The Scenario
Three days before a Mailchimp import, your email marketing manager opened the sign-up form export: 2,000 email addresses collected over four months, sitting in column A of a Google Sheet with no validation applied at intake.
Some of these came from paid ad traffic. Some came from a partner co-registration where the incentive was a discount, not genuine interest. A portion are almost certainly disposable or syntax-broken.
Mailchimp's import will flag bad addresses on the way in — but that happens after you've already paid for the list cleanup tool, after you've already set up the campaign, and after you've already discovered that 400 of your contacts were never real.
The bad version:
- Export the column, run it through a free email validation service with a 500-row cap, get back results that don't match the original row order.
- Manually cross-reference which flagged emails belong to which rows in the original sheet, mark them, repeat for the next 500-row batch.
- Realize the service flagged valid business addresses as "catch-all" and now you're second-guessing which ones to remove.
There are 2,000 rows and the import window is Thursday.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet that reads your data and calls BigDataCloud's email verification API across the full column — in one pass, not in 500-row chunks.
Open SheetXAI from the Extensions menu and type:
Verify every email in column A of my sheet using BigDataCloud and write the verification result (valid/invalid/disposable) and failure reason into columns B and C
What You Get
- Column B: verification result — "valid", "invalid", or "disposable"
- Column C: failure reason for non-valid addresses (e.g., "invalid syntax", "domain does not exist", "disposable email provider", "catch-all domain")
- Rows that return "valid" get a blank cell in column C — no clutter for the rows you're keeping
- SheetXAI notes the total count of each category in the sidebar after the run
What If the Data Is Not Quite Ready
The email column has whitespace or mixed-case formatting
Verify every email in column A using BigDataCloud — trim whitespace and normalize to lowercase before the verification call, then write result and failure reason into columns B and C
You want to filter out bad rows immediately, not just flag them
Verify all emails in column A using BigDataCloud, mark invalid and disposable addresses in column B, then create a new sheet called "Clean List" with only the rows where column B is blank (verified valid)
The sheet has a mix of personal and business emails and you want to segment them
Verify every email in column A using BigDataCloud — write result and failure reason into columns B and C, then add a column D that classifies each valid email as "business" (non-free-provider domain) or "consumer" (gmail, yahoo, hotmail, etc.)
Full list hygiene pass before the import
Verify all 2,000 emails in column A using BigDataCloud — trim and normalize formatting, write result and failure reason into B and C, create a "Mailchimp Ready" sheet with only valid business emails, and add a summary row at the top of that sheet showing how many were removed and why
One prompt covers the normalization, the verification, the segmentation, and the export.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a sign-up form email export — run the verification prompt above before your next campaign import and know exactly what you're sending to. See the phone validation spoke if you also need to clean the phone number column in the same sheet.