The Scenario
You're a supply chain analyst. Your master product catalog — 800 SKUs, maintained in a Google Sheet — updates every month when purchasing finalizes the new pricing and codes. Field reps use DataScope forms to record their orders, and the form's dropdown pulls from a metadata list inside DataScope called 'products.' Last month someone noticed that reps were selecting items that had been discontinued two months ago. You traced it back: the DataScope list hadn't been updated since Q3. Nobody set up a process for keeping it current because nobody thought it would drift.
The bad version:
- Export the current product catalog from your sheet as a CSV.
- Log into DataScope's metadata section, find the 'products' list, delete all 800 existing entries one page at a time.
- Import the new list — discover the CSV column headers don't match what DataScope expects, reformat the file, try again.
The catalog changes every month. Your job is analysis, not data entry. Nobody budgeted time for a monthly 90-minute sync ritual when the catalog was first connected to DataScope.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the catalog, talks to DataScope through its built-in integration, and replaces the metadata list in one pass — no CSV formatting, no DataScope UI.
Read all rows from my Products sheet and bulk-replace the 'products' metadata list in DataScope with the current SKU names and codes from columns A and B.
What You Get
- The 'products' metadata list in DataScope replaced with the current contents of the Products sheet — SKU name in the label field, SKU code in the value field.
- A confirmation written back to the sheet showing how many items were added, how many removed, and the timestamp of the sync.
- Any SKU name that contains characters DataScope rejects flagged in column C for review.
What If the Data Is Not Quite Ready
Some SKUs in the catalog are marked as discontinued and should be excluded
Read all rows from my Products sheet and bulk-replace the 'products' metadata list in DataScope — but only include rows where column C does not say 'DISCONTINUED'. Write a count of included and excluded SKUs into cell F1 and F2 of the Products sheet.
You need to compare the existing DataScope list before overwriting
Compare the current 'products' metadata list in DataScope against column A of my Products sheet — list any SKU names that are in DataScope but not in the sheet, list any that are in the sheet but not in DataScope, and write both lists into a new sheet called 'Catalog Diff' before making any changes.
Multiple metadata lists need to be updated from different tabs
Read the Products sheet and update the 'products' metadata list in DataScope using columns A and B. Then read the Locations sheet and update the 'locations' metadata list using columns A and B. Report how many entries were updated in each list.
Full sync: diff, update, and log the changes in one prompt
Compare the current 'products' metadata list in DataScope against my Products sheet (column A = name, column B = code), write a diff to a 'CatalogSync' sheet showing what's new, what's removed, and what's unchanged — then replace the DataScope list with the full current Products sheet contents and timestamp the sync in cell A1 of CatalogSync.
Cleanup and the sync operation together, no intermediate steps needed.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet where your master product catalog lives, then ask it to push the current list into DataScope and log what changed. Also worth reading: Bulk Create DataScope Locations From a Google Sheet Roster and the full DataScope integration guide.