The aim of this study was to analyze the electricity consumption of individual households in three different districts of the city of Winterthur, Switzerland. Furthermore, the effects of socio-economic and socio-spatial data on the households’ electricity consumption were investigated. On one hand the basis of the data were smart meter devices from the three accommodations, which were measured quarter-hourly from July 2012 to February 2016. Cluster analysis was applied to build consumer segments with similar load profiles. On the other hand, the city of Winterthur collects data about the socio-economic as well as the socio-spatial status of the utility’s clients. This data was edited and related with the electricity consumption data. In a first step, statistical key figures were calculated from the electricity consumption data, to find out more about the conduct of the electricity consumption. Additionally, a multi-dimensional scaling of the key figures was applied, to evaluate the context of the key figures. Finally, the effect of the socio-economic and socio-spatial data was investigated with additive regression models. The results reveal that the factors household size, living area and the heating of warm water have a significant effect on the electricity consumption. Another outcome of the present study shows that customers at the age of 30-65 years use more often the moderate tariff in the night to save money. These and further results shall serve to provide recommendations to the city of Winterthur as well as to its utility in order to better design load shifting and power saving interventions.