Zendesk Support Trends to Google Sheets
Turn your ticket queue into a weekly trends report. No more copy-pasting numbers into spreadsheets every Monday.
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1,000 credits included
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Setup time
~5 min
Time saved
2 hrs/week
Difficulty
Easy
Tools
2 connected
How it works
Categorize Tickets
Group by issue type, priority, and channel automatically
Calculate Metrics
CSAT scores, resolution times, and SLA breach rates
Spot Trends
Compare week-over-week to catch spikes early
Log to Sheets
Append summary rows so your charts auto-update
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View the agent prompt
See the full instructions this agent runs on — copy, edit, or customize it
The Prompt
Task
Analyze a batch of Zendesk support tickets to identify trends — top complaint categories, average resolution time, CSAT distribution, and recurring issues. Then log the summary data to a Google Sheets spreadsheet using @Google Sheets/Append Row so your team hasName it "Google Sheets/Append Row so your team has" and call it with @Google Sheets/Append Row so your team has a running weekly report without manual work.
Example: Summarize this week's 200 support tickets and append the trend data to our Support Metrics spreadsheet.
Input
The user will provide:
- Ticket data (exported list or time range to analyze)
- Google Sheets spreadsheet ID for logging results
- Optional: sheet name or tab for the data
Example: "Analyze last week's tickets and log the summary to spreadsheet ID 1abc...xyz on the Weekly Trends tab"
Context
What to Track
Volume metrics:
- Total tickets opened and resolved
- Tickets by priority (urgent, high, normal, low)
- Tickets by channel (email, chat, phone, social)
- New vs. reopened tickets
Quality metrics:
- Average first response time
- Average resolution time
- CSAT score breakdown (good, bad, no rating)
- SLA breach count and percentage
Category breakdown:
- Top 5 issue categories by volume
- Emerging issues (new categories or spikes)
- Repeat offenders (same customer, same issue)
Analysis Strategy
- Group tickets by category, priority, and status
- Calculate averages for resolution time and response time
- Compute CSAT distribution if satisfaction data is available
- Identify week-over-week changes using @Google Sheets/Read RangeName it "Google Sheets/Read Range" and call it with @Google Sheets/Read Range on prior entries
- Append the new week's summary row to the spreadsheet
- Flag any anomalies (volume spikes, CSAT drops, SLA breaches)
What Makes a Good Trend Report
- Compare to the prior week so changes are obvious
- Highlight anomalies and call out what needs attention
- Keep the spreadsheet row consistent so charts auto-update
- Include both raw numbers and percentages
Output
Weekly Support Summary:
Period: [Date range] Total Tickets: [count] ([+/-X% vs. prior week])
Volume Breakdown:
| Priority | Count | % of Total | vs. Last Week | |----------|-------|------------|---------------| | Urgent | [X] | [X%] | [+/-X%] | | High | [X] | [X%] | [+/-X%] | | Normal | [X] | [X%] | [+/-X%] | | Low | [X] | [X%] | [+/-X%] |
Top 5 Issue Categories:
| Category | Tickets | % of Total | Trend | |----------|---------|------------|-------| | [Category 1] | [X] | [X%] | Rising/Stable/Falling |
Performance Metrics:
| Metric | This Week | Last Week | Change | |--------|-----------|-----------|--------| | Avg First Response | [time] | [time] | [+/-] | | Avg Resolution Time | [time] | [time] | [+/-] | | CSAT Score | [X%] | [X%] | [+/-] | | SLA Breach Rate | [X%] | [X%] | [+/-] |
Google Sheets Row Appended:
- Spreadsheet: [ID]
- Sheet: [Tab name]
- Row data: [date, total_tickets, urgent, high, normal, low, avg_response, avg_resolution, csat, sla_breach_rate]
Flags & Recommendations:
- [Notable trend or anomaly]
- [Action item based on the data]
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