The Scenario
The support analytics manager is three days into a quarterly review when her director asks for the first-contact-resolution rate across all departments for the last 30 days. She knows the closed tickets are in Zoho Desk. She knows the resolution data is in those tickets. What she doesn't have is any of it in a spreadsheet where she can actually calculate FCR.
The bad version:
- Export closed tickets from Zoho Desk in CSV format. The export includes 200 tickets across six departments.
- Open the CSV. The resolution field is blank for about 40 rows — some tickets were closed without a resolution note, others used a canned response that isn't captured in this export.
- Spend an hour deciding which tickets to exclude, manually noting the close date, trying to back-calculate time-to-close from two separate timestamp columns.
By the time the data is in a state she can calculate FCR from, the afternoon is gone. The calculation takes ten minutes. The prep work is what ate the day.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It connects to Zoho Desk, pulls the closed ticket data you need, and writes it into the Sheet in a format where you can immediately start calculating — no CSV juggling, no manual timestamp arithmetic.
List all Zoho Desk tickets closed in the last 30 days and write ticket ID, subject, department, close date, and resolution summary into this sheet
What You Get
- All 200 closed tickets from the last 30 days, one row each
- Close date in a readable date format — not raw millisecond timestamps
- Resolution summary pulled from the ticket's resolution field where it exists
- Tickets with no resolution note flagged as blank rather than silently omitted, so the FCR denominator is accurate
What If the Data Is Not Quite Ready
You need time-to-resolution, not just the close date
List all Zoho Desk tickets closed in the last 30 days and write ticket ID, subject, department, close date, and time to resolution in hours (from ticket creation to close) into this sheet
Time-to-close lands in the Sheet as a number you can average — no manual timestamp subtraction.
You need to separate tickets that were reopened from clean first-contact closures
List all Zoho Desk tickets closed in the last 30 days and write ticket ID, subject, department, close date, resolution summary, and reopen count into this sheet; flag any ticket with a reopen count greater than 0 with 'REOPENED' in column G
FCR becomes calculable: count the rows without the REOPENED flag, divide by total, done.
You only want tickets from specific departments
List all Zoho Desk tickets closed in the last 30 days where the department is 'Enterprise Support' or 'SMB Support' — write ticket ID, subject, department, close date, time to resolution in hours, and resolution summary into this sheet
The analysis scope is constrained to the departments the director actually asked about.
Full kill chain: pull data, flag FCR-eligible rows, and surface the outliers
List all Zoho Desk tickets closed in the last 30 days and write ticket ID, subject, department, close date, time to resolution in hours, and reopen count into columns A through F; flag tickets with reopen count 0 as 'FCR ELIGIBLE' and tickets with reopen count greater than 0 as 'REOPENED' in column G; also flag any FCR-eligible ticket with time to resolution greater than 24 hours with 'SLOW CLOSE' in column H
One prompt returns the full FCR dataset with eligibility flags and outlier tags, ready for the quarterly deck.
The pattern: ask for the classification logic alongside the data pull — the Sheet arrives analysis-ready rather than needing another pass.
Try It
Get the 7-day free trial of SheetXAI and open a blank Google Sheet, then ask it to pull all closed Zoho Desk tickets from the last 30 days with reopen counts so you can calculate FCR without touching another export. For related tasks, see how to export open tickets for a backlog review, or return to the Zoho Desk overview for the full picture.