Copy-paste formulas to classify support tickets in Google Sheets
Paste a formula into row 2, test on a few tickets, then drag down.
Topic label
A: ticket text · B: your topic list
=GPT("Classify this ticket into one topic from the list, or other. List: " & B2 & ". Ticket: " & A2)
Urgency and sentiment
A: ticket text
=GPT("Return urgency (high/medium/low) and sentiment (positive/neutral/negative) for this ticket, comma-separated. Ticket: " & A2)
Suggested reply
A: ticket text · B: tone
=GPT("Draft a brief, helpful reply for an agent to review. Do not make promises or guarantees. Tone: " & B2 & ". Ticket: " & A2)
Short answer
Classifying support tickets in Sheets means tagging each message by topic, urgency, and sentiment, and optionally drafting a suggested reply, so the queue is triaged before agents open it. GPT for Sheets applies your label set across every row.
Fastest path: Install GPT for Sheets → paste ticket text → add the classify formulas using your labels → review → fill down.
This page is for support and CX ops analyzing exported tickets in a spreadsheet. Keep a human in the loop for routing and replies, and redact personal data you do not need; AI tags are a triage aid, not a final decision.
Workflow
A practical sheet for this workflow usually has these columns:
| Column | What to put there | Why it matters |
|---|---|---|
| A | Ticket ID | Row anchor |
| B | Ticket text | Source the AI classifies |
| C | Topic | Routing category from your label set |
| D | Urgency | High/medium/low for prioritization |
| E | Sentiment | Flags frustrated customers |
| F | Suggested reply | Draft for agent review |
Define your label set
Classification is only useful if the topics match how your team routes work. Pass your own topic list into the formula so the model picks from your taxonomy and returns ‘other’ when nothing fits, rather than inventing categories.
Triage, then assist
Run topic, urgency, and sentiment on a sample, confirm the labels route correctly, then fill down. Use the reply-draft formula as a starting point that an agent edits and approves, never as an auto-send.
Use cases
- Queue triage: route by topic automatically.
- Prioritization: surface high-urgency tickets first.
- Escalation: flag negative sentiment for managers.
- Agent assist: start replies, not finish them.
- Reporting: quantify ticket topics over time.
Best for / not best for
Best for: Support and CX ops who export tickets to Google Sheets and want fast, consistent triage labels and reply drafts for agents to review.
Not best for: auto-replying to customers without review, or handling regulated or sensitive cases where a human must classify and respond; AI tags and drafts require approval.
The strongest use case is pre-sorting an exported queue by topic, urgency, and sentiment so agents start with the right tickets and a draft they refine.
Internal links and next workflows
- GPT for Sheets product page
- GPT for Sheets pricing
- Categorize leads by industry
- AI lead enrichment guide
- ICP fit scoring in Google Sheets
- B2B sales account research
Safety, compliance, and data quality
AI tags and reply drafts are a triage aid, not a final decision. Keep agents in the loop for routing and responses, redact unneeded personal data, avoid promises in replies, and follow your support and privacy policies.
Frequently Asked Questions
Can it use my own ticket categories?
Yes. Pass your topic list into the formula so it classifies into your taxonomy and returns ‘other’ when nothing fits, keeping labels aligned with how you route.
Should I auto-send the suggested replies?
No. Treat drafts as a starting point an agent reviews, edits, and approves. The prompt avoids promises, but a human should always confirm before sending.
Does it handle sentiment?
Yes. It labels sentiment so you can flag frustrated customers for faster or higher-touch handling.
Is the classification always right?
No. It is a triage aid; review a sample, keep an ‘other’ bucket, and let agents override labels when needed.
Start triaging tickets in Google Sheets
Export tickets to a sheet, install GPT for Sheets, and tag topic, urgency, and sentiment with reply drafts agents review.