The Scenario
It's Thursday afternoon and the weekly ops meeting is tomorrow at 9 AM. Your field teams have been running site inspections all week through DataScope — 150+ submissions across 30 locations — and the facilities director wants a summary by location showing defect rates. You've been in this role three months. The person before you built the report by hand in a Google Sheet every Thursday. You've been doing the same thing: logging into DataScope, downloading a CSV, pasting it into the sheet, reformatting the date column that always comes in wrong, writing a COUNTIF for each location, and hoping nothing shifts between the export and the pivot.
The bad version:
- Download the DataScope export, discover the submission timestamps are UTC and your locations are split across four time zones, spend 25 minutes writing a formula to shift each row correctly.
- Manually delete the 12 submissions from a form version that was retired in February, which DataScope still includes in exports because the form ID is still active.
- Build the per-location defect rate by hand — COUNTIF across 500 rows — realize you named one location "Site 4A" in the sheet and DataScope exported it as "Site 4-A," and now your summary is off by 14.
You have a meeting in 16 hours. Doing this manually one more time isn't something your Thursday evening can absorb.
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 looking at, and talks to DataScope directly through its built-in integration. You describe the output you need. It handles the API calls, the grouping logic, and the writeback.
Fetch the last 500 form answers from DataScope and write each submission as a row in a new sheet called 'Inspections' with columns for submission date, technician name, location, and each answer value. Then create a second sheet called 'Summary' that groups submissions by location, shows total count, and calculates the percentage where any answer contains 'fail' or 'no'.
What You Get
- A new Inspections sheet with one row per submission — date, technician name, location, and all answer values in labeled columns.
- A Summary sheet with one row per location — submission count and defect rate as a percentage.
- Locations that appear under more than one spelling in DataScope are surfaced as separate rows, flagged for review.
- Any submission that returned a partial result (missing answer values) is written with a note in a Status column.
What If the Data Is Not Quite Ready
The timestamps are in UTC but your locations span multiple time zones
Fetch the last 500 DataScope submissions and write them to the Inspections sheet — but convert the submission_date field from UTC to the local timezone listed in the Locations reference tab for each submission's location name, and flag any location not found in the reference tab with 'TIMEZONE UNKNOWN' in column F.
The export includes retired form versions you need to exclude
Pull all DataScope form answers from the past 30 days, but only include submissions where the form name matches one of the active form names listed in column A of my ActiveForms sheet — skip any submission from a retired form and write a count of excluded rows at the top of the Inspections sheet in cell A1.
Your location names don't match between DataScope and the sheet
Fetch the last 500 DataScope submissions, write them to the Inspections sheet, then run a lookup against my Locations reference tab: match each submission's location name to column A, write the canonical location ID from column B into a new 'CanonicalID' column, and flag any unmatched location name in red in column G.
Clean the data, build the summary, and flag problem rows in one pass
Fetch the last 500 DataScope submissions, normalize location names against my Locations tab, exclude any submissions from retired forms listed in my ArchivedForms tab, convert timestamps to local timezone from the Locations tab, write all rows to the Inspections sheet, and build a Summary sheet grouped by canonical location showing total submissions and defect rate — marking any location with a defect rate above 20% in bold.
One prompt handles the normalization and the analysis together — no intermediate cleanup step required.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet where your team tracks site inspections, then ask it to pull this week's DataScope submissions and build a location summary. Also worth reading: Bulk Create DataScope Locations From a Google Sheet Roster and the full DataScope integration guide.