The Scenario
The fundraising campaign letter drops in eleven days. Your direct mail coordinator pulled the donor list — 1,200 rows, column A, raw addresses collected over three years from event sign-up forms, pledge cards, and a CSV import from a defunct CRM. Some have full ZIP+4. Some are missing the ZIP entirely. A few are clearly from the form field that accepted free text, which means one person entered "St." and another entered "Street" for the same block.
The bad version:
- Copy a row from column A, paste it into the AddressZen web form, copy the verified result, paste it into column B, note whether the API returned a match or a failure, move to the next row
- Somewhere around row 60, accidentally paste a verified result into the wrong row, shifting every subsequent entry one cell off from its source record
- Flag the failures by hand in column C — except the definition of "failure" was never pinned down, so some rows get "INVALID" and some get "?" and some just get left blank because it's row 340 and the logic got fuzzy
Your organization mails to unverified addresses at $1.12 per piece. You do not have the budget for 200 pieces of returned mail, and you definitely don't have the runway to explain to the development director why the year-end appeal had a 17% return rate.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, talks to AddressZen, and writes the results back — without you touching a single row manually.
For each address in column A, use AddressZen to resolve the full deliverable US address and write the result to column B — mark any that fail as INVALID in column C
What You Get
- Column B: the full standardized US address for each resolvable row (street number, street name, city, state, ZIP+4 where available)
- Column C: INVALID for any row AddressZen couldn't resolve — consistently, across all 1,200 rows, with no drift in the flag language
- The original column A is untouched — your source data stays intact for reference
- Rows with INVALID in column C are your pull list for manual review before the print run
What If the Data Is Not Quite Ready
The addresses are split across three columns (street, city, state/ZIP)
Combine columns A (street), B (city), and C (state + ZIP) into a single address string for each row, then use AddressZen to verify each combined address and write the result to column D — mark failures as INVALID in column E
Some rows are missing ZIP codes entirely
For rows in column A where the ZIP code is missing, attempt AddressZen verification anyway and write whatever result it returns to column B — if AddressZen returns a resolved ZIP, include it in the output; if it can't resolve, mark column C as INVALID and column D as MISSING-ZIP
Failed rows need to move to a separate worksheet for review
Validate all addresses in column A using AddressZen, write verified results to column B and INVALID to column C for failures — then move all INVALID rows (with their original data) to a new worksheet called 'Address Review', preserving the raw address in column A of that sheet
Full cleanup, validation, and isolation in one pass
Trim whitespace and fix obvious capitalization in column A, then run each cleaned address through AddressZen — write the standardized result to column B, flag column C as INVALID for failures, move all INVALID rows to a new 'Address Review' worksheet, and add a count of verified vs. failed addresses in cell E1 of the main sheet
The pattern is always the same: cleanup and routing happen in the same prompt, not as separate steps you have to sequence yourself.
Try It
If you have a donor list, a customer import, or any address column that needs to be clean before it touches a downstream system, Get the 7-day free trial of SheetXAI and run the validation prompt against your workbook. You can also see how SheetXAI handles standardizing Shopify shipping addresses, or go back to the AddressZen overview for the full picture.