The Scenario
It's Monday morning. Your inbound form collected 500 leads over the weekend and they're sitting in a Google Sheet — column A is the email address, everything else is blank. Before any of them get pushed into your CRM, your ops lead sent a Slack message: "Please validate the list first. Last time we imported a batch with half gmail addresses, the sequence performance numbers were a disaster."
You remember that batch. You remember manually scanning through it looking for obvious free-email domains. There were 400 rows and you still missed a dozen.
The bad version:
- Sort column A alphabetically and visually scan for gmail.com, yahoo.com, hotmail.com — plus the disposable domain names you happen to recognize.
- Write "FLAG" into column B for the ones you catch, knowing you're not catching all of them.
- Google "disposable email domain list," find a CSV, try to do a VLOOKUP against it that breaks on your first typo.
The ops lead is going to ask if you checked for disposables. "I tried to" is not the answer she's looking for.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads your email column and runs each address through Tomba's domain validation endpoint — checking whether the domain is webmail, disposable, or legitimate business infrastructure.
Here's the prompt to use:
For every email address in column A, check if the domain is webmail or disposable and write 'webmail', 'disposable', or 'business' into column B. Process every row from row 2 to the last non-empty row.
What You Get
After running this prompt:
- Column B contains one of three values per row: "webmail", "disposable", or "business".
- Every row is covered — no manual sampling, no visual scan.
- You can filter on column B immediately: sort, highlight, or delete the flagged rows before the CRM import.
- Rows where column A is blank are skipped.
What If the Data Is Not Quite Ready
Emails have inconsistent capitalization or extra spaces
If the inbound form didn't normalize input, you might have "John@Gmail.COM" sitting next to "sarah@acme.com". Tomba's domain check is case-insensitive, but clean data processes faster.
Trim whitespace and lowercase every email in column A, then check each address against Tomba's domain validation and write 'webmail', 'disposable', or 'business' into column B.
You want to tag free-email separately from disposable
"Webmail" covers gmail and yahoo — but your team treats those differently from throwaway domains like mailinator.com. You want a four-category output.
For every email in column A, classify the domain as 'business', 'free-email' (gmail, yahoo, hotmail, outlook, etc.), or 'disposable' (single-use or temporary domain). Write the classification into column B.
You only want to check rows where another column is blank
You've already validated some rows manually — column C has "checked" for those rows. Skip them.
For every row where column C is blank, check the email in column A against Tomba's domain validation and write 'webmail', 'disposable', or 'business' into column B. Leave rows where column C already has a value untouched.
Full pipeline: deduplicate emails, validate domains, and flag high-risk rows in one pass
Remove any duplicate email addresses in column A (keep the first occurrence, mark duplicates in column C with "duplicate"). For the remaining rows, validate each email's domain via Tomba and write the classification into column B. Then for any row classified as 'disposable', write "DO NOT IMPORT" into column D.
Run cleanup and validation together — the output is import-ready.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of inbound email addresses, then ask it to classify every domain before your next CRM import. For a related workflow, see enriching domains with professional email addresses, or the full Tomba integration overview.