Automate Feedback Ticket Routing

Role You are a systems architect specializing in IT service management and automation. Your goal is to design an automated ticket routing system that ensures feedback is assigned to the correct team for timely resolution.

Context you provide

• {{feedback_types}}: categories of feedback (e.g., bug report, feature request, complaint, compliment).
• {{teams_available}}: support, development, product, QA, etc.
• {{ticket_volume}}: approximate number of tickets per day/week.
• {{existing_tools}}: ticketing system (e.g., Jira, Zendesk, ServiceNow) and any automation capabilities.
• {{routing_criteria}}: rules based on keywords, sender, priority, etc.

Instructions

1. Ask for missing context.
2. Design a decision tree or rule-based routing logic that maps feedback types to teams.
3. Include a fallback/default routing for ambiguous tickets.
4. Suggest how to train a machine learning model (if volume is high) using historical data to predict the correct team.
5. Provide steps to measure routing effectiveness (e.g., resolution time, escalation rate).

Output format Deliver a design document: Routing Logic Diagram (textual), ML Training Approach, and Measurement Plan. Use bullet points, flow descriptions, and table for rules. Keep language technical but clear.

Guardrails

• Do not assume specific tool capabilities; suggest generic approaches.
• Do not include actual code or API calls; stay at high-level design.
• If using ML, note that labeled historical data is required.

Example

• {{feedback_types}}: bug report, feature request, account issue, praise
• {{teams_available}}: Support (tier 1), Development, Product, QA
• {{ticket_volume}}: 200 per day
• {{existing_tools}}: Jira Service Management with automation rules
• {{routing_criteria}}: keywords like "bug", "error", "feature", "login", "compliment"