Analyze support issue sentiment and alert via Slack
Workflow Description
Workflow that automatically collects support issues, processes them in batches, analyzes emotional tone using AI, removes duplicates, stores results in Airtable, and sends consolidated alerts to Slack for real-time visibility.
How it works
- 1.Fetch support issues from Airtable or trigger on schedule
- 2.Process issues in batches and analyze sentiment using OpenAI API
- 3.Identify and remove duplicate entries from the dataset
- 4.Classify issues by sentiment score and update Airtable records
- 5.Send summarized alerts to designated Slack channels
Use cases
- Monitor customer satisfaction by automatically analyzing support messages
- Flag critical negative sentiment issues for immediate escalation
- Reduce manual effort in triaging and categorizing support inquiries
- Generate periodic sentiment reports to track service quality trends
Requirements
- Active OpenAI API key configured and ready
- Full access to Airtable base containing support issues
- Slack workspace connection with message posting permissions
- Well-structured issue data with text, timestamp, and status fields
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (19)
Issues to List
Split Out
OpenAI Chat Model
OpenAI
Combine Sentiment Analysis
Set
Sentiment over Issue Comments
Information Extractor
Copy of Issue
Set
For Each Issue...
Split In Batches
Get Existing Sentiment
Airtable
Update Row
Airtable
Airtable Trigger
Airtable Trigger
Sentiment Transition
Switch
Fetch Active Linear Issues
Graphql
Schedule Trigger
Schedule Trigger
Deduplicate Notifications
Remove Duplicates
Report Issue Negative Transition
Slack
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Sticky Note3
Sticky Note
Sticky Note4
Sticky Note