Coldwell Banker Property Search Scraper: Extract US Real Estate Market Data

Why Coldwell Banker Data Matters for Real Estate Intelligence

Coldwell Banker is one of the most established real estate brands in the United States, with over 115 years of market presence and thousands of offices nationwide. The platform aggregates property listings across multiple MLS (Multiple Listing Service) systems, making it a comprehensive source for understanding local and national real estate markets.

For real estate investors, market analysts, and property researchers, Coldwell Banker's data provides crucial insights into pricing trends, inventory levels, property characteristics, and market velocity. However, manually collecting data from hundreds of listings across different cities is impractical. This scraper automates that process, delivering structured data ready for analysis, visualization, or integration into investment decision tools.

Scraper Capabilities and Target Users

This scraper extracts comprehensive property information from Coldwell Banker's search results and city pages. It captures both basic listing details and market-specific metadata including MLS identifiers, days on market, and coming soon indicators that signal market dynamics.

The tool serves real estate investors analyzing markets for acquisition opportunities, appraisers building comparable property databases, market researchers tracking pricing trends and inventory levels, and property data aggregators building comprehensive real estate databases. It handles both residential and commercial property types across all US markets where Coldwell Banker operates.

Input Configuration Explained

The scraper accepts city-level search URLs from Coldwell Banker. These URLs follow the pattern https://www.coldwellbanker.com/city/[state]/[city-name] and display property search results for that location.

Input Parameters:

{
  "proxy": {
    "useApifyProxy": false
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [
    "https://www.coldwellbanker.com/city/fl/hallandale-beach"
  ]
}

Example Screenshot:

Proxy configuration: Residential US proxies are recommended as they mimic legitimate user behavior and reduce blocking risk. Using US-based proxies is particularly important for real estate sites that may restrict international access.

max_items_per_url: Controls how many properties to scrape per URL. Set to 20 by default for testing, but can be increased to extract complete market data (typically 50-500+ properties per city depending on inventory).

ignore_url_failures: When true, the scraper continues processing remaining URLs even if some fail. Useful when scraping multiple cities where some URLs might be temporarily unavailable.

URLs array: Include multiple city URLs to scrape properties across different markets in a single run. Each URL will be processed sequentially up to the max_items_per_url limit.

Output Structure and Field Descriptions

The scraper returns JSON data with each property as a structured object containing identification, pricing, specifications, and market metadata.

Core Identification Fields:

Listing Master ID - Unique identifier for the property listing, critical for deduplication and tracking listings across time. MLS ID - Multiple Listing Service identifier used by real estate professionals for cross-referencing with official MLS databases. Property Address - Complete street address for geocoding, mapping, and location analysis.

Visual Assets:

Photos - Array of image URLs showcasing the property. Essential for visual verification, marketing materials, or training computer vision models for property assessment.

Pricing Information:

Price - Current listing price in USD, the primary metric for comparative market analysis. Marker Price - Display price that may differ from actual price during negotiations or special conditions. Hide Price - Boolean indicating if the seller has chosen to hide the price publicly (common for luxury properties or pocket listings).

Property Specifications:

Beds - Number of bedrooms, critical for property categorization and comparable analysis. Baths - Number of bathrooms (typically includes half-baths), another key specification metric. Square Feet - Total livable area, essential for calculating price per square foot and comparing similar properties. Property Type Value - Classification such as Single Family, Condo, Townhouse, Land, or Commercial, enabling segmentation by property category.

Market Status and Timing:

Standard Status - MLS status code (Active, Pending, Sold, Coming Soon, etc.) indicating the property's current market position. Days on Market - Number of days since listing, a key velocity metric indicating demand and pricing accuracy. Is Coming Soon - Boolean flag for pre-market listings, valuable for identifying opportunities before public availability. Last Change Date - Timestamp of the most recent listing update, useful for tracking price changes or status updates.

Additional Metadata:

Disclaimer Attribution - Legal attribution text required by MLS rules, important for compliance when republishing data. GIS - Geographic Information System data, typically containing latitude/longitude coordinates for mapping. Is Virtual Tour Available - Boolean indicating if 3D walkthrough or virtual tour exists, a feature increasingly important in modern real estate. Property Details Route Path - URL path to the full property details page for accessing additional information not captured in search results.

Example Output:

[
  {
  "listing_master_id": "P00800000H2uq9dQY3zO90lWSVVVhra7RrYFrSqs",
  "photos": [
    {
      "index_num": 0,
      "media_url": "https://images-listings.coldwellbanker.com/SEFMLS/A1/19/18/61/0/_P/A11918610_P00.jpg",
      "is_portrait": true
    }
  ],
  "property_address": "1904 S Ocean Dr #508, Hallandale Beach, FL 33009",
  "price": "$630,000",
  "marker_price": 630000,
  "beds": 2,
  "baths": 2,
  "square_feet": "1,440",
  "property_type_value": "Condo",
  "standard_status": "ACTIVE",
  "mls_id": "A11918610",
  "days_on_market": 0,
  "is_coming_soon": false,
  "disclaimer_attribution": {
    "disclaimer": "Information deemed reliable but not guaranteed. Information is provided, in part, by Greater Miami MLS. This information being provided is for consumer's personal, non-commercial use and may not be used for any other purpose other than to identify prospective properties consumers may be interested in purchasing."
  },
  "last_change_date": "2025-12-10T17:52:30.681Z",
  "gis": {
    "latitude": 25.9822473,
    "longitude": -80.1188343
  },
  "is_virtual_tour_available": false,
  "property_details_route_path": "/fl/hallandale-beach/1904-s-ocean-dr-apt-508s/lid-P00800000H2uq9dQY3zO90lWSVVVhra7RrYFrSqs",
  "hide_price": false,
  "from_url": "https://www.coldwellbanker.com/city/fl/hallandale-beach"
}
]

How to Use the Scraper Effectively

Create an Apify account and locate the Coldwell Banker Property Search Scraper. Identify target markets by browsing Coldwell Banker's city pages or using their search functionality to find relevant locations. Copy the complete city page URLs.

Configure your input JSON with the URLs and adjust max_items_per_url based on your needs. For comprehensive market analysis, set this to a high number (200-500) to capture most available inventory. For quick sampling or testing, 20-50 properties per city is sufficient.

Start the scraper and monitor progress through the Apify console. Processing time scales with the number of properties: expect 5-10 minutes for 100 properties. Once complete, download your data in JSON for database integration or CSV for spreadsheet analysis.

For regular market monitoring, schedule recurring runs (daily or weekly) to track new listings, price changes, and inventory trends over time. Compare datasets across time periods to identify market shifts.

Practical Applications and Use Cases

Investment Analysis: Build comparable property databases for specific neighborhoods or property types. Calculate average price per square foot, identify underpriced opportunities, and analyze market segmentation by property characteristics.

Market Research: Track inventory levels across different cities to identify hot and cold markets. Monitor days on market trends to gauge demand intensity. Analyze coming soon listings to identify markets with strong future supply.

Appraisal Support: Create automated comparable property reports by filtering for similar beds, baths, square footage, and location. Track recent sales (by monitoring status changes from Active to Sold) to update valuation models.

Price Monitoring: For targeted properties or markets, scrape regularly to detect price reductions or increases, signaling seller motivation or market strength respectively.

Geographic Analysis: Use GIS coordinates to map property distributions, identify clustering patterns, and perform spatial analysis like proximity to amenities or schools.

Best Practices for Data Collection

Set realistic max_items_per_url values. Most cities have 50-200 active listings, while major metros may have 1000+. Sample first to understand typical inventory levels, then adjust accordingly.

Schedule regular scrapes rather than one-time extraction. Real estate markets change daily with new listings, status updates, and price changes. Weekly or bi-weekly scraping captures these dynamics effectively.

Implement data validation checks: verify prices are reasonable, square footage is positive, and coordinates fall within expected geographic boundaries. Flag anomalies for manual review.

Store historical data to enable time-series analysis. Track individual properties across scrapes using Listing Master ID to identify price changes, status transitions, and time on market accurately.

Respect rate limits by spacing out scrapes and avoiding excessive concurrent requests. Use appropriate proxy rotation to distribute load and maintain access reliability.

Conclusion

The Coldwell Banker Property Search Scraper provides systematic access to one of America's largest real estate listing networks. Whether conducting investment analysis, market research, or building property databases, this tool delivers structured, actionable data from a trusted real estate source.