The Scenario
You're a growth engineer at a SaaS startup. The migration date has been locked for two weeks. You exported 800 active users from the legacy database into a Google Sheet last Thursday — uid, email, first name, last name, plan tier — and the handoff note said "get them into Engage before go-live." Go-live is tomorrow morning.
The bad version:
- Open Engage's user creation UI. Find the "create user" form. Fill in uid, email, first name, last name, plan. Click save. Go back. Row 2. Repeat 799 more times.
- Try the CSV import instead. Discover Engage's import template wants a column called "identifier" not "uid." Reformat the header. Re-upload. Row 47 fails because of a special character in the name field. Fix it. Re-upload again.
- Give up on CSV after row 200, switch back to the form, and start manually entering the rest at 11 PM.
Nobody hired you to be a data-entry operator for the night before a platform migration.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your data and talks to Engage for you — no template to configure, no CSV format to massage. Open the sidebar, describe the job.
Create an Engage user for each row in my Google Sheet — columns are uid, email, first name, last name, and plan — and write each returned user ID to column F
What You Get
- An Engage user record created for every row in the sheet, with uid mapped to the identifier field, email, first name, last name, and plan all set correctly.
- Each returned Engage user ID written back to column F as rows are processed, so you have a confirmed record of what landed.
- Any rows that fail (duplicate email, invalid field value) are flagged in a status column so you know exactly which ones need attention.
- A full sheet of 800 rows processed in a single operation — not 800 separate form submissions.
What If the Data Is Not Quite Ready
The uid column has mixed formats — some are integers, some are strings with a prefix
Create an Engage user for each row in my Google Sheet. Column A has user IDs — some are plain integers like 10042 and some are prefixed strings like usr_10042. Normalize all of them to the prefixed format before creating the user, and write the returned Engage user ID to column F.
Some rows are missing a first name — only a full name in one column
Create an Engage user for each row. Column C has a full name in one field. Split it into first name and last name on the space, use the first token as first name and everything after as last name, then create the user with email from column B, identifier from column A, and plan from column E. Write the returned user ID to column F.
Users with plan = 'legacy' should be skipped
Create an Engage user for each row where column E is not 'legacy'. Use uid from column A, email from column B, first name from column C, last name from column D, and plan from column E. Write the returned user ID to column F for created rows, and write 'skipped' to column F for legacy rows.
Clean the data, deduplicate by email, and create all users in one shot
Deduplicate my Google Sheet by email address in column B, keeping the row with the most recent timestamp in column G. Normalize the uid column A to prefixed format (usr_XXXXX). Then create an Engage user for every remaining row with uid, email, first name, last name, and plan, and write the returned user ID to column F.
The pattern: prep the data and run the import in a single prompt — no manual pre-flight required.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet with your user export, then ask it to push all rows into Engage with a single prompt. Or try the sibling article on subscribing users to an Engage list, or see the full Engage integration overview.