The conventional blue/white collar market segmentation has dominated travel demand modelling since the 1960s. Many city-region transport models have therefore struggled to keep up with systemic changes in Australian labour markets, especially the growing participation of women. Our aims were to help the Queensland Government develop a new commuter classification structure for the Brisbane Strategic Travel Demand Model using the latest South East Queensland Travel Survey data. An inductive approach is used, identifying from within the data itself what might be improved groupings of commuters for market segmentation. Using cluster analysis, commuter types are grouped by a key set of occupational, industry, and socio-demographic variables (i.e., gender, age, household size, household vehicle ownership and worker skill score). The results reveal there are distinct types of commuters that cannot be easily combined into one or two groups. We propose a market segmentation of three types of workers for SEQ. This includes revisions to what are the previous ‘blue’ and ‘white’ collar workers, and a new female-dominated type, which we call ‘pink-collar’ workers. All have distinct travel behavior characteristics. ‘Blue collar’ workers travel longer distances to work and show the highest levels of dependence on private motor vehicles; ‘white collar’ workers have the lowest car dependence and greatest use of public transport and travel relatively short trip distances. ‘Pink-collar’ workers have the shortest median commutes. This is in line with previous research on Australian households showing that women often take work closer to home to be closer to schooling and childcare.