The GSMA’s Gender Analysis and Identification Toolkit (GAIT)

Friday 31 Aug 2018 | Bangladesh | Big data | Business model | Case study | Connected Women | Digital Inclusion | Digital Inclusion for Women | English | Gender | Global | Mobile Money for Women | Operational best practices | Resource | Toolkit |

The GSMA’s Gender Analysis and Identification Toolkit (GAIT) image

The GSMA’s Gender Analysis and Identification Toolkit (GAIT) addresses an issue many mobile operators face: the absence of reliable gender-disaggregated data on mobile ownership and usage. This information gap is an important one to solve, as understanding the nature and scale of the mobile gender gap is a prerequisite for closing it.

GAIT is a machine learning algorithm that analyses mobile usage patterns to estimate the gender of subscribers. This allows operators to predict the gender of their subscribers on an individual, MSISDN level. GAIT was developed in partnership with Dalberg Data Insights.

This document provides an overview of what the toolkit allows operators to do, how it works and what is required to apply the algorithm successfully. GAIT is freely available to all operator members of the GSMA. To access the full toolkit and technical documentation, please contact Connected Women at connectedwomen@gsma.com.