Connect to IntercomTicket Aging
Ticket Aging tracks how long open, unresolved tickets have been sitting in the queue without resolution. It is typically measured as the average age of all currently open tickets (in hours or days), and visualized as an aging bucket report (0–24h, 24–72h, 3–7 days, 7+ days). Aging reports are a real-time operational view of backlog health — they reveal which tickets are at risk of SLA breach and which issue types are systematically difficult to resolve.
Average Ticket Age = Sum of (current time − creation time) for all open tickets ÷ Number of open tickets
Report in business hours when your team operates within defined support hours — a ticket 72 calendar hours old but only 8 business hours old is not the same as one that is 72 business hours old. Most helpdesks support business-hours filtering. Track aging at the same time each day (e.g., end of shift) for consistent comparisons.
B2B SaaS, standard tier (end-of-day snapshot)
Calculate average ticket age
- 1Not reviewing aging reports daily — tickets age fastest during high-volume periods, and late discovery means late intervention.
- 2Treating all aging tickets as equal urgency — a ticket from a churning enterprise account that is 6 hours old needs more urgency than a low-priority feature request at 48 hours.
- 3Conflating ticket aging with SLA breach — SLA is a commitment to customers; aging is an internal operational view. You can be within SLA and still have unhealthy aging patterns.
- 4Not using aging data for staffing decisions — a shift where 30% of tickets are over 48 hours old is a workload signal that warrants a staffing adjustment.