Current transport systems are not sufficiently sustainable and equitable, making the development of effective interventions indispensable. An intervention's effectiveness increases when tailored to a specific target group. To facilitate this, mobility types available in a population need to be identified. To date, no segmentation study has profiled a nation's mobility behavior both geographically (spatial type of household location) and socio-demographically. The present study aims to fill this gap by using a uniquely vast data set to segment a representative sample of the German population into distinct mobility types. The data (N = 86,498) was derived from MiD, a national survey on citizens’ everyday mobility behavior commissioned by the German Federal Ministry of Transport and Digital Infrastructure. It includes a broad array of variables, among them information on general mobility behavior and equipment in conjunction with mobility behavior on a reference date, socio-demographic data, as well as psychographic data such as satisfaction with transport modes or tech-savviness. The latter has increased in importance as technology-based mobility options such as sharing services have emerged in the recent years. By means of an exploratory procedure incorporating principal component analysis followed by K-means cluster analysis, eight distinct, stable mobility profiles were extracted. The results partly overlap with previous research but substantially extend the body of knowledge existing in the field. The description of the profiles and allocated interventions offer recommendations for the development of effective, nation-wide interventions and policies to enable the establishment of a sustainable and equitable mobility system.