How to Connect Gender API to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Gender API

You have an Excel workbook full of contact names — first names, full names, email addresses — and you need to know the likely gender behind each one. Maybe it's for personalized salutations before an email campaign. Maybe it's for regional segmentation. Maybe it's for cleaning up a CRM export that came in with no demographic fields at all.

Gender API is good at inferring gender from a name or email with a calibrated confidence score. But feeding a workbook of 5,000 names into it is not a one-click experience. The standard flow is: export the name column to CSV, write a script or build an integration that calls the API row by row, parse the JSON response, figure out what to do with low-confidence results, and paste everything back into the right columns.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: CSV Export and Paste-Back

The most common workflow for Excel users: export the name column as CSV, run it through a script or the Gender API playground, get results, and paste the gender column back into the right worksheet.

For ten names, manageable. For five thousand, it becomes its own project.

You keep a tally of where you left off. Row 847. You come back after a break and you're not sure if it was 847 or 874. The confidence scores land in a browser tab, formatted differently across batches. You find that 200 rows had no first name — just an email — and the playground doesn't handle that identically to the API.

Every fresh contact import means starting from scratch. Columns shift between files, the threshold for "Unknown" isn't written down anywhere, and the person who built the original workbook is gone.

Method 2: Power Automate

Power Automate has connectors that can call external APIs. You can wire up a flow that triggers on a new row in an Excel table, calls Gender API, and writes the gender and confidence back to the right columns.

Before going further: do you know what an HTTP action is? JSON parsing expressions? Array filtering in Power Automate? If those feel foreign, this isn't your path. Jump to Method 4.

For those still here: the setup works. You build a flow, configure the HTTP action for the Gender API endpoint, map the name or email field as the query parameter, parse the response body, and write to your target columns. The challenge is in the details — handling null names, setting confidence thresholds, treating email-only rows differently. None of that is expressible as a native connector setting.

Power Automate also fires one row at a time.

You probably just need to process an import of 3,000 names before a campaign goes out tomorrow. You probably have no idea how to build a conditional Power Automate flow with JSON parsing expressions. So you send a message to your IT contact — and now you're waiting on their queue while the campaign deadline moves closer.

Add row-skipping logic — don't re-process rows that already have a gender — and the flow complexity doubles.

Licensing tiers for Power Automate run-per-action billing add up fast on large lists.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable name-enrichment workflows was a category of add-ons that let you manually configure column mappings, save a reusable template, and run API calls in batches on demand.

That was a genuine improvement over CSV juggling. You picked your input column, your output columns, set a confidence threshold, saved the config, and ran it.

But you were still responsible for defining what "low confidence" meant, maintaining the column mapping when the workbook structure changed, re-running manually after each new import, and handling the edge cases — no name, foreign characters, initials only — that the template didn't cover. The tool moved the data. You still had to think through every edge case by hand. And when someone renamed a worksheet or added a column, the config broke silently until someone caught it.

This is the previous generation. It worked. But it still asked a lot of the person running it.

The Easy Way: Using SheetXAI in Excel

There is a different approach entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, understands the column structure, and through its built-in Gender API integration it can call the API for every row — or a filtered subset — and write the results back to the right columns. No template setup, no Power Automate flow, no CSV export. You describe what you want.

Example 1: Enrich a full contact workbook with gender and salutation

For every row in this workbook where column G is blank, use Gender API to infer gender from the first name in column B. Write the gender result to column G, the confidence score to column H, and write "Mr." / "Ms." / "Unknown" to column I based on the result — use "Unknown" for any confidence below 70%.

SheetXAI calls Gender API for each name, applies the confidence threshold inline, and populates all three columns. Rows that already have a value in column G are skipped automatically.

Example 2: Process email-only rows separately

For all rows in the 'Contacts' worksheet where column B is blank but column D has an email address, call Gender API using the email field. Write gender and confidence to columns G and H. Flag rows where confidence is below 60% with "Review" in column I instead of a salutation.

The pattern: instead of pre-filtering the workbook yourself and then running the enrichment, you describe the conditional logic and SheetXAI handles it in one pass.

Try It

Get the 7-day free trial of SheetXAI and open any Excel workbook with a contact list, then ask it to enrich your name column with Gender API results. The Gender API integration is included in every SheetXAI plan.