The Scenario
Your marketing ops lead handed you a purchased list — 800 email addresses from a trade show badge scan — and said "clean it before you upload it to Klaviyo." You've heard the stories about what happens to sender reputation when a bad list goes through an ESP. You don't want to be the person who finds out firsthand.
The list is already in a Google Sheet, column A. You have until end of day.
The bad version:
- Open Hunter's email verifier, paste in the first address, copy the status, score, and risk flags back into columns B, C, and D.
- Move to row 3. Paste. Copy. Move.
- 800 rows. At 30 seconds per row you're here until midnight.
Nobody hired you to paste email addresses into a verification box for eight hours. You're supposed to be thinking about the campaign, not the data hygiene.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads your column structure and through its Hunter integration it can verify every email in column A in bulk, writing the deliverability status and risk metadata back to the right columns without you touching a single row.
Verify every email address in column A using Hunter and write the deliverability status, score, and any risk flags (disposable, catch-all, etc.) to columns B, C, and D.
What You Get
- Column B: deliverability status for each address — VALID, RISKY, INVALID, or UNKNOWN.
- Column C: Hunter's numeric verification score (0–100).
- Column D: risk flags where applicable — disposable domain, catch-all server, role-based address (e.g. info@, support@), or syntax error.
- The full run completes across all 800 rows without row-by-row intervention.
What If the Data Is Not Quite Ready
You want to filter and mark rows, not just populate columns
You need INVALID and RISKY rows highlighted in red and UNKNOWN rows in yellow before you hand this off to the campaign manager.
Verify every email in column A using Hunter and write status to column B, score to column C, and flags to column D. Then apply conditional formatting: red background for INVALID and RISKY rows, yellow for UNKNOWN, green for VALID.
Some addresses have extra whitespace or inconsistent capitalization
The badge scan data is messy. Half the addresses have a trailing space, some are ALL CAPS, a few have double dots in the local part.
Before verifying, clean every email address in column A: trim whitespace, lowercase the entire address, and fix any obvious formatting issues like double dots. Write the cleaned address to column E and then verify column E using Hunter. Write results to columns B, C, and D.
You only want to verify rows above a certain score threshold before uploading
Your ESP has a bounce rate tolerance of 2%. You want to understand what score cutoff gives you a list that clears that bar.
Verify all emails in column A using Hunter. Write status to column B and score to column C. Then add a column D that marks each row "INCLUDE" if the score is 80 or above and "EXCLUDE" if below. Count how many rows fall in each bucket and write the summary to cell F1.
You want cleanup + verification + segmentation in one shot
You need the cleaned addresses, their verification status, their risk category, and a recommended action — all in one pass, ready for the campaign manager to review.
Clean every email in column A (trim, lowercase, fix formatting), then verify each cleaned address with Hunter. Write the cleaned email to column B, status to column C, score to column D, risk flags to column E, and a recommended action to column F: "SEND" for VALID above 75, "MANUAL REVIEW" for RISKY or UNKNOWN, "REMOVE" for INVALID.
Asking for the full sequence in a single prompt means you get a decision-ready output, not a data dump you still have to interpret.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet where column A holds a list of email addresses you need cleaned before a send. Ask SheetXAI to verify them with Hunter and label the results. Then see how to bulk-find emails from names and domains or go back to the Hunter overview.