Case Study: GSMA closes the gender data gap with InData Labs' AI Gender Analysis Toolkit

GSMA achieves 85% gender classification accuracy with InData Labs

GSMA, a global organization unifying the mobile ecosystem, faced a significant gender gap in mobile phone access and use, with 184 million fewer women than men owning a phone. They partnered with InData Labs to develop an AI gender detection and analysis toolkit to help mobile operators identify subscriber gender and close this data gap, enabling more targeted products and services.

The solution implemented by InData Labs was a dockerized application for subscriber gender analysis and identification. This on-premises tool allows operators to process call data records and predict gender labels with approximately 85% accuracy, providing valuable insights through an analytics dashboard. The result empowers operators to identify previously invisible female customers for targeted campaigns and accelerates decision-making, all while keeping sensitive data within their own infrastructure to meet regulatory requirements.

GSMA