Triaging 1,200 weekly tickets before an agent opens one
Support was getting 1,200 tickets a week through a single shared inbox. Five categories made up most of the volume: billing questions, password resets, feature requests, bug reports, and how-do-I questions. Three agents spent the first hour of every shift sorting, tagging, and assigning before they could write a single response. Real bugs sat in the queue for five hours on average while the team worked through the noise.
What was getting in the way
Support was getting 1,200 tickets a week through a single shared inbox. Five categories made up most of the volume: billing questions, password resets, feature requests, bug reports, and how-do-I questions. Three agents spent the first hour of every shift sorting, tagging, and assigning before they could write a single response. Real bugs sat in the queue for five hours on average while the team worked through the noise.
How we shaped the fix
We built a triage layer that reads each incoming ticket, classifies it into one of the five known categories, and acts on it before it ever lands in front of an agent. Billing, password, and how-do-I tickets get an immediate auto-response from a pre-approved macro library and only escalate if the customer replies. Feature requests get acknowledged and routed to a product board. Bug reports get parsed for error codes and stack traces, tagged with a rough severity, and pushed to the specialist queue. Agents see a clean inbox of tickets that genuinely need a human.
What changed
68% of tickets get an auto-response within 90 seconds. Real bug response time dropped from five hours to forty minutes. Agents handle roughly 40% more cases per shift because the sort work is gone. The team is the same size.
What we did not change
The team’s helpdesk software stayed. The macro library is the one the agents had already written and tested. We did not introduce a new chatbot product or a new tool the agents had to learn. The triage layer sits invisibly in front of the existing setup and does the sorting work that was already happening, just faster and at any hour.
The numbers
- 68% of tickets auto-responded within 90 seconds
- 5 hours to 40 minutes bug response time
- 40% more cases handled per agent shift
- 0 new tools added to the agent workflow
What this would look like in your business
Support teams with steady ticket volume and repeating categories are well-suited to this shape of work. The threshold is usually category stability: if 70% or more of your tickets fall into five repeating shapes, automating the triage and response on those frees the team for the genuinely novel cases that need judgement. Below that threshold, the work is the categorisation itself and a different approach makes sense.
What this shipped back to support.
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