Built a GTM automation pipeline to enrich company data from CSV files, qualify leads based on business rules, and notify sales instantly when high-value companies are detected.
The sales team needed a faster and more scalable way to evaluate potential B2B leads from raw company lists. Manual research to understand company size, industry, and relevance was time-consuming and delayed outreach opportunities.
My responsibility was to design an automated GTM workflow that could enrich company data at scale, apply lead qualification logic, store structured results, and notify sales teams in real time when a company met outreach criteria.
I designed and implemented a Zapier-based GTM automation workflow that processes companies individually from a CSV file uploaded to Google Drive. Each workflow run parses company names and domains, then calls the AbstractAPI Company Enrichment API via webhook to retrieve firmographic data such as industry, LinkedIn URL, and headcount.
Using Zapier utilities and looping logic, each company is enriched, normalized, and written into a structured Google Sheets / Excel file for visibility and future use. I implemented a qualification rule based on headcount, where companies with more than 50 employees were automatically flagged as high-value leads. When this condition was met, the workflow triggered an automatic email notification to the sales team, enabling immediate follow-up.
The full step-by-step implementation, workflow logic, and architecture are documented and attached for reference.
The automation eliminated manual company research and enabled consistent, rules-based lead qualification at scale. Sales teams were notified instantly when a qualified company was detected, significantly reducing time to outreach and improving focus on higher-value opportunities. The system created a reusable GTM foundation that can easily be extended with new enrichment sources or qualification rules.