The Scenario
It's a Wednesday afternoon and you're three hours into a localization project that was supposed to take one. You're on the localization team at a B2B software company. Someone handed off a 1,500-row contact list — first names in column A, country codes in column B — and asked you to add a gender column before the email generation pipeline runs.
The pipeline uses the gender to assign salutations: "Herr," "Frau," "Mr.," "Ms.," and so on. Get the gender wrong in Germany and you've sent a business email with the wrong honorific to a prospect. That's not a minor formatting issue.
The handoff note from the person who left the project says "just use GenderAPI.io, it handles country codes." It does not say how.
The bad version:
- Look up GenderAPI.io's documentation for the country-code parameter, realize the API call requires both a name and a country code in the query string, and figure out how to format that for 1,500 rows
- Build a formula or macro to construct the API URL for each row, run it, parse the JSON response for each cell, and write the gender back — discovering at row 300 that some country codes in column B are lowercase and the API returns an error
- Spend 45 minutes normalizing the country codes, re-run the enrichment for the failed rows, and realize you still have to manually check 60-odd rows where the API returned "unknown" because the first name is a nickname that doesn't appear in GenderAPI.io's training data for that locale
This work was supposed to be upstream setup, not the main event. The pipeline is waiting on you.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that sits inside your Excel workbook. It understands what's in the columns and can call GenderAPI.io with the right parameters — including the country-code localization hint — across every row, without you building a single formula or macro.
Here's the prompt for this task:
Use GenderAPI.io to look up gender for each first name in column A, passing the country code from column B as a localization hint, and write the result into column C
SheetXAI reads columns A and B together, constructs each API call with the country-code parameter, and writes the inferred gender into column C. Rows where the API returns an error or "unknown" are marked in the result so you can spot them without scanning 1,500 cells.
What You Get
- Column C: inferred gender for every row, localized to the country code in column B
- Rows with "unknown" or error responses explicitly marked rather than filled with a default
- Results ready for the salutation-assignment pipeline to consume without additional cleanup
- No formula maintenance — the enrichment is a one-time ask, not a live function
What If the Data Is Not Quite Ready
The country codes are inconsistent — some are uppercase, some lowercase, some are full country names
The list was assembled from three different sources and nobody normalized the country column before the handoff.
Before calling GenderAPI.io, normalize column B so all country codes are uppercase two-letter ISO codes — convert any full country names to their ISO equivalents — then run the gender lookup for each first name in column A with the corrected country code and write the result into column C
Some rows have no country code at all
About 80 rows in the list have a blank in column B — probably contacts added before the country field was required.
For rows where column B is empty, query GenderAPI.io using only the first name in column A with no country-code hint and write the gender into column C; for rows with a country code in column B, include it in the lookup
The contact list is split across regional worksheets — Europe, APAC, Americas — and needs to be enriched consistently
The list was partitioned by region at some earlier point in the project. You need all three worksheets enriched with the same approach.
Enrich the 'Europe', 'APAC', and 'Americas' worksheets by calling GenderAPI.io for each first name in column A with the country code from column B, writing the gender result into column C on each worksheet — flag any row where the API returns unknown or an error
The list needs gender, salutation assignment, and a confidence threshold applied — all before it goes to the pipeline
The pipeline downstream requires a confidence score above 0.75 to use the inferred gender. Anything below that should default to a gender-neutral salutation.
Use GenderAPI.io to look up gender for each first name in column A with the country code from column B, write the gender and confidence score into columns C and D, and in column E write the appropriate salutation — use the gendered honorific if confidence is above 0.75, otherwise write 'Dear [First Name]'
One prompt handles the enrichment, the threshold logic, and the salutation column the pipeline actually reads.
Try It
Get the 7-day free trial of SheetXAI and open the contact workbook waiting for gender enrichment, then ask it to run GenderAPI.io lookups with whatever country-code column you have. See also: enriching a subscriber list with gender from email addresses and the GenderAPI.io integration overview.