Monitor customer risk and AI feedback using PostgreSQL, Gmail and Discord
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This workflow has 23 nodes and runs on a schedule (every day) (plus 1 other trigger). Along the way it connects Google Sheets, Gmail, Postgres and Discord. It also calls api.groq.com over HTTP.
How it runs
Trigger: On a schedule (every day) (plus 1 other trigger).
- Edit Fields (Edit Fields (Set)): sets 1 field: isDaily
- Edit Fields (Edit Fields (Set)): sets 1 field: isWeekly
- Switch: routes items into 2 branches
- Fetch Customer Risk Data (Postgres): run a query
- Get row(s) in sheet (Google Sheets): uses Google Sheets
- Is High Risk Customer? (If): checks a condition and branches into true / false
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- Prepare Escalation Summary For Low Risk User (Edit Fields (Set)): sets 9 fields: customer_id, customer_name, email…
- Prepare Escalation Summary For High Risk User (Edit Fields (Set)): sets 9 fields: customer_id, customer_name, email…
- Merge: merges the data from its input branches
…plus 11 more steps. See the full node list below.
Services it uses
HTTP calls to: api.groq.com
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (13)
- Google Sheets
n8n-nodes-base.googleSheets - HTTP Request
n8n-nodes-base.httpRequest - Code
n8n-nodes-base.code - Gmail
n8n-nodes-base.gmail - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Merge
n8n-nodes-base.merge - Wait
n8n-nodes-base.wait - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - Switch
n8n-nodes-base.switch - Postgres
n8n-nodes-base.postgres - If
n8n-nodes-base.if - Discord
n8n-nodes-base.discord
From the author
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…