Connect to IntercomTicket Tagging
Ticket Tagging (also called Ticket Categorization or Classification) is the practice of labeling support conversations with structured metadata — issue type, product area, root cause, customer tier, resolution type — to enable accurate reporting, trend analysis, and routing. Consistent, accurate tagging is the data foundation that makes every other support metric meaningful. Without it, volume reports tell you how many tickets arrived but not why, and product teams have no reliable signal from support data.
Tagging Accuracy Rate = (Tickets tagged with the correct category ÷ Total tickets sampled in audit) × 100
Measure tagging accuracy by auditing a random sample of tickets (50–100 per week) and comparing agent-applied tags against expected tags based on ticket content. Track accuracy by agent and by tag type — some categories are consistently misapplied.
B2B SaaS support teams with defined taxonomy
Calculate tagging accuracy rate
- 1Building a taxonomy that is too granular — 150 tags produce inconsistent tagging and unusable data. Aim for 15–25 top-level categories with optional sub-tags.
- 2Not tracking tagging compliance (whether agents tag at all) separately from tagging accuracy — untagged tickets corrupt all reports silently.
- 3Changing the taxonomy without migrating historical data — adding or renaming tags mid-year makes year-over-year trend analysis impossible.
- 4Treating tagging as low-priority work — ticket categorization data is often the most valuable product feedback signal a support team produces. It deserves accuracy and ownership.