Realtor Property Harvester Bulk Property Data Extraction Made Simple Extract live property listings from Realtor.com across multiple cities with customizable filters. Perfect for market analysis, investment research, data analytics, and competitive intelligence. --- ## 🎯 What This Does The Realtor Property Harvester pulls structured property data from Realtor.com based on your search criteria. Get listing details, agent contacts, and pricing information in clean JSON format—ready for analysis or integration. ### Key Capabilities - Multi-City Search - Extract listings from multiple locations simultaneously - Property Type Filtering - Target specific property categories - Flexible Sorting - Order results by price, date, size, or activity - Pagination Control - Fetch multiple pages per city for deep data collection - Status-Based Queries - Filter by for sale, sold, or all listings - Agent Data Included - Get listing agent contact info with every property --- ## 📥 Input Parameters ### Request Structure json { "cities": ["Los Angeles"], "page_count": 1, "property_type": "ANY", "sort_option": "relevant listings", "status": "for_sale" } ### Configuration Options | Parameter | Type | Description | Default | | ---------------- | ---------- | ----------------------------------------------------- | ------------------- | | cities | array | List of cities to scrape (required) | - | | page_count | integer | Number of pages to fetch per city | 1 | | property_type | string | Property category filter | ANY | | sort_option | string | How to order the results | relevant listings | | status | string | Listing status filter | for_sale | --- ## 🏘️ Property Type Options | Value | Description | | ---------------- | ---------------------------------------- | | ANY | All property types | | single_family | Single-family homes | | condo | Condominiums and co-ops | | townhome | Townhouses | | multi_family | Multi-unit residential buildings | | mobile | Mobile/manufactured homes | | farm | Farms and ranches | | land | Vacant land and lots | --- ## 📊 Sort Options | Value | Description | | ---------------------- | ---------------------------------------- | | relevant listings | Default Realtor.com relevance | | highest price | Most expensive first | | lowest price | Least expensive first | | newest | Recently listed properties | | year built | Organized by construction year | | open houses | Properties with scheduled open houses | | price reduced | Recently price-dropped listings | | largest sqft | Biggest properties by square footage | | largest lot | Biggest properties by lot size | | most photos | Listings with extensive photo galleries | --- ## 🏷️ Status Options | Value | Description | | ------------ | ---------------------------------------- | | for_sale | Active listings currently on market | | sold | Recently sold properties | | all | Both active and sold listings | --- ## 📤 Output Structure ### Response Format json [ { "city": "Los Angeles", "data": { "results": [ { "property_id": "1046112528", "property_url": "https://www.realtor.com/realestateandhomes-detail/10644-Bellagio-Rd_Los-Angeles_CA_90077_M10461-12528", "status": "for_sale", "list_price": 190000000, "sold_price": null, "sold_date": null, "beds": 7, "baths": "20", "sqft": null, "type": "single_family", "address": "10644 Bellagio Rd", "city": "Los Angeles", "state": "CA", "postal_code": "90077", "latitude": 34.080184, "longitude": -118.443899, "photo": "https://ap.rdcpix.com/7b45597f98feb75954c47a5af692a1d3l-m3010574789s.jpg", "agent_name": "Jimmy Heckenberg", "agent_phone": "3106501116", "agent_email": "jimmyheck@heckandberghomes.com", "fulfillment_id": "1566815", "office_name": "Rodeo Realty", "list_date": "2025-10-10T16:15:35.000000Z" } ] }, "success": true } ] ### Field Descriptions | Field | Type | Description | | ----------------- | ---------- | -------------------------------------------------- | | property_id | string | Unique property identifier | | property_url | string | Direct link to listing on Realtor.com | | status | string | Current listing status (for_sale, sold, etc.) | | list_price | integer | Current or last listing price | | sold_price | integer | Final sale price (if sold) | | sold_date | string | Date of sale (if applicable) | | beds | integer | Number of bedrooms | | baths | string | Number of bathrooms | | sqft | integer | Interior square footage | | type | string | Property type classification | | address | string | Street address | | city | string | City name | | state | string | State abbreviation | | postal_code | string | ZIP/postal code | | latitude | float | Geographic coordinate | | longitude | float | Geographic coordinate | | photo | string | Primary listing photo URL | | agent_name | string | Listing agent's full name | | agent_phone | string | Agent's phone number | | agent_email | string | Agent's email address | | fulfillment_id | string | Agent's Realtor.com identifier | | office_name | string | Brokerage/office name | | list_date | string | Date property was listed (ISO 8601) | --- ## 💡 Usage Examples ### Example 1: Single City Search json { "cities": ["Miami"], "page_count": 3, "property_type": "condo", "sort_option": "newest", "status": "for_sale" } Result: ~120 condo listings from Miami, sorted by newest first --- ### Example 2: Multi-City Investment Scan json { "cities": ["Austin", "Phoenix", "Tampa"], "page_count": 2, "property_type": "single_family", "sort_option": "lowest price", "status": "for_sale" } Result: ~240 affordable single-family homes across 3 growth markets --- ### Example 3: Luxury Property Research json { "cities": ["Beverly Hills", "Malibu"], "page_count": 5, "property_type": "ANY", "sort_option": "highest price", "status": "for_sale" } Result: ~400 high-end listings sorted by most expensive --- ### Example 4: Recent Sales Analysis json { "cities": ["Seattle"], "page_count": 10, "property_type": "ANY", "sort_option": "newest", "status": "sold" } Result: ~400 recently sold properties with sale prices and dates --- ### Example 5: Motivated Seller Finder json { "cities": ["Denver"], "page_count": 5, "property_type": "single_family", "sort_option": "price reduced", "status": "for_sale" } Result: ~200 properties with recent price reductions --- ## 🎯 Perfect For | Use Case | Configuration | | ------------------------- | ---------------------------------------------------------- | | Market Analysis | Multiple cities, all types, high page count | | Investment Scouting | Single city, specific type, sort by lowest price | | Comp Research | Target area, sold status, recent listings | | Lead Generation | High page count to capture agent contacts | | Price Monitoring | Price reduced sort, frequent scraping | | New Listing Alerts | Newest sort, low page count, daily runs | --- ## ⚡ Performance Specs | Metric | Specification | | --------------------------- | ------------------------------ | | Properties per Page | ~40 listings | | Max Cities per Request | Unlimited (practical: 10-20) | | Max Pages per City | 100+ pages available | | Response Time | 4-8 seconds per city | | Data Freshness | Real-time from Realtor.com | | Agent Contact Rate | 95%+ of listings include agent | --- ## 🔧 Pro Tips Tip #1: Multi-City Efficiency Request 5-10 cities at once with page_count: 2-3 for broad market snapshots. Tip #2: Deep Dives For single city analysis, use page_count: 10+ to get hundreds of listings. Tip #3: Fresh Listings Combine sort_option: "newest" with daily scraping to catch new properties immediately. Tip #4: Sold Comps Use status: "sold" with recent date sorting to build comparable sales databases. Tip #5: Agent Prospecting High page counts = more unique agent contacts for outreach lists. Tip #6: Price Drops sort_option: "price reduced" reveals motivated sellers for negotiation opportunities. --- ## 📊 Output Processing ### Typical Results per Configuration 1 city × 1 page = ~40 properties 1 city × 5 pages = ~200 properties 3 cities × 3 pages = ~360 properties 10 cities × 2 pages = ~800 properties ### Data Export Options - JSON - Native format, ready for APIs and databases - CSV - Flatten for Excel, Google Sheets, or BI tools - Database - Direct import to PostgreSQL, MySQL, MongoDB - CRM - Map fields to Salesforce, HubSpot, or custom CRMs --- ## 🚀 Common Workflows Workflow 1: Daily New Listing Monitor Input: Target cities, newest sort, page_count: 1, status: for_sale Schedule: Daily at 8am Output: Fresh listings for immediate follow-up Workflow 2: Weekly Market Report Input: 5 metro areas, all types, page_count: 5, status: for_sale Schedule: Every Monday Output: 1,000+ listings for trend analysis Workflow 3: Investment Deal Finder Input: Growth markets, single_family, price reduced sort, page_count: 3 Schedule: Twice weekly Output: 240+ potential deals with motivated sellers --- ## 🔐 Data Quality ✓ Live Data - Directly from Realtor.com, not cached ✓ Complete Profiles - Property details + agent contact info ✓ Accurate Pricing - Current list prices and sale histories ✓ Geographic Precision - Lat/long coordinates for mapping ✓ Photo URLs - Direct links to listing images --- ## 🌟 Why Choose This Tool? | Advantage | Benefit | | ---------------------- | ---------------------------------------------------- | | Simple Input | Just specify cities and preferences | | Structured Output | Clean JSON ready for any workflow | | Agent Data | Contact info included automatically | | Flexible Sorting | Find exactly what you need | | Scalable | 1 city or 100 cities, same easy process | | No Rate Limits | Batch process without throttling | --- Transform Realtor.com into your personal property data pipeline.