Consensus reaching is a key issue in group decision-making, because conflicts of interest among groups are common. Democratic consensus refers to achieve a soft consensus among collective as well as ensure the effective participation and satisfaction of individuals. Multi-person multi-criteria large scale decision making (MpMcLSDM) usually involves a huge number of decision makers (DMs/participants), and different DMs usually have different interests. Thus, how to effectively manage individuals to promote democratic consensus is a current research challenge. To do that, this research develops a democratic consensus reaching process (DCRP) for MpMcLSDM problems. In the proposed approach, a clustering method that considers both the opinion similarity and individual concern similarity of DM is firstly given to decrease the complexity of MpMcLSDM issues. Subsequently, we propose to assign equal initial weight to each cluster to protect the interests of minorities. Meanwhile, a consensus contribution-based dynamic interactive weight updating method is implemented in the DCRPs to promote a high level of democratic consensus. Besides, a compromise degree-based consensus feedback strategy is developed to improve the efficiency of the DCRPs. The proposed feedback mechanism effectively considers the individual concern and adjustment willingness of DMs in the DCRPs. Finally, a case study and some comparisons are given to show the effectiveness and innovation of this research.