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AI agent for ux writers

Support Ticket Language Mining Agent

Find the copy that confuses customers, fix it, and prove whether the fix reduced tickets.

AnalysisWritersCreatives
See how it worksGet access
Support Ticket Language Mining Agent: what goes in, what the agent does and what you get

What it does

Customers write to support when copy confuses them, but nobody maps the tickets to the screens and words that caused it. This agent reads support tickets and groups them by the screen or feature they mention and the phrases customers quote or misunderstand. It finds repeated confusion, such as many people asking what a button does or misreading a label, and ranks them by volume and severity. For the top items, it proposes copy changes tied to the exact string. After the writer approves and the change ships, it watches the ticket volume for that topic and compares it with the earlier rate. If tickets do not drop, it reopens the item with new suggestions. It never changes copy. The writer approves every change. Edge case: tickets caused by a bug, not wording, are routed to the product team.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Weekly run 2 USES A TOOL Read new tickets and match them to screens andstrings 3 DOES Group tickets by topic and quoted wording 4 CHECKS THE RESULT Is the cause wording rather than a bug or missingfeature? If not: route the group to the product team with theevidence. Back to step 3. 5 DOES Rank wording issues by volume and severity 6 DOES Propose copy changes for the top issues 7 YOU APPROVE Writer approves the changes 8 USES A TOOL After release, count tickets for the topic over thenext 3 weeks 9 CHECKS THE RESULT Did tickets fall by at least the target? If not: propose a new wording and reopen the item. Backto step 6. 10 RESULT Confusion log with results
Read the steps as a list
  1. Weekly run
  2. Read new tickets and match them to screens and strings
  3. Group tickets by topic and quoted wording
  4. Is the cause wording rather than a bug or missing feature?If not: route the group to the product team with the evidence. Back to step 3.
  5. Rank wording issues by volume and severity
  6. Propose copy changes for the top issues
  7. Writer approves the changesThe agent waits here for your OK.
  8. After release, count tickets for the topic over the next 3 weeks
  9. Did tickets fall by at least the target?If not: propose a new wording and reopen the item. Back to step 6.
  10. Confusion log with results

How it decides

It ranks an issue by ticket count, customer effort and how clearly the ticket points to a specific string. It judges a fix by comparing ticket rates before and after.

  • Rank higher when over 20 tickets a month cite the same string
  • Route bug-caused tickets to product
  • Compare 3 weeks before and 3 weeks after release
  • Reopen an item when tickets fall by less than 30%

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Ticket tags and sources
  • Volume threshold (default 20 a month)
  • Success target (default 30% drop)
  • Measurement window
  • Report format

What keeps you in control

It always asks you first

  • Each copy change

Hard limits

  • Never change copy or reply to customers
  • Hide personal data in examples

It stops when

  • Done: tickets fall to target
  • Stop: ticket data unavailable

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn March, 64 tickets asked what Archive does on the project screen, and 23 thought it deleted files. The agent proposed Move to archive, files stay available. After release, tickets in the following 3 weeks fell from 64 to 41, a drop of 36%, over the 30% target. The writer closed the item.

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