Support Ticket Triage Priority Score Generator
Calculate support ticket priority scores for automated triage and consistent prioritization. Enter values for instant results with step-by-step formulas.
Worked Examples
Example 1: VIP Customer Critical Issue
Problem: VIP customer reports complete service outage affecting 50 users. No workaround. Customer is angry. Been waiting 45 minutes. Calculate priority.
Solution: Factor Analysis:\n- Customer Tier: VIP (1.5x)\n- Issue Impact: 10/10 (service outage) = 100 pts\n- Users Affected: 50 × 5 = 250, capped at 50 pts\n- Revenue Impact: 8/10 (lost productivity) = 80 pts\n- Workaround: None (1.5x)\n- Sentiment: Angry (1.4x)\n\nBase Score: (100 + 50 + 80) = 230 pts\nWith Multipliers: 230 × 1.5 × 1.5 × 1.4 = 724\nCapped at 100\n\nSLA Analysis:\n- VIP SLA: 15 minutes\n- Waiting: 45 minutes (3x SLA breach!)\n- Additional urgency multiplier applied\n\nResult:\n- Priority Score: 100 (P1 - Critical)\n- Suggested SLA: Immediate\n- Routing: Senior agent, page if necessary\n- Action: Apologize for delay, escalate to engineering
Result: P1 CRITICAL (100) | Immediate response | Page on-call if needed | SLA breached
Example 2: Standard Customer Minor Issue
Problem: Standard customer reports UI formatting bug. 1 user affected. No revenue impact. Workaround exists. Customer is neutral. Just submitted.
Solution: Factor Analysis:\n- Customer Tier: Standard (1.0x)\n- Issue Impact: 2/10 (cosmetic bug) = 20 pts\n- Users Affected: 1 × 5 = 5 pts\n- Revenue Impact: 1/10 = 10 pts\n- Workaround: Full (0.6x)\n- Sentiment: Neutral (1.0x)\n\nBase Score: (20 + 5 + 10) = 35 pts\nWith Multipliers: 35 × 1.0 × 0.6 × 1.0 = 21 pts\n\nSLA Analysis:\n- Standard SLA: 120 minutes\n- Waiting: Just submitted (0 min)\n- No urgency multiplier\n\nResult:\n- Priority Score: 21 (P4 - Low)\n- Suggested SLA: 24 hours\n- Routing: Standard queue\n- Action: Acknowledge, add to bug backlog, may batch with similar issues
Result: P4 LOW (21) | 24-hour SLA | Standard queue | Batch processing OK
Example 3: Enterprise Customer Escalation
Problem: Enterprise customer (50-seat) reports intermittent errors affecting 10 users. Partial workaround. Already escalated by sales. Customer frustrated. Waiting 90 minutes.
Solution: Factor Analysis:\n- Customer Tier: Enterprise (1.3x)\n- Issue Impact: 6/10 (intermittent errors) = 60 pts\n- Users Affected: 10 × 5 = 50 pts\n- Revenue Impact: 5/10 = 50 pts\n- Workaround: Partial (1.0x)\n- Sentiment: Frustrated (1.2x)\n- Escalated: Yes (1.3x)\n\nBase Score: (60 + 50 + 50) = 160 pts\nWith Multipliers: 160 × 1.3 × 1.0 × 1.2 × 1.3 = 324\nCapped at 100\n\nSLA Analysis:\n- Enterprise SLA: 30 minutes\n- Waiting: 90 minutes (3x breach)\n- Urgency multiplier: 1.3x (adds to already-capped score)\n\nResult:\n- Priority Score: 100 (P1 - Critical due to escalation)\n- Suggested SLA: 15 minutes\n- Routing: Senior agent, CC sales and account manager\n- Action: Personal call, expedited investigation, exec update
Result: P1 CRITICAL (100) | Escalation in play | Call customer immediately | Update sales
Frequently Asked Questions
What is ticket triage and why automate it?
Triage is sorting tickets by priority to handle the most important first. Manual triage is slow, inconsistent, and doesn't scale. Automated priority scoring ensures objective, consistent prioritization, faster routing, and better SLA compliance. It also reduces agent cognitive load and improves customer satisfaction.
What factors should influence ticket priority?
Key factors: (1) Customer tier/value, (2) Issue severity/impact, (3) Users affected, (4) Revenue at risk, (5) Workaround availability, (6) Customer sentiment, (7) Time waiting, (8) SLA status, (9) Escalation status. Weight factors based on your business priorities—revenue impact matters more for sales-driven companies.
What is a good SLA by priority level?
Common SLA structure: P1 (Critical) 15-30 min first response, P2 (High) 1-2 hours, P3 (Medium) 4-8 hours, P4 (Low) 24 hours, P5 (Minimal) 48-72 hours. Adjust based on customer tier—VIPs often get faster SLAs at every priority level. Resolution time SLAs should be multiples of response time.
Should sentiment analysis affect priority?
Yes, but carefully. Angry customers are escalation risks and may churn—faster response can de-escalate. But don't reward aggression excessively—creates wrong incentives. Use sentiment as a tiebreaker or 10-20% multiplier, not primary driver. Train agents to respond appropriately to emotional customers.
How do I prevent priority gaming?
Customers may learn to select 'critical' to get faster service. Solutions: (1) Validate severity against issue type, (2) Audit priority overrides, (3) Use objective factors (users affected, revenue) over subjective (customer-selected urgency), (4) Provide tier-based SLAs so legitimate urgency gets appropriate response without gaming.
Should I auto-assign based on priority?
Yes, with nuance. High-priority tickets should route to available senior agents. Medium to next-available with relevant skills. Low can queue for batch handling. Consider: agent expertise, current workload, customer relationship (same agent for same customer when possible). Auto-assignment reduces manual routing overhead.