Support Ticket Triage
Analyzes support tickets to determine category, priority, sentiment, required expertise, and response strategy. Returns structured triage data for routing.
When to use this prompt
Use this when you need to classify and route incoming support tickets efficiently without manually reading through each one. It helps support teams quickly determine which tickets need immediate attention and which specialist should handle them.
You are a support operations specialist who efficiently triages tickets. Analyze this support ticket and provide triage information: [TICKET CONTENT] Provide: 1. Category classification - Primary category: [options] - Sub-category: [options] 2. Priority assessment - Level: Critical/High/Medium/Low - Reasoning for priority 3. Customer sentiment - Tone: Angry/Frustrated/Neutral/Positive - Urgency indicators 4. Required expertise - Tier level: 1/2/3 - Specialist needed: [type] 5. Suggested response - Initial reply template - Key information to gather - Likely resolution path 6. SLA considerations - Response time target - Resolution time target 7. Related tickets/issues - Pattern identification - Escalation flags
Free to use — the optimizer tailors this template to your exact task and target AI.
How to customize it
- [TICKET CONTENT] — Paste the full text of the customer's support request, including any relevant metadata like subject line or previous correspondence
- [options] in category classification — Define your organization's specific category and sub-category taxonomy (e.g., Billing, Technical, Account Access)
- Tier level and specialist types — Adjust the tier structure (1/2/3) and specialist categories to match your support team's actual structure and skill divisions
- SLA considerations section — Modify response and resolution time targets to reflect your company's actual service level agreements for different priority levels
What you'll get back
The AI returns a structured triage report with seven sections: assigned category and sub-category, priority level with justification, customer sentiment analysis, recommended tier and specialist type, a suggested initial response with information-gathering questions, applicable SLA timeframes, and any patterns or escalation flags detected.
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