The Scenario
Your localization team just handed you a 2,000-row contact sheet. It came from a third-party list vendor — first name in column C, email in column D, region in column E, but no salutation field and no geographic origin for any name. You're supposed to assign each contact a locale before it gets imported into the translation workflow: en-US, en-GB, de-DE, fr-FR, and so on. The region column says "Europe" for 800 contacts. That's not granular enough.
You've been staring at this sheet for twenty minutes, and you know the answer lives somewhere in the name column.
The bad version:
- Manually research common first names by country of origin for a 2,000-row list — which is not a thing a human can actually do at scale.
- Look up each name individually in Gender API's playground, record the country result, paste it into column F, and repeat.
- Discover that 600 rows have names from multiple possible countries and make judgment calls with no data to back them up.
The localization handoff is at 4 PM. You have twelve other things on your list, and "research 2,000 name origins by hand" wasn't one of them when you got to work this morning.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads the columns, understands the context, and calls Gender API — including its country-of-origin data — for every row. Tell it what you need.
Use Gender API to query every first name in column C. Fetch gender, confidence score, and the top country of origin. Write gender to column D, confidence score to column E, and country of origin to column F for each row.
What You Get
- Column D: "male," "female," or "unknown" for each contact.
- Column E: numeric confidence score (0–100).
- Column F: top country of origin returned by Gender API (e.g., "DE," "FR," "US") — the highest-probability country for that name.
- Rows with names that return no country result get an empty cell in column F, not a silent failure.
What If the Data Is Not Quite Ready
Column C has full names — "Marie Dupont" — not just first names
For all full names in column C of the 'Contacts' tab, call Gender API's full-name endpoint. Write gender, confidence, and primary country of origin to columns D, E, and F.
The same contact appears in multiple rows (duplicates by email in column D)
Before calling Gender API, identify all unique first names in column C by deduplicating on column D. Call Gender API once per unique name. Write the results back to columns G, H, and I for every row that shares that name.
You need to map the country code to a locale string — "DE" should become "de-DE," "FR" should become "fr-FR"
Use Gender API to get gender and top country of origin for each first name in column C. Write gender to column D, confidence to column E, and country code to column F. Then in column G, write the full locale string — "de-DE" for Germany, "fr-FR" for France, "en-US" for US, "en-GB" for UK — based on the value in column F.
You need gender, country origin, and a confidence-gated salutation in one pass — and rows below 65% confidence should be flagged for manual review
For every first name in column C, call Gender API and fetch gender, confidence, and top country of origin. Write gender to column D, confidence to column E, country to column F. In column G, write "Mr." for male or "Ms." for female when confidence is 65 or above; write "FLAG" for anything below 65% so those rows can be reviewed separately.
Combining the enrichment, the threshold logic, and the review flag in one prompt means no second pass.
Try It
Open your contact localization sheet and get the 7-day free trial of SheetXAI. Ask it to run Gender API across your name column and write gender, confidence, and country of origin to the columns your localization workflow expects. See also: bulk salutation enrichment and the hub overview.