Programmatic Lead Generation & AI-Driven Attribution Engine
Executive Summary
Engineered a proprietary lead generation system using Make.com and Gemini (LLM) to automate the end-to-end lifecycle of lead acquisition. By implementing a custom data attribution layer, the system transformed a manual, high-cost outreach process into a scalable engine that processed over 3,000 MQLs and identified high-velocity engagement windows, resulting in a 600% lift in processing capacity.
The Challenge: Attribution Gaps and Scaling Friction
Manual Bottlenecks
Lead sourcing was a linear process that drove high operational Cost Per Lead (CPL) and capped daily outreach volume.
Lack of Visibility
Initial data showed no significant trends in lead scores or industry patterns, revealing a critical need for deeper behavioral attribution.
Resource Drain
Manual qualification and outreach required 20+ hours per week, creating an operational barrier to scaling the growth engine.
The Solution: Systems Architecture & Intelligence
Automated Data Pipeline
Built an end-to-end acquisition funnel in Make.com that eliminated manual entry, reducing operational CPL by 60%.
AI-Powered Lead Scoring
Integrated Gemini (LLM) to evaluate 3,068 raw leads, filtering them into a high-precision 12.9% SQL cohort based on custom relevancy logic.
Multi-Branch Distribution
Orchestrated complex workflows using routers and filters to manage content generation and distribution across Slack and Gmail, ensuring human effort remained focused on top-tier prospects.
The Breakthrough: Data Attribution & Optimization
A custom tracking layer monitored response rates by Day-of-Week and Daypart. Analysis of this data drove targeted optimizations that more than doubled engagement.
85% Conversion Concentration
Optimal Dayparting
16% Peak Performance Lift
32.7% Engagement Rate
6x Scale Capacity
Operational ROI
Engagement by Day of Week