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It classifies ticket conversation history as positive, negative, or neutral and provides reasoning for the classification.

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Quick start

1

Add to your workflow

Add the action to workflows that process tickets with customer communications.
2

Configure basic settings

The action works with default settings, but you can add custom instructions for your specific business context.
3

Set up custom fields (optional)

By default the action writes to fields named “Neo - Customer Sentiment” and “Neo - Customer Sentiment Reasoning”. Create these fields in your PSA before you configure the action, or set different field names in the action settings. Both fields must be of type Text.
4

Add follow-up actions

Use “Update Ticket Fields” to save sentiment data and “Notify Internal Team” to alert staff about negative sentiment tickets.

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How it works

The action focuses on customer messages to determine the overall sentiment:
  1. Positive - Appreciation, satisfaction, or optimism
  2. Negative - Frustration, urgency, dissatisfaction, or complaints
  3. Neutral - Factual, routine, or emotionally neutral communication
The AI provides detailed reasoning for its classification and can optionally save both the sentiment and reasoning to custom fields in your PSA.

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Setup

Tickets to analyze: Works with any tickets from your workflow - typically all tickets from a specific search or filter. Custom instructions (optional): Add guidance such as:
  • “Consider urgency keywords like ‘ASAP’ or ‘critical’ as negative sentiment”
  • “Treat thank you messages as positive, even if brief”
Save to PSA (optional): You can save sentiment results and reasoning directly to custom fields in your PSA system for tracking and reporting.

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Common use cases

Automatically escalate tickets with negative sentiment by notifying team leads, increasing ticket priority, adding to “Needs Attention” queues, or assigning to senior technicians.
Monitor neutral sentiment on long-running tickets for proactive customer check-ins.
Analyze sentiment patterns across different service types, technicians, or time periods to identify areas for improvement.