📌 Project Overview

• Role: Operations Automation Engineer

• Platform: Make.com (Enterprise)

• Stack: Airtable, OpenAI, JSON Parser, Gmail API, Slack API

• Key Outcome: Recovered a projected 30–60% of lost inbound student leads by transforming an education academy’s manual outreach into an instant, 3-phase automated conversion loop.

• 📉 The Challenge

• ⚙️ The Technical Solution & Architecture

Phase 1: Ingestion Bridge (Bridge - Lead Language)

• Core Function: Decentralized Cloud Form & Database Ingestion Engine.
• Technical Milestone: Engineered a lightweight data bridge that monitors inbound student registration payloads from a native Google Form linked to a master Google Sheet ledger. The scenario instantly captures fresh rows, normalizes student contact formats, and writes an uncorrupted single source of truth into an Airtable CRM database, preventing data loss at the absolute first point of user contact.

Phase 2: Intelligent Triage Engine (Main - Lead Language)

• Passed fresh records into an OpenAI text prompt completion model to run sentiment analysis and measure student urgency and experience levels.
• Utilized native JSON parsing modules to cleanly map tokens into structured fields.
• Deployed a multi-branch Router dividing leads by classification state (HOT, WARM, COLD):
  • HOT: Immediately dispatches a personalized intake message via Gmail while firing an urgent Slack alert for manual staff interception.
  • WARM / COLD: Stamps lead classifications into Airtable to prepare rows for systematic secondary workflows.

Phase 3: Lifecycle Nurturing Array & Filter Debugging (Follow-up EMAIL)