Monitor customer risk and AI feedback using PostgreSQL, Gmail and Discord

How it works This workflow monitors customer health by combining payment behavior, complaint signals, and AI-driven feedback analysis. It runs on daily and weekly schedules to evaluate risk levels, escalate high-risk customers, and generate structured product insights. High-risk cases are notified instantly, while detailed feedback and audit logs are stored for long-term analysis.

Step-by-step - Step 1: Triggers & mode selection - Daily Risk Check Trigger – Starts the workflow on a daily schedule. - Weekly schedule1 – Triggers the workflow for weekly summary runs. - Edit Fields3 – Sets flags for daily execution. - Edit Fields2 – Sets flags for weekly execution. - Switch1 – Routes execution based on daily or weekly mode.

- Step 2: Risk evaluation & escalation - Fetch Customer Risk Data – Pulls customer, payment, product, and complaint data from PostgreSQL. - Is High Risk Customer? – Evaluates payment status and complaint count. - Prepare Escalation Summary For Low Risk User – Assigns low-risk status and no-action details. - Prepare Escalation Summary For High Risk User – Assigns high-risk status and escalation actions. - Merge Risk Result – Combines low-risk and high-risk customer records. - Send a message4 – Sends the customer risk summary via Gmail. - Send a message5 – Sends the same risk summary to Discord. - Code in JavaScript3 – Appends notification status and timestamps. - Append or update row in sheet3 – Logs risk evaluations and notification status in Google Sheets.

- Step 3: AI feedback & reporting - Get row(s) in sheet1 – Fetches customer records for feedback analysis. - Loop Over Items1 – Processes customers one by one. - Prompt For Model1 – Builds a structured prompt for product feedback analysis. - HTTP Request1 – Sends data to the AI model for insight generation. - Code in JavaScript – Merges AI feedback with original customer data. - Append or update row in sheet – Stores AI-generated feedback in Google Sheets. - Wait1 – Controls execution pacing between records. - Merge1 – Prepares consolidated feedback data. - Send a message1 – Emails the final AI-powered feedback report.

Why use this? - Detect customer churn risk early using payment and complaint signals - Automatically escalate high-risk customers without manual monitoring - Convert raw customer issues into executive-ready product insights - Keep a complete audit trail of risk, feedback, and notifications - Align support, product, and leadership teams with shared visibility