The Scenario
Your ops team exported 5,000 contacts from the CRM last Tuesday. The export has been sitting in a shared Drive folder since then. This morning someone flagged that the last campaign had an unusually high bounce rate — 8% — and now marketing wants to know how many of those contacts have invalid or unreachable email addresses before the list goes back into the CRM for the next send.
The bad version:
- Open the CRM export sheet, copy column C (the email column), paste it somewhere, figure out how to send it through Mailboxlayer, receive back a bulk result you can't easily join to the original rows
- Paste in the mx_found and smtp_check results column by column, making sure row 1 in the result still corresponds to row 1 in the original sheet even though you sorted the export before you started
- Manually build a 'valid' or 'invalid' label in a new column based on a combination of three different fields that all mean something slightly different
This work is going to take an hour you do not have, and it will need to happen again after the next CRM export, and the one after that.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the column structure, calls Mailboxlayer for every row, and writes the results back — valid/invalid verdict, MX flag, SMTP check — without you touching a single API response. You describe what you want.
Run Mailboxlayer validation on every email in column C and write 'valid' or 'invalid' to column D — also write the mx_found and smtp_check flags to columns E and F
What You Get
- Column D: 'valid' or 'invalid' per row — a single field your team can filter on immediately
- Column E: mx_found — TRUE or FALSE showing whether a mail exchange record exists for that domain
- Column F: smtp_check — whether the receiving mail server confirmed the address is reachable
- Rows with FALSE in column E or F will also show 'invalid' in column D, giving you two levels of signal: the quick filter column and the specific reason underneath
What If the Data Is Not Quite Ready
Column C has emails in mixed case — some all-caps domains, some lowercase
Lowercase every email in column C, run Mailboxlayer validation on all 5,000 rows, and write 'valid' or 'invalid' to column D with mx_found and smtp_check in columns E and F
The export has a handful of rows where column C is blank or contains a placeholder like 'N/A'
Skip any row in column C that is blank or contains non-email text like 'N/A', validate the remaining rows with Mailboxlayer, write 'valid' or 'invalid' to column D and mx_found, smtp_check to columns E and F — write 'Skipped' in column D for the blank/placeholder rows
Emails are spread across two tabs — 'Q1 Contacts' and 'Q2 Contacts' — and I need both validated
Validate all emails in column C of the 'Q1 Contacts' tab and column C of the 'Q2 Contacts' tab using Mailboxlayer — write 'valid' or 'invalid' to column D and the mx_found flag to column E on each tab
Clean the data, validate, and produce a summary sheet in one operation
Lowercase and trim all emails in column C, skip blanks and placeholder rows, validate the rest with Mailboxlayer — write 'valid' or 'invalid' to column D with mx_found and smtp_check in E and F, then create a new tab called 'Validation Summary' with a count of valid, invalid, and skipped rows
One prompt handles the cleanup, the validation, and the summary — no intermediate steps needed.
Try It
Get the 7-day free trial of SheetXAI and open your CRM export sheet, however messy it came out of the system, and ask it to run Mailboxlayer across the email column and tag each row. Also see bulk validating lead gen emails or the full Mailboxlayer integration overview.