An automated lead generation system with web crawling and business intelligence integration

Lead generation remains a resource-intensive process for businesses, requiring manual research and data collection across multiple platforms. This paper presents an automated lead generation system that integrates Google Places API with web crawling capabilities to streamline business prospect identification. The system combines location-based search with automated website crawling to extract business intelligence, implements chain detection algorithms to identify business relationships, and provides comprehensive data management for lead tracking. The architecture employs Django framework with PostgreSQL database for data operations, enabling efficient search execution and result management. The web crawling module processes business websites within 10-15 seconds per location, extracting social media profiles and contact information while respecting robots.txt directives and implementing appropriate rate limiting. System evaluation through 127 comprehensive unit tests validates functional reliability, while real-world testing demonstrates practical viability for systematic business discovery. The implementation addresses key challenges in lead generation including manual research inefficiency, fragmented data collection workflows, and limited business intelligence gathering, providing an integrated solution accessible to businesses of varying sizes.