The Scenario
You're three days out from switching off the old OMS and going live on Simla.com. The migration spreadsheet has 500 historical orders — external order IDs, customer emails, offer IDs, quantities, delivery addresses — and every one of them needs to exist in Simla before the cutover. The platform team has signed off on the data structure. Now it's on you to get the rows in.
The bad version:
- Open Simla's order import wizard, match each column to its expected field name, upload 50 rows at a time, and manually investigate each row the validator rejects.
- Fix the rejected rows in the sheet, re-export, re-upload, and reconcile the two result logs to figure out which ones actually landed.
- Repeat until all 500 are in — then cross-reference the sheet against Simla's order list to confirm nothing was silently skipped.
The go-live window doesn't have room for three rounds of debugging a CSV uploader. The platform team needs confirmation that the orders are in before they flip the switch, and you need that confirmation in writing.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent built into Google Sheets. It reads your migration spreadsheet, understands the column structure, and uses Simla's order creation API to push every row — processing them in batches and writing the resulting Simla order IDs back into the sheet so you have a clean audit trail.
Upload all orders from this sheet to Simla using external order ID in column A, customer email in column B, product offer ID in column C, quantity in column D, and delivery address in column E — process all rows in batches of 50.
What You Get
- All 500 orders created in Simla as new order records
- The resulting Simla internal order ID written into column F for each successfully created row
- Failed rows flagged with the error message returned by the API, so you can address them specifically
- A complete batch log in the sidebar showing how many succeeded per batch
What If the Data Is Not Quite Ready
Delivery addresses are stored as full strings, not split into fields
Simla expects structured address data — street, city, and postal code as separate fields. If your column E has full address strings like "12 Baker Street, London, W1U 6TN", ask SheetXAI to parse and split them before uploading.
Split the delivery addresses in column E into street (column E), city (column F), and postal code (column G), then upload all orders to Simla using external order ID in column A, customer email in column B, offer ID in column C, quantity in column D, and the split address columns.
Offer IDs in the sheet don't match Simla's current catalog
If your sheet was exported from the old OMS, offer IDs may have changed since the Simla catalog was built. Cross-reference before importing.
Check each offer ID in column C against the offer IDs in my Simla Catalog tab and flag any that don't match with "MISSING OFFER" in column G — then upload only the rows without flags to Simla.
Some external order IDs already exist in Simla from a partial migration
If a previous partial import already pushed some of these orders, re-importing them creates duplicates.
For each row in this sheet, check whether the external order ID in column A already exists in Simla — skip rows that do, and upload only the new ones, writing the result in column G.
Full cleanup and upload in one shot
Normalize the delivery addresses in column E into street, city, and postal code, remove any rows where column C has a blank offer ID, check for existing external IDs in Simla and skip duplicates, then upload the remaining rows in batches of 50 and write the Simla order ID into column F.
The pattern: handle the data quality issues and the API operation in a single ask, rather than running them as separate cleanup passes.
Try It
Get the 7-day free trial of SheetXAI and open your Simla order migration spreadsheet, then tell it which columns map to which fields and how many rows to batch. Link to the Bulk Import Customers spoke for the next step in the migration, or back to the Simla.com integration hub for the full overview.