The Indian Energy grid is growing rapidly and there is a large simulation to improve not only the grid reliability, but also provide power for all by 2027. To this aim the Government of India has launched the Restructured Accelerated Power Development Program (RAPDRP). In India, residential loads contribute to about 27% of the total power consumption, and hence understanding the residential power consumption is a key stepping stone to improving the performance of the grid and optimizing energy usage via dynamic load management like demand response programs. While there is a lot of prior-art related to short and long term forecasting residential loads, similar models are still very limited in the Indian context. The Indian power grid is a complex eco-system, where demand and consumption patterns are influenced by weather, socio-economic status, geographic location, political events to name a few. Hence, it is difficult to build a model for energy forecasting at residential level. This paper is an attempt to build a residential forecasting model depending on the socio-economic factor and geographical location. To this aim, in this paper we first discuss the influence of socio-economic status on the energy consumption in urban and rural area’s. The socio-economic status includes number of earning members of the family, age, gender and profession etc. All these factors influence the number of devices within a home, which in turn impacts the overall energy consumption. Based on some of these observations, recommendation on modeling approaches are made to enable future data driven research into the energy consumption at residential level in India. This can further be used to enable smart grid technologies, especially from a smart demand, response perspective.