Automated Lead Discovery
Differential scraping and automated reporting
> The context
The client was manually monitoring multiple websites looking for new business opportunities. The process was slow, error-prone, and unscalable: new listings were discovered late or missed entirely, directly impacting acquisition capability.
- Manual monitoring of dozens of web pages
- Leads discovered late or missed entirely
- Process neither scalable nor repeatable
> The solution
I designed a differential scraping system that automatically monitors target websites. On each run, the system captures a page snapshot, compares it against the previous one, and identifies new listings. Results are filtered and sent as a structured report via Gmail API. Everything is containerized with Docker Compose and scheduled via cron on a VPS.
- Scraping with Puppeteer and headless Chromium
- Differential comparison based on atomic snapshots
- Automated reports via Gmail API
- Docker Compose deployment on VPS with cron scheduling
> The result
The client receives weekly reports with newly identified leads, without any manual intervention. Time spent on research has been eliminated and response time to new opportunities has increased significantly.
- Complete elimination of manual work
- Automated, structured weekly reports
- Response time reduced from days to hours