Templates / Analyze customer feedback and alert negative sentiment with gpt-5.6-terra and Telegram

Analyze customer feedback and alert negative sentiment with gpt-5.6-terra and Telegram

Ready for 3.0

by Khairul Muhtadin ✓ · 37 views · created 2026-08-12 · Ticket Management, AI Summarization

Ready 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 AI workflow has 26 nodes and runs when an HTTP POST request hits its webhook URL (plus 2 other triggers). Along the way it connects Telegram, Google Sheets, OpenAI Chat Model and Gmail.

How it runs

Trigger: When an HTTP POST request hits its webhook URL (plus 2 other triggers).

  1. Normalize Feedback (Edit Fields (Set)): sets 8 fields: feedback_id, received_at, customer_name…
  2. Read Feedback from Sheets (Google Sheets): uses Google Sheets
  3. Read Analysis from Sheets (Google Sheets): uses Google Sheets
  4. Validate Feedback Input (If): checks a condition and branches into true / false
  5. Summarize Monthly Feedback (AI Agent): runs an AI agent, with model: OpenAI Monthly Model
  6. Filter Last 7 Days (Code): runs custom JavaScript code
  7. Log Feedback to Sheets (Google Sheets): append
  8. Notify Invalid Feedback (Telegram): uses Telegram
  9. Send Monthly Report (Telegram): uses Telegram
  10. Summarize Weekly Feedback (AI Agent): runs an AI agent, with model: OpenAI Weekly Model

…plus 9 more steps. See the full node list below.

Services it uses

TelegramGoogle SheetsOpenAI Chat ModelGmail

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 (10)

From the author

Catch unhappy customers before they leave. This workflow receives feedback via webhook, logs it to Google Sheets, classifies sentiment with OpenAI, and fires a Telegram alert the moment sentiment turns negative. Last updated: September 2026. Quick overview…

Excerpt from Khairul Muhtadin's description on n8n.io.

View the original on n8n.io → Check your own copy

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