YouTube Creator Contact Discovery Automation
API-enhanced and Selenium-powered automation system that discovers niche-based YouTube creators daily and extracts verified contact emails into PostgreSQL. Client needed a scalable system to discover active U.S.-based YouTube creators under 1,000 subscribers producing niche content and automatically extract contact emails for outreach
Daily Videos Processed
Extraction Speed
Monthly Maintenance
Automation Level
Client needed a scalable system to discover active U.S.-based YouTube creators under 1,000 subscribers producing niche content and automatically extract contact emails for outreach.
Built a hybrid automation engine combining headless Selenium for dynamic rendering and Python requests-based extraction with rotating proxies and PostgreSQL storage.
After implementation, Fully automated creator discovery pipeline that scans thousands of daily uploads and stores verified contact emails in PostgreSQL.
Behind the Scenes
How the system moved from problem to controlled execution.
Problem
Client needed a scalable system to discover active U.S.-based YouTube creators under 1,000 subscribers producing niche content and automatically extract contact emails for outreach. No native YouTube API endpoint for reliable email extraction. Email visibility in About section triggers CAPTCHA and account limits. Daily requirement to scan ~5,000 newly uploaded videos. Need to filter creators by niche relevance (documentary, true crime, tutorials, etc.).
System Built
Built a hybrid automation engine combining headless Selenium for dynamic rendering and Python requests-based extraction with rotating proxies and PostgreSQL storage. Workflow covered: PostgreSQL database setup on VPS with keyword-driven architecture; Keyword + search_results_limit + sort_by stored in database; Headless Selenium performs keyword-based YouTube searches (Upload Date, Relevance, Views, Rating); Scroll and extract video URLs dynamically; Switch to high-speed requests module for video & channel data extraction.
What Changed
5,000 videos processed daily (initial configuration). 1 req/sec optimized hybrid extraction speed. 0 monthly maintenance required (except VPS cost). 100% fully automated daily execution via CRON. Designed scalable keyword-driven architecture (fully database-controlled). Built hybrid bot: dynamic UI scraping + static HTTP extraction.
Before / After
What changed after the system was rebuilt.
Daily video processing
Before
Manual discovery
After
5,000 videos automated
Extraction speed
Before
~12 videos/minute
After
1 req/sec (60/min)
Maintenance
Before
Ongoing manual work
After
0 monthly maintenance
Email discovery
Before
No scalable solution
After
Automated regex-based extraction
Delivery Scope
What was included in the system delivery.
Hybrid YouTube creator discovery automation
PostgreSQL keyword-driven configuration
Email extraction and fallback parsing logic
Daily CRON execution workflow
Structured storage for found and not-found email records
Controls
Checks built in to keep the workflow reliable.
Duplicate prevention based on channel URL
Only channels with found emails are stored in the main outreach table
Proxy rotation and cooldown logic reduce throttling risk
Run summaries are logged for operational visibility
Keywords and limits are controlled from the database
Tools & Stack
Tools used to build, connect, and deliver this system
Similar System
Want similar results?
Share the manual process, messy data flow, or system gap you want to fix. We will help you understand what can be rebuilt into a controlled operating system.