Automated lead generation and hyper-personalized email drafting at scale. From 4 hours of manual work to 20 minutes.
The client was spending 4+ hours daily on lead generation - manually researching prospects, finding contact information, and writing individualized outreach emails. At best, they could reach 15-20 prospects per day, and the quality suffered as fatigue set in.
They needed a way to reach 10x more prospects without sacrificing the personalization that drove their best conversion rates.
I built a Python automation pipeline with three integrated stages that work together seamlessly:
Automated extraction from LinkedIn, company websites, and directories. Contact enrichment and deduplication built in.
LLM-powered email generation that analyzes prospect context and crafts personalized outreach with dynamic templates.
Scheduled sending with rate limiting, bounce handling, and tracking. CSV export for CRM integration.
Pipeline flow: Lead Sources → Scraping → Enrichment → AI Drafting → Review Queue → Scheduled Send
Daily outreach time dropped from 4 hours to 20 minutes - mostly spent reviewing the AI-drafted queue. The personalization quality remained high because the AI analyzed each prospect's context before drafting, something humans struggle to sustain at scale.