Multi-Channel Customer Sentiment Tracker with Real-Time Analytics and Alerting

Go to Workflow
0 views
Built by Cheng Siong Chin Cheng Siong Chin
Created on June 05, 2026

Description

How It Works
Scheduled processes retrieve customer feedback from multiple channels. The system performs sentiment analysis to classify tone, then uses OpenAI models to extract themes, topics, and urgency indicators. All processed results are stored in a centralized database for trend tracking. Automated rules identify high-risk or negative sentiment items and trigger alerts to the relevant teams. Dashboards and workflow automation then visualize insights and support follow-up actions.

Setup Instructions
Data Sources: Connect social media APIs, survey tools, and customer support platforms.
AI Analysis: Configure the OpenAI API with sentiment and theme-extraction prompts.
Database: Set up a feedback storage schema in your utility database.
Alerts: Configure email notifications and CRM triggers for priority issues.
Dashboards: Link your analytics and reporting tools for real-time insights.

Prerequisites
Social media/survey API credentials; OpenAI API key; database access; CRM system credentials; email notification setup

Use Cases
Customer sentiment tracking; product feedback aggregation; support ticket prioritization; brand monitoring; trend identification

Customization
Adjust sentiment thresholds; add new feedback sources; modify categorization rules

Benefits
Reduces analysis time 85%; captures actionable insights; enables rapid response to issues

Nodes Used (9)

Azure OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatAzureOpenAi
Code
n8n-nodes-base.code
Google Sheets
n8n-nodes-base.googleSheets
HTTP Request
n8n-nodes-base.httpRequest
OpenAI
@n8n/n8n-nodes-langchain.openAi
Postgres
n8n-nodes-base.postgres
Send Email
n8n-nodes-base.emailSend
Sentiment Analysis
@n8n/n8n-nodes-langchain.sentimentAnalysis
Slack
n8n-nodes-base.slack