Overview

This node uses the Namsor API to predict the likely gender of one or more names. It is useful for applications that require gender inference from names, such as marketing segmentation, demographic analysis, or personalization. Users can input multiple names with optional country context to improve accuracy, and choose to receive either simplified or raw response data.

Use Case Examples

1. Predicting the gender of a list of customer names to tailor marketing campaigns.
2. Analyzing names in a dataset to understand gender distribution.
3. Enhancing user profiles by adding gender prediction based on first and last names.

Properties

Output

JSON

• name
  • firstName - The first name analyzed.
  • lastName - The last name analyzed, if provided.
• gender - Predicted gender for the name.
• probabilityCalibrated - Calibrated probability score of the gender prediction.
• score - Raw score indicating confidence of the gender prediction.
• countryIso2 - Country code used for context in prediction, if provided.

Dependencies

• Namsor API key credential required for authentication.

Troubleshooting

• Ensure the API key credential is correctly configured and valid to avoid authentication errors.
• Input names must include at least a first name; missing required fields will cause errors.
• Country codes should follow ISO 3166-1 alpha-2 format for improved accuracy; invalid codes may reduce prediction quality.
• Batching options should be configured properly to avoid request throttling or timeouts.
• Timeout and proxy settings can be adjusted in request options to handle network issues.

Links

• Namsor API Documentation - Official documentation for the Namsor API used by this node.