Abstract This paper presents an incentive based framework for demand response scheduling in smart distribution networks with commercial, residential and industrial load sectors using designated cloud storage in cyber physical cloud based smart distribution system. The proposed approach consists of a two stage procedure where dual objective problem is modeled to achieve both responsive load agent (RLA) economic benefits as well as distribution system operator (DSO) preferences. The two stage coordinated scheduling of RLAs with DSO network operation preferences is carried out by demand response aggregation agent (DRAA) through incentives. The cloud based information exchange between different stakeholders provides the necessary communication at different stages of responsive load scheduling. The concept of private, shared and community clouds are incorporated into the cyber physical cloud based DAM framework proposed in this work. The first stage scheduling of responsive loads is carried out by RLAs with electricity payment minimization objective looking into the tariff structure. Whereas, the second stage scheduling is carried out by DRAA in which incentives are offered to RLAs for the deviation from personalized schedules of first stage. The customer characterization and behavior (risk averse, incentive preferences etc.) of scheduling the responsive loads is considered through incentive range based clusters. The proposed DRAA coordinated DR scheduling framework is simulated using IEEE 37 bus distribution test system with commercial, residential and industrial sectors. The impact of stage 1 and stage 2 scheduling of responsive loads is analyzed with respect to system performance indices such as total operational cost, load factor, total network losses etc. The sensitivity analysis is performed to examine the impact of weightage assignment to DSO and RLA objectives on system performance aspects. The proposed DRAA coordinated two stage framework has shown considerable improvement in techno-economic aspects of responsive load scheduling in distribution network that can be appended to real world applications at distribution level/retail markets.