The Scenario
You're a growth marketer at a SaaS company. The webinar sign-up forms have been running for three months and the Excel workbook now has 4,200 rows — name, company, email, source — collected from six different form providers with no validation at the point of capture.
Tomorrow you need to push this to Mailchimp before the post-event nurture sequence goes out. Which means today you need to know which of these 4,200 addresses will actually receive mail.
The bad version:
- Export column B to a CSV, upload to a verification tool, wait 40 minutes for results, download a second CSV.
- Open both files side by side and do a VLOOKUP to match verdicts back to the right rows — hoping nothing drifted between export and download.
- Manually apply red/orange formatting to the bad rows, then delete them one section at a time while trying not to accidentally pull a valid address with them.
That's two hours of reconciliation work for a list that's going to change again as soon as you finish. The campaign window doesn't move because the list prep took longer than expected.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook that reads the data and talks to Mailcheck for you. You describe what you want done — which column to verify, what to write back, how to flag the results — and it handles the API calls, the column writes, and the formatting in one pass.
Verify every email in column B using Mailcheck and write the verdict (valid/risky/invalid), disposable flag, and reason back into columns C, D, and E — then highlight invalid rows red and risky rows orange
What You Get
- Column C: verdict string — "valid", "risky", or "invalid" — for every row in column B.
- Column D: disposable flag — TRUE or FALSE.
- Column E: plain-English reason — "MX record not found", "disposable domain", "role address", etc.
- Invalid rows: red background fill across the entire row.
- Risky rows: orange background fill so you can review before deciding whether to include them.
What If the Data Is Not Quite Ready
The emails are in the wrong format — trailing spaces, mixed case, "@company" without a TLD
Before verifying, clean every email in column B — trim whitespace, lowercase everything, remove entries that don't match a basic email pattern — then run Mailcheck on the cleaned values and write results to columns C, D, and E
Some rows have a company email in column B and a personal backup in column F — verify whichever is more likely to be the primary contact
For each row, check if column B has a valid-looking email. If it does, verify that with Mailcheck and write the result to column C. If column B is empty or malformed, verify column F instead and note "used backup" in column D alongside the verdict.
The workbook has leads from multiple sources in column G — I only want to verify the rows where column G says "Webinar"
Filter to rows where column G equals "Webinar", then verify every email in column B for those rows using Mailcheck and write verdict, disposable flag, and reason to columns C, D, and E — leave the other rows untouched
Verify the list, flag the riskies, delete the invalids, and give me a count I can paste into the campaign brief
Use Mailcheck to verify every email in column B. Delete all rows where the verdict is "invalid" or the disposable flag is TRUE. For rows where the verdict is "risky", highlight column B in orange. Then write a summary in cell A1: total rows checked, rows deleted, rows flagged risky, rows remaining.
The pattern is to ask for the cleanup and the action together — one prompt, one pass through the workbook.
Try It
Get the 7-day free trial of SheetXAI and open the Excel workbook where your webinar leads are sitting, then ask it to verify and triage the address column before your next upload to any ESP. Or check out how to validate prospect domains before sales outreach and the full Mailcheck integration overview.