Support ticket analysis
Support ticket analysis that reads the tickets, not just the tags.
Support ticket analysis is reading a queue’s conversations together to find what they have in common: the bug behind a run of tickets, the question your docs never answer, the customer who mentions a competitor.
Overdesk does that reading on a schedule, on Help Scout, Zendesk, Intercom and FreeScout, and gives you the result as a short, ranked list of findings.
14 days with every Pro feature. No card.
By hand or on a schedule
A person can read a week of tickets. Few have time to do it each week.
Analysis by hand works: export the tickets, read them, note the patterns, write it up. It also costs a day, so it happens when someone asks, usually after the problem has grown.
Overdesk reads the queue on a schedule and writes the findings for you, so a pattern shows up in the next run instead of the next quarterly review.
What it reads
Message bodies, not tags or ticket fields.
Tags and fields are what an agent chose to record, in a hurry, at the end of a reply. The cause is in what the customer wrote. The analyses read the subject and the opening snippet your help desk shows for each recent conversation. Recurring bugs, post-release regressions, churn signals and frustration signals also read the start of the messages in the thread. Out-of-date docs also reads the customer’s message, the draft and your team’s reply.
Questions it answers
The questions a support lead gets asked, answered from the queue.
What looks broken since the last release?
Which bugs keep coming back?
Recurring bugs, most frequent and severe first.
Who is about to cancel, and why?
Churn signals, with the ticket each one came from.
What are customers asking us to build?
Feature requests, merged and ranked by demand.
What should we document next?
Documentation gaps and the most repeated questions.
What could a saved reply handle?
Automation candidates, ranked by volume.
When it runs
Daily for what can hurt you this week, weekly for the rest.
Post-release regressions, frustration signals and churn signals run every morning over the last 3 days.
Recurring bugs, feature requests, repeated questions, documentation gaps, automation candidates, themes and the per-product breakdown run every Monday over the past 7 days. Out-of-date docs runs when you start it.
Assist runs documentation gaps, repeated questions and automation candidates every week. The other analyses are Pro features. See plans and pricing.
On Pro, alerts for serious new problems and a daily morning briefing go to Slack or ClickUp.
What you get
A short list of problems, ranked, with the tickets behind each.
A recurring problem becomes one finding, with how many conversations mention it and whether it is getting worse. Each finding carries a severity, the tickets it cites, and a trend: new, steady or getting worse. When something needs a decision, the weekly summary opens with it.
You review the brief and file it, with email addresses and card numbers taken out. It goes to GitHub, Linear or Jira.
Two steps have their own pages: filing support tickets as issues, and the revenue at risk behind churn and frustration.
Your data
Your customers paste passwords into tickets. Overdesk takes them out first.
Before the AI reads a ticket, Overdesk swaps out the email addresses, card numbers, licence and API keys, and labelled passwords customers paste in. It does not catch everything. How redaction works.
Every analysis runs on the Anthropic account you connect, and Anthropic bills you for it.
Questions
We already have reports in our help desk. Isn’t that the same?
Not quite. Help desk reports mostly count tickets by volume, tag and response time. Support ticket analysis reads what the tickets say and groups them by cause, so you see which bug is behind the volume. Keep both: they answer different questions.
How often should support tickets be analysed?
Daily for anything that can hurt you within days: a bad release, angry customers, people ready to leave. Weekly for patterns that need a week of tickets to show, like recurring bugs, feature requests and repeated questions. On Pro, Overdesk schedules them that way from the start.
Does it work with Help Scout, Zendesk, Intercom and FreeScout?
Yes. Connect Help Scout, Zendesk, Intercom or FreeScout and the analyses read its conversations. Your team keeps working in the help desk it uses today.
How do findings reach my developers?
You review the issue brief Overdesk writes from a finding, then file it in GitHub, Linear or Jira. Overdesk never writes code or opens pull requests: it stops at the issue.
Something we didn’t cover? Email us or book a demo.