",
      "@id": "https://www.loopnet.com/commercial-real-estate-brokers/profile/peter-davidson/q71jm4yb/33769868#RealEstateAgent",
      "name": "Peter Davidson",
      "image": {
        "@type": "ImageObject",
        "@id": "https://images1.loopnet.com/i2/w9rxcUDd3YvLkDq66ohEX7pVMKlEEo2dMX87DxbCDTE/106/image.jpg#primaryImage",
        "url": "https://images1.loopnet.com/i2/w9rxcUDd3YvLkDq66ohEX7pVMKlEEo2dMX87DxbCDTE/106/image.jpg"
      }
    }
  ],
  "date_modified": "2026-01-05",
  "content_location": {
    "same_as": [],
    "address": {
      "address_country": "GB",
      "address_locality": "London",
      "postal_code": "SE5 9HR",
      "street_address": "Lilford Rd",
      "@type": "PostalAddress",
      "@id": "https://www.loopnet.com/place/London-SE5 9HR/#place"
    },
    "@type": "Place"
  },
  "is_part_of": [
    {
      "@type": "CollectionPage",
      "@id": "https://www.loopnet.com/search/industrial-space/united-kingdom/for-lease/#CollectionPage"
    }
  ],
  "context": null,
  "type": null,
  "id": null,
  "name": "Bloom Camberwell | London SE5 9HR - 3,575 - 36,275 SF of Industrial  Space Available",
  "description": "Laid out over two parallel terraces with an open central courtyard, Bloom Camberwell is a new, cutting-edge industrial site with units fitted out to the highest specification while offering businesses a prime location in South London. This best-in-class development comprises eight purpose-built warehouse units totaling 52,495 square feet, with units ranging from 3,575 to 10,030 square feet.",
  "url": "https://www.loopnet.com/Listing/Lilford-Rd-London/33769868/",
  "image": "https://images1.loopnet.com/i2/80pJZ6YDgLmBAKBWUJBTvtW2NuLkGK_klQaRF__bOAQ/112/image.jpg",
  "additional_property": [
    {
      "value": [
        "36,275 SF"
      ],
      "@type": "PropertyValue",
      "name": "Total Space Available"
    },
    {
      "value": [
        "10,170 SF"
      ],
      "@type": "PropertyValue",
      "name": "Max. Contiguous"
    },
    {
      "value": [
        "Industrial Park"
      ],
      "@type": "PropertyValue",
      "name": "Park Type"
    }
  ]
}
]

The scraper returns structured property data with each field serving specific purposes for real estate analysis:

• Offers: Property offering details including sale price, lease rates, and transaction terms. Critical for financial analysis, investment evaluation, and pricing comparisons across comparable properties.

• Provider: Listing broker or agency information. Essential for broker contact, relationship building, and understanding market representation patterns.

• Date Modified: Last modification timestamp for the listing. Important for tracking listing activity, identifying stale properties, and monitoring market velocity.

• Content Location: Geographic location data including address and coordinates. Fundamental for location analysis, mapping, geographic market segmentation, and proximity-based research.

• Is Part Of: Parent property or portfolio relationship. Useful for identifying multi-property portfolios, related assets, and portfolio-level investment opportunities.

• Context: Additional contextual information about the property or listing. Provides background details that support comprehensive due diligence and market understanding.

• Type: Property type classification (office, retail, industrial, land, multifamily, etc.). Critical for property segmentation, sector-specific analysis, and filtering by investment focus.

• ID: Unique LoopNet listing identifier. Essential for database management, tracking properties over time, and preventing duplicate records in your CRM.

• Name: Property name or address identifier. Primary reference for property identification, communication, and report generation.

• Description: Detailed property description including features, amenities, and highlights. Provides comprehensive property overview for initial screening, marketing materials, and investment summaries.

• URL: Direct link to the property listing page. Reference for accessing full listing details, sharing with stakeholders, and verification of extracted data.

• Image: Property images and visual assets. Valuable for property identification, visual inspection, presentation materials, and initial property assessment.

• Additional Property: Supplementary property specifications including square footage, lot size, building class, year built, parking, zoning, and other technical details. Critical for detailed analysis, valuation modeling, comparison matrices, and investment underwriting.

Each field supports comprehensive commercial real estate workflows including investment analysis, market research, broker prospecting, and portfolio management.

Usage Guide

Setting Up Property Extraction

Step 1: Identify Target Properties

Navigate to LoopNet.com and locate the specific property listings you want to analyze. You can find properties through:

• Property type searches (office, retail, industrial, etc.)
• Geographic searches (city, state, zip code, neighborhood)
• Filtered searches (price range, size, cap rate, etc.)
• Saved searches or portfolio tracking

Copy the complete URL of each property detail page from your browser's address bar.

Step 2: Configure Your Input JSON

Create your input configuration with the property URLs you want to scrape. Add multiple URLs to collect data from different properties in a single run:

{
  "urls": [
    "https://www.loopnet.com/Listing/Property-1/ID1/",
    "https://www.loopnet.com/Listing/Property-2/ID2/",
    "https://www.loopnet.com/Listing/Property-3/ID3/"
  ]
}

Step 3: Configure Proxy Settings

For optimal results with LoopNet:

• Enable Apify proxy with residential proxy groups
• Set apifyProxyCountry to "US" for US residential proxies
• This prevents detection and ensures reliable access to property data

Step 4: Set Error Handling

Configure retry and failure handling:

• Set max_retries_per_url to 2-3 for standard operations
• Enable ignore_url_failures to ensure batch jobs complete even if individual URLs fail
• This is critical when scraping large property portfolios

Best Practices

URL Management:

• Verify each URL loads correctly before adding to batch
• Organize URLs by property type, location, or investment criteria
• Maintain backup lists of URLs as listings may expire
• Track which properties have been successfully scraped

Property Type Organization:

• Group similar property types together for efficient analysis
• Separate URLs by investment strategy (value-add, core, development)
• Tag URLs with custom identifiers for post-processing
• Create systematic naming conventions for output files

Data Collection Strategy:

• Start with smaller batches (10-20 properties) to validate output
• Scale to larger batches once format is verified
• Schedule regular extractions to track listing changes
• Monitor for property status updates (sold, leased, price changes)

Proxy Configuration:

• Always use US residential proxies for LoopNet
• Monitor for access issues and adjust proxy settings if needed
• Implement appropriate delays between requests
• Rotate proxy IPs for large-scale extraction

Common Troubleshooting

Access Issues:

• Verify proxy configuration uses US residential proxies
• Check if URLs are correctly formatted and accessible
• Ensure property listings are still active (not removed)
• Adjust retry settings if experiencing intermittent failures

Data Completeness:

• Verify output contains all expected fields
• Check for properties with incomplete listings
• Cross-reference sample outputs with actual LoopNet pages
• Note that some fields may be empty for certain property types

URL Validation:

• Ensure URLs include complete LoopNet domain and property ID
• Test URLs manually before batch processing
• Remove duplicate URLs from input list
• Verify listing hasn't been removed or relocated

Benefits and Applications

The LoopNet Property Details Scraper dramatically reduces time spent on manual property research. What would require hours of copying data from individual listings is automated into minutes, enabling real estate professionals to focus on analysis and decision-making rather than data entry.

Primary Applications:

Investment Deal Sourcing: Investors can rapidly build databases of potential acquisition targets with complete property specifications, pricing, and broker contact information for systematic deal evaluation and pipeline management.

Market Comparable Analysis: Create comprehensive comp databases for valuation analysis, include detailed property specifications and transaction terms, track pricing trends across similar properties, and support broker price opinions and appraisals.

Portfolio Monitoring: Track competitive properties and market inventory, monitor pricing changes and listing activity, identify market trends and investment opportunities, and maintain current data on target acquisitions.

Broker Prospecting: Build contact databases of active listing brokers, identify high-volume brokers in target markets, analyze broker market share and specializations, and support relationship development for deal flow.

Market Research: Conduct systematic analysis of property supply by type and location, assess pricing trends and cap rate movements, identify emerging markets and investment opportunities, and generate market reports with comprehensive property data.

The scraper provides competitive advantages through:

• Structured extraction of comprehensive property details
• Consistent data format enabling database integration and analysis
• Automated collection eliminating manual data entry errors
• Scalable extraction supporting portfolio-level research
• Regular updates enabling time-series analysis and trend tracking

The structured output integrates with real estate CRM systems, investment analysis tools, and business intelligence platforms, enabling immediate use for underwriting, portfolio management, and strategic planning.

Conclusion

The LoopNet Property Details Scraper transforms manual property research into automated data collection. By providing structured access to North America's largest commercial real estate marketplace, it empowers investors, brokers, and analysts to make data-driven decisions faster and more accurately.

Whether you're building investment pipelines, conducting market analysis, or tracking competitive properties, this scraper delivers the systematic data extraction capabilities needed to accelerate your commercial real estate intelligence gathering.

Ready to streamline your LoopNet property research? Start extracting valuable commercial real estate data today and transform your investment analysis workflow.

Related Actors

• Loopnet Property Search Scraper: A specialized data extraction tool engineered to harvest detailed property information from Loopnet's property marketplace.

Your feedback

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