The Scenario
It's Monday at 8:45 AM and your technicians arrive in fifteen minutes. You're the shop manager, and you need to know exactly what's sitting in the queue — how many open tickets, who they're assigned to, and which jobs have been waiting long enough that someone needs to make a call. The information is in RepairShopr. You need it in a Google Sheet that the whole team can see during standup.
The bad version:
- Log into RepairShopr, navigate to the tickets view, apply the open-status filter, and export to CSV.
- Open the CSV in Sheets, delete the eighteen columns you don't need, reformat the date column, and sort by created date.
- Paste the result into the planning sheet, which has a different column layout from the CSV export, and manually rearrange columns before the meeting starts.
That sequence takes twenty-five minutes on a good day. Most Mondays it takes longer, because the export includes resolved tickets that slipped through the filter, or the CSV encoding breaks one of the date values and you spend five minutes figuring out why column E is showing a number instead of a date.
The standup is happening whether the sheet is ready or not.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands what you're working with, and through its built-in RepairShopr integration it can pull ticket data directly — no CSV export, no column rearranging, no manual cleanup. You describe what you need and it handles the rest.
Fetch all open tickets from RepairShopr and write ticket number, customer name, subject, assigned technician, and created date into columns A through E
What You Get
- Column A: RepairShopr ticket number
- Column B: customer name as it appears in RepairShopr
- Column C: ticket subject line
- Column D: assigned technician name
- Column E: ticket created date in a readable format
- Any ticket that fails to pull (e.g., a permission issue) is flagged in column F with the error message
What If the Data Is Not Quite Ready
The date column is in epoch format instead of readable dates
Fetch all open RepairShopr tickets and write ticket number, customer name, subject, assigned technician, and created date into columns A through E, formatting the created date in column E as MM/DD/YYYY
You want to highlight tickets open more than 7 days without a separate formula
Get all RepairShopr tickets with status open and write ticket ID, customer, subject, days open, and assigned technician into columns A through E, then add the text "OVERDUE" in column F for any row where column D is greater than 7
The ticket list spans multiple shops and you only need one location
Fetch all open RepairShopr tickets where the location name contains "Main St" and write ticket number, customer name, subject, and created date into columns A through D
Full morning prep in one shot: pull tickets, flag overdue, sort by wait time
Pull all open RepairShopr tickets, write ticket number, customer name, subject, assigned technician, and days open into columns A through E, put "OVERDUE" in column F for any ticket open more than 7 days, then sort the entire table by column E descending so the oldest tickets appear first
The pattern across all four: describe the filter, the format, and the sort in one prompt instead of doing each step manually after the data lands.
Try It
Open a Google Sheet with your RepairShopr data and get the 7-day free trial of SheetXAI — ask it to pull this week's open tickets, flag anything overdue, and sort by wait time before your next standup. For related workflows, see how to export ticket timers for labor analysis or the full RepairShopr integration overview.