Automated Sentiment Analysis Tracking for Support Issues via Linear, Slack & Air

Overview

This workflow automates sentiment analysis on support issues, integrating Linear, Slack, OpenAI, and Airtable. It streamlines the process of monitoring customer feedback and team responses, providing actionable insights in real time.

Key Features

• Automated Sentiment Extraction: Uses OpenAI's language model to analyze sentiment from issue comments.
• Data Integration: Syncs support issues and sentiment data between Linear and Airtable for centralized tracking.
• Real-Time Notifications: Notifies relevant teams via Slack when sentiment transitions are detected.
• Batch Processing: Efficiently processes multiple issues and comments in batches for scalability.

Benefits

• Enhanced Customer Insight: Quickly identifies shifts in customer sentiment, enabling proactive support.
• Time Savings: Eliminates manual sentiment tracking, reducing workload for support teams.
• Improved Collaboration: Keeps teams informed through Slack notifications, fostering faster response times.
• Centralized Data: Maintains a single source of truth in Airtable for reporting and analytics.

Use Cases

• Monitoring customer satisfaction trends on support tickets.
• Alerting teams to negative sentiment spikes for rapid intervention.
• Generating sentiment-based reports for management review.

Integrations & Automation

Key integrations include Airtable for data storage, OpenAI for sentiment analysis, and Slack for notifications. The workflow leverages n8n's automation capabilities to orchestrate these processes seamlessly.