Genderize.io

Overview

Genderize.io provides an API for predicting the gender of a person based on their first name. The service operates by analyzing a large dataset of names and their associated genders across various countries and languages. When a first name is submitted to the API, it returns a predicted gender (male or female), a probability score indicating the confidence of the prediction, and the count of observations for that name in its dataset. Users can also specify a country code to refine predictions based on local naming conventions, which can be particularly useful for names that have different gender associations in different regions.

The API is designed for developers and technical buyers who need to integrate gender prediction capabilities into their applications or data pipelines. Common use cases include enhancing customer relationship management (CRM) systems by adding inferred demographic data, personalizing user interfaces or content delivery, and enriching datasets for market research and analytics. For instance, an e-commerce platform might use Genderize.io to tailor product recommendations or marketing messages, while a research firm could use it to segment survey responses.

Genderize.io emphasizes ease of integration, offering a straightforward RESTful API that accepts standard GET requests. The documentation includes code examples in multiple programming languages, facilitating quick adoption. The service also maintains API reference documentation that details endpoints, parameters, and response formats. Compliance with GDPR regulations is a stated feature, addressing data privacy concerns for users operating within the European Union.

The service's utility extends to scenarios where explicit gender data is unavailable or undesirable to collect directly. By inferring gender from first names, applications can maintain a level of personalization without requiring users to disclose sensitive information. This approach aligns with privacy-conscious design principles while still providing valuable demographic insights. For example, a content delivery network might use the API to suggest articles or videos that statistically appeal more to one gender, based on a user's registered first name, without ever asking for gender directly. The accuracy of predictions can vary depending on the name's commonality and the availability of data for specific regions, making the probability score a key component for developers to consider when implementing the service.

Overall, Genderize.io positions itself as a tool for data enrichment and personalization, offering a programmatic way to add gender predictions to various datasets and applications. Its simplicity and focus on name-based prediction make it suitable for tasks ranging from small-scale data cleaning to large-scale demographic analysis, particularly for applications dealing with international user bases where name origins and gender associations can be diverse.

Key features

• Gender Prediction from First Name: Predicts whether a given first name is male or female based on a global dataset.
• Probability Score: Provides a confidence score for each prediction, ranging from 0 to 1, indicating the likelihood of the predicted gender.
• Observation Count: Returns the number of times a name has been observed in the dataset, offering insight into the prediction's statistical basis.
• Country-Specific Predictions: Allows specifying a 2-letter ISO 3166-1 alpha-2 country code to refine gender predictions based on national naming trends. This is crucial for names with different gender associations across cultures.
• Batch Processing: Supports sending multiple names in a single API request, optimizing efficiency for processing larger datasets.
• Multi-language Support: The underlying dataset includes names from various linguistic backgrounds, enabling predictions for international names.
• GDPR Compliance: Adheres to General Data Protection Regulation (GDPR) standards for data processing and privacy.
• Developer SDKs: Offers client libraries in Python, Ruby, PHP, JavaScript, Java, and Go to streamline integration.
• Clear API Reference: Comprehensive API documentation detailing endpoints, parameters, and response structures.

Pricing

Genderize.io offers a free tier for basic usage and tiered paid plans for higher request volumes. Paid plans are structured based on the number of API requests per month.

Pricing as of May 2026. For the most current details, refer to the official Genderize.io pricing page.

Common integrations

Genderize.io can be integrated into various systems and workflows due to its RESTful API design and available SDKs. Common integration points include:

• CRM Systems: Enriching customer profiles with inferred gender for better segmentation and personalized communication. Developers might integrate it with platforms like Salesforce via custom Apex code or external integration tools to update contact records automatically, as described in Salesforce's documentation on making HTTP requests from Apex.
• Marketing Automation Platforms: Tailoring email campaigns, ad targeting, and content suggestions based on predicted gender.
• Business Intelligence (BI) Tools: Feeding demographic data into dashboards and reports for deeper market analysis. This often involves custom scripts or ETL processes that call the API to enrich data before it enters a BI system.
• E-commerce Platforms: Personalizing product recommendations, site navigation, and promotional offers.
• Data Warehouses and Lakes: Adding a gender attribute to large datasets during ingestion or transformation processes.
• Customer Support Systems: Providing agents with additional context about users for more personalized service.
• Survey and Research Platforms: Segmenting survey respondents or research participants based on inferred gender for more granular analysis.

Alternatives

Several other APIs offer similar functionality for gender prediction from names or broader demographic analysis:

• Name API: Provides gender and origin predictions for names, often used for similar data enrichment tasks.
• Namsor: Focuses on name origin, gender, and ethnicity prediction, with an emphasis on compliance and diversity analytics.
• Gender-API.com: Another direct competitor offering gender prediction from first names, including country-specific analysis.

Getting started

To begin using Genderize.io, developers typically register for an API key on the Genderize.io website. Once an API key is obtained, requests can be made to the API endpoint. The primary method involves a GET request to api.genderize.io with a name parameter. For country-specific predictions, an optional country_id parameter can be included.

Here's a basic example using Python to predict the gender of the name "Peter" and then "Anna" in a batch request:

import requests

# Replace 'YOUR_API_KEY' with your actual API key
API_KEY = 'YOUR_API_KEY' 

# Single name prediction
name_single = "Peter"
url_single = f"https://api.genderize.io?name={name_single}&apikey={API_KEY}"
response_single = requests.get(url_single)
data_single = response_single.json()
print(f"Prediction for {name_single}: {data_single}")

# Batch name prediction
names_batch = ["Anna", "Maria", "John"]
# Constructing the query string for multiple names
name_params = "&".join([f"name[]={name}" for name in names_batch])
url_batch = f"https://api.genderize.io?{name_params}&apikey={API_KEY}"
response_batch = requests.get(url_batch)
data_batch = response_batch.json()
print(f"\nBatch prediction for {', '.join(names_batch)}: {data_batch}")

# Example with country_id for "Peter" in Denmark (DK)
name_country = "Peter"
country_id = "DK"
url_country = f"https://api.genderize.io?name={name_country}&country_id={country_id}&apikey={API_KEY}"
response_country = requests.get(url_country)
data_country = response_country.json()
print(f"\nPrediction for {name_country} in {country_id}: {data_country}")

This Python script demonstrates how to make both single and batch requests, as well as how to specify a country for more refined predictions. The API returns a JSON object containing the name, predicted gender, probability, and count of observations. Developers should consult the Genderize.io API documentation for full details on error handling, rate limits, and advanced parameters.