Segregation, defined as the degree of separation between two or more population groups, helps to understand a complex social environment and subsequently provides a basis for public policy intervention. To measure segregation, past works often propose indexes that are criticized for being over-simplified and over-reduced. In other words, these indexes use the highly aggregated information to measure segregation. In this paper, we propose three novel indexes to measure segregation, namely: (i) Individual Segregation Index (ISI), (ii) Individual Inclination Index (III), and (iii) Overall Behavioural Index (OBI). The ISI index measures individuals' segregation, and the III index reports the individuals' inclination towards other population groups. The OBI index, calculated using both III and ISI index, is non-simplified and not only recognizes individuals' connectivity behaviour but group's connectivity behavioural distribution as well. By considering commonly used Freeman's segregation and homophily index as baseline indexes, we compare the OBI index on real call data records (CDR) dataset of Estonia to show the effectiveness of the proposed indexes.