The Scenario
The person who tracked estimate conversion left the company last quarter. Their replacement inherited the role three weeks ago and has just discovered there are 200 estimates in RepairShopr from the past 90 days — accepted, declined, pending — with no historical report showing the conversion rate. The new coordinator needs to pull those estimates into an Excel workbook, calculate the conversion rate, and present the numbers to the sales director on Friday. They're a coordinator, not a data analyst. The data is in RepairShopr.
The bad version:
- Export estimates from RepairShopr to CSV. Open in Excel.
- Find the "status" column has five different spellings of the same statuses — "Accepted," "accepted," "ACCEPTED," "Invoice Created," and blank — which means any COUNTIF formula returns wrong results until everything is normalized.
- Spend an hour doing find-and-replace on the status column before the pivot table will work correctly.
The presentation is on Friday. The data cleanup just ate Tuesday.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, understands the analysis context, and through its built-in RepairShopr integration it can pull all estimates with consistent status values — no normalization needed before you can build the analysis.
List all RepairShopr estimates from the last 90 days with customer name, total amount, and status in this Google Sheet
What You Get
- Column A: customer name
- Column B: total amount (numeric)
- Column C: status as a consistent label (not inconsistently capitalized)
- All 200 estimates from the date range, none silently excluded
What If the Data Is Not Quite Ready
You need all six fields for the full estimates export
Fetch all RepairShopr estimates and write estimate number, customer name, subtotal, tax, total, and status into columns A through F
You want the conversion rate calculated alongside the raw data
Fetch all RepairShopr estimates from the last 90 days and write estimate number, customer name, total, and status into columns A through D; then in cell F2 write a COUNTIF formula counting rows where column D equals "Accepted," and in F3 divide F2 by the total estimate count to show the conversion rate
Some estimates are linked to invoices and you want to identify those separately
Pull all RepairShopr estimates from the last 90 days and write estimate number, customer name, total, status, and linked invoice number into columns A through E; put "CONVERTED" in column F for any row where column E is not empty
Full conversion analysis in one pass: pull, classify, summarize
Fetch all RepairShopr estimates from the last 90 days and write estimate number, customer name, total, and status into columns A through D; categorize each in column E as "Won," "Lost," or "Open" based on the status; add a summary table starting in column G with total count, total value, and percentage for each category
The pattern: one prompt gives you the analysis-ready output, not a raw export that needs another hour of cleanup.
Try It
Open an Excel workbook and get the 7-day free trial of SheetXAI — ask it to pull your RepairShopr estimates from the past quarter, classify by outcome, and add a summary table for Friday's presentation. For related work, see how to export unpaid invoices for collections or the RepairShopr integration overview.