Real Estate Market Research Agent An autonomous Apify actor that generates comprehensive real estate market research reports by analyzing data from multiple authoritative sources. ## 🤖 Autonomous Capabilities The agent operates through a series of autonomous modules, each handling specific aspects of market research: 1. Search Agent - Autonomously discovers relevant market research URLs - Filters and validates sources based on authority and relevance - Supports major real estate platforms (Zillow, Redfin, Realtor.com) 2. Data Extraction Agent - Scrapes market data from validated sources - Handles different page structures and data formats - Memory-efficient crawling with residential proxy support 3. Market Analysis Agent - Validates and normalizes price data - Detects high-cost markets automatically - Calculates key metrics with outlier detection - Cross-references data points for accuracy 4. Newsletter Generation Agent - Creates professional market reports using AI - Formats data in a consistent, readable structure - Provides actionable insights and recommendations - Includes source citations and data comparisons ## 💡 Strategic Advantages of Domain-Specific Approach This agent focuses on real estate market research for several strategic reasons: 1. Data Quality Assurance - Real estate platforms provide structured, verifiable data sources - Metrics can be cross-validated across multiple authoritative sources - Numerical data extraction demonstrates more technical complexity than text-only scraping 2. Showcasing Apify's Core Strengths - Leverages Apify's powerful scraping capabilities for complex websites - Demonstrates handling of sophisticated anti-bot measures on real estate sites - Utilizes residential proxies to access geo-restricted market data 3. Business Value & Market Need - Real estate professionals require accurate, timely market data - Consumers need unbiased analysis from multiple sources - Investment decisions rely on comprehensive market information 4. Technical Differentiation - More challenging extraction tasks requiring precise numerical data - Complex validation rules and outlier detection - Domain-specific knowledge integration for analysis - Transformation of raw data into actionable business insights While general newsletters can be created with many platforms, real estate market analysis specifically leverages Apify's unique advantages in structured data extraction from complex sources. ## 💰 Pay-Per-Event Pricing The actor uses a transparent pay-per-event pricing model: - Search initialization: $0.02 - URL processing: $0.02 per valid URL - Data extraction: $0.02 per source - Market analysis: $0.02 per source - Newsletter generation: $0.50 Total cost per run: $0.72 - $0.80 (depending on number of sources) ## 🚀 Input Parameters json { "location": "City, State", "debug": false } ## 📊 Output Format json { "location": "City, State", "filtered_urls": { "zillow": "url", "redfin": "url", "realtor": "url" }, "market_data": { // Raw extracted data from each source }, "analysis": { "metrics": { // Processed market metrics }, "source_urls": { // Source attribution } }, "newsletter": "Formatted markdown report" } ## 🔧 Technical Requirements - Python 3.13+ - OpenAI API key - Apify Platform account - Residential proxy access (provided by Apify) ## 🛠️ Environment Variables Required: - APIFY_TOKEN: Your Apify API token - OPENAI_API_KEY: Your OpenAI API key ## 📝 Newsletter Format The generated newsletter includes: - Executive Summary - Market Overview - Market Data Comparison - Price Analysis - Market Activity - Market Forecast - Recommendations - Additional Resources ## 🏗️ Architecture The actor is built with a modular architecture: src/ ├── agents/ │ ├── search_agent.py │ ├── extraction_agent.py │ ├── analysis_agent.py │ └── newsletter_agent.py ├── models/ │ └── schemas.py ├── utils/ │ └── url_patterns.py └── main.py ## 📈 Validation & Error Handling - Price validation ranges adjust automatically for high-cost markets - Outlier detection in price and market metrics - Comprehensive error logging and state tracking - Graceful handling of missing or invalid data ## 🔄 Continuous Updates The agent automatically: - Updates search patterns for current year - Validates data freshness - Adapts to source website changes - Handles new market conditions ## 📚 Usage Example python from apify_client import ApifyClient # Initialize the client client = ApifyClient('YOUR_API_TOKEN') # Run the actor run = client.actor('username/real-estate-market-research').call(run_input={ 'location': 'San Jose, CA' }) # Get results output = client.dataset(run['defaultDatasetId']).list_items().items[0] print(output['newsletter']) ## 🤝 Contributing Contributions are welcome! Please read our contributing guidelines and submit pull requests. ## 📄 License This project is licensed under the MIT License - see the LICENSE file for details.