All Technologies Used
Motivation
Real estate agents struggle to get complete and accurate client information before signing contracts, wasting time and risking misinformed decisions. Our objective was to create a platform that automates data collection from multiple sources, bypasses privacy restrictions, and aggregates it into reliable customer profiles, reducing uncertainty and improving lead qualification.
Main Challenges
The websites targeted for scraping imposed strict privacy policies and actively monitored abnormal behavior. Detection could result in account or IP bans, making reliable data extraction extremely challenging. Our team had to research user-tracking mechanisms and develop algorithms that mimic normal user behavior to avoid detection.
Modern websites use JavaScript frameworks like React, Angular, and Vue to generate content dynamically, which traditional scrapers cannot handle. Rendering these pages required a dedicated, multithreaded Golang-based engine using WebLoop to efficiently process JavaScript-heavy content without crashing or slowing down the system.
Collected data often contained common names or incomplete profiles, making it difficult to correctly identify the right customer. We implemented intelligent matching algorithms that considered usernames, emails, education info, and natural language similarities, combined with partial manual verification to ensure accurate profiles.
Our Approach
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Web Scraping Engine
- Real-time data scraping from multiple platforms
- JavaScript rendering with WebLoop
- Proxy rotation and multi-account support
- Error handling and retries for blocked requests
Data Matching and Aggregation
- ML-assisted data matching
- Partial manual verification
- Handling of common names and ambiguous records
- Profile enrichment with aggregated information
Interactive Dashboard
- Vue.js-based interactive UI
- Visual display of customer details and sources
- Search and filter functionality
- Real-time updates as new data is collected
Privacy Compliance and Security
- Algorithms to bypass detection without violating laws
- Secure storage of scraped data
- Proxy and account management for anonymous access
- Maintains compliance with Northern California privacy laws
Business Value
Faster Client Insights: The platform enabled agents to gather actionable customer data in real-time, reducing time spent manually searching multiple sources.
Improved Data Accuracy: Intelligent data matching and aggregation increased profile accuracy by up to 70%, ensuring agents had reliable information before client meetings.
Scalability and Performance: Multithreaded Golang engine with WebLoop ensured high-performance scraping even on JavaScript-heavy sites, reducing processing time by 70–90%.
Enhanced Decision-Making: Agents could make informed decisions based on enriched customer profiles, improving lead quality and client engagement.
Reduced Maintenance Costs: Robust scraping algorithms mimicking real user behavior minimized account bans and manual intervention, saving long-term costs.
Customer Satisfaction: The real estate firm received a prototype within three weeks, was impressed by the platform’s capabilities, and viewed Azati as a trusted technology partner.
