How it works
How it works This workflow automatically detects completed orders in PostgreSQL and prepares them for AI-based post-purchase communication. It enriches each order with customer, product, and payment data, then generates a personalized message using an AI agent. The message is delivered via email and WhatsApp and finally logged in Google Sheets for tracking and auditing. Step-by-step Step 1: Fetch and prepare completed orders for AI processing** Postgres Trigger – Watches the orders table for updates and initiates the workflow. Postgres (Execute query) – Fetches only orders marked as completed. Split In Batches – Loops through completed orders safely and sequentially. Postgres (Execute query) – Retrieves full customer, product, and payment details using joins. AI Agent – Generates a personalized post-purchase message using order data. Groq Chat Model – Supplies the language model used by the AI agent. Merge – Combines AI-generated text with database results for downstream use. Step 2: Deliver messages and log post-purchase communication** Code – Formats AI output into clean email and WhatsApp message templates. Gmail – Sends the post-purchase email to the customer. WhatsApp – Sends the same message via WhatsApp. Set – Flags email and WhatsApp messages as successfully sent. Google Sheets – Appends customer, order, and communication details. Wait – Pauses before continuing to process the next completed order. Why use this? Automates post-purchase communication with zero manual effort. Ensures consistent, personalized messaging across email and WhatsApp. Adapts message tone automatically based on payment status. Creates a centralized audit log in Google Sheets. Scales easily as order volume grows. An n8n automation workflow template by Avkash Kakdiya.
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