The purpose of this PhD thesis is to explore the efficiency of psychographic segmentation of social media users using their digital footprints. The Conceptual model was set for better understanding of the relationship between variables. To test the model, research will be conducted in two parts. First, using a survey method it will test personality traits, and as a result it will generate a user personality trait-reaction „Like“ matrix. This matrix will be unique for this economic, cultural and political region, and it will allow marketing experts to make psychographic segmentation of their segment without using a Personality Item Pool. Second part of this research will be conducted using some kind of experiment on social media Facebook users from Croatia. Users of Facebook will be presented with ads tailored to certain personality traits. To make appropriate segmentation results, the first part of the research will be used. Users who score high on certain personality traits will be exposed to ads tailored to that personality trait, as well as ads tailored on one of four remaining personality traits. Efficiency will be observed when personality traits meet the ads tailored to that personality trait. The data will be analysed using statistical methods and procedures. Scientific contribution of the primary research conducted for the purpose of this PhD thesis is presented in building a personality trait-reaction „Like“ matrix, as well as, for the first ever demonstrated in the world, a unique personality trait- category of reaction „Like“ matrix and category in which Facebook classifies certain personality trait-reactions „Like“. Also, the reaction „Like“ matrix will be introduced as a type of digital footprint of social media users in this geo-economic region. For the first time, the efficiency barrier of psychographic segmentation efficiency of all personality traits will be observed using this type of digital footprint, while also investigating the limit of social media users’ efficiency along with contemplating the moderator effect using age, gender and geo location of social media users as variables. The entire research will confirm the efficiency of psychographic segmentationof social media users using their digital footprints.