Ticket Tagging

What it means

Tags are short labels attached to tickets that describe their content: 'order-status', 'return-request', 'damaged-item', 'discount-code', 'cancel-order', 'product-question'. Tags can be applied manually by agents, automatically by rules (if ticket contains 'track' → apply 'tracking'), or by AI (which reads the full conversation and applies the most accurate classification). A clean, consistent tag taxonomy is foundational for support analytics. When every return request carries the 'return-request' tag, you can track return inquiry volume over time, correlate it with product return rates, and measure the impact of a policy change. Without consistent tagging, those analyses are impossible. For Shopify brands, the tag taxonomy should reflect the actual distribution of ticket types in the store's queue. A typical ecommerce tag set includes: WISMO/tracking, return-request, exchange-request, refund-status, order-modification, product-question, discount-shipping, general-feedback, and escalation. Keeping the taxonomy under 20 primary tags maintains usability — overly granular tag sets lead to inconsistent application. AI auto-tagging dramatically improves tag consistency by applying classifications at ticket creation without relying on agents to remember to tag. Agents who are focused on resolution frequently skip tagging; AI never does.