Faster Client Insights
The platform enabled agents to gather actionable customer data in real-time, reducing time spent manually searching multiple sources.
Technologies used
Golang
Webloop
Vue.js
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
Challenge 01
Website Restrictions and Privacy Policies
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.
#1
Challenge 02
JavaScript Rendering and Resource-Intensive Pages
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.
#2
Challenge 03
Data Matching and Aggregation Complexity
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.
#3
Our approach
Bypassing Privacy Restrictions
We developed algorithms to simulate normal user behavior, combined with proxy rotation and multiple accounts, to bypass detection and prevent bans, ensuring continuous and reliable data collection.
Leveraging Golang and WebLoop for Scalability
Golang was used for its multithreading and concurrency capabilities. WebLoop enabled efficient JavaScript rendering, allowing the scraper to process modern dynamic websites without failures, even on resource-intensive pages.
Intelligent Data Matching
An initial ML-assisted algorithm helped match records across websites, reducing manual effort. The system evaluated similarities in usernames, emails, and other fields, allowing agents to manually verify only the most ambiguous cases.
Phased Development
The project was developed in stages: pre-alpha scripts for initial scraping, alpha integration into a single system, and MVP 1.0 featuring a Vue.js dashboard and basic matching functionality. Feedback from the client guided subsequent improvements.
Facing the same challenge?
Bring your complexity. We'll bring the plan. Tell us about your project and we'll get back within one business day.
Inquire for more infoSolution
01
Web Scraping Engine
Collects detailed customer data in real-time from platforms like Yelp, TripAdvisor, Facebook, and Airbnb, including reviews, locations, work information, and social mentions. Handles modern JavaScript-heavy pages efficiently.
Key capabilities:
- Real-time data scraping from multiple platforms
- JavaScript rendering with WebLoop
- Proxy rotation and multi-account support
- Error handling and retries for blocked requests
02
Data Matching and Aggregation
Intelligently matches and aggregates records across platforms, associating multiple mentions of the same person into a single enriched profile. Supports partial manual verification for higher accuracy in ambiguous cases.
Key capabilities:
- ML-assisted data matching
- Partial manual verification
- Handling of common names and ambiguous records
- Profile enrichment with aggregated information
03
Interactive Dashboard
Displays all matched and aggregated customer data in an intuitive, user-friendly interface. Agents can quickly explore profiles, filter and search leads, and view aggregated statistics for decision-making.
Key capabilities:
- Vue.js-based interactive UI
- Visual display of customer details and sources
- Search and filter functionality
- Real-time updates as new data is collected
04
Privacy Compliance and Security
Ensures that data collection respects privacy regulations while still enabling effective aggregation and profiling for business purposes. Maintains compliance with Northern California data privacy laws.
Key capabilities:
- 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
Results & business impact
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.
