Built a GTM automation pipeline to enrich company data from CSV files, qualify leads using rules, and notify sales instantly when high-value companies are detected.
Pipeline snapshot
Manual research
Removed
Firmographic lookup automated end-to-end.
Qualification
Rules
Headcount > 50 flagged as high-value.
Sales alerts
Instant
Email notification triggered automatically.
In this video, I walk you through a mini GTM engineering automation project I built to enrich a list of companies from a CSV file and notify our sales team via email when a company qualifies as a lead.
The goal: take raw company lists, enrich them automatically, qualify them by rules, store clean outputs, and alert sales instantly.
Sales needed a faster, scalable way to evaluate B2B leads from raw company lists. Manual research for size, industry, and relevance delayed outreach and wasted time.
Design an automated workflow to enrich company data at scale, apply qualification logic, store results in a structured file, and notify sales in real time when a company meets outreach criteria.
Built a Zapier-based pipeline triggered by CSV uploads in Google Drive. Each run parses company names/domains, calls the AbstractAPI Company Enrichment API via webhook to retrieve firmographics (industry, LinkedIn, headcount), normalizes results, writes output into Google Sheets / Excel, and flags companies using rules (headcount > 50). When qualified, an automatic email notification is sent to sales for immediate follow-up.
Manual research was eliminated and lead qualification became consistent and scalable. Sales was notified instantly for qualified companies, reducing time to outreach and improving focus on high-value opportunities. The system created a reusable GTM foundation that can be extended with new enrichment sources or rules.