The popularity of reducing domestic electricity consumption is growing following the decision of several European governments to quit nuclear power in the near future. However, finding out which equipment should be replaced and more importantly which behavior should be modified to reach this goal is not a simple task, since helpful tools are not easy to find or implement. The disaggregation of the global electricity consumption could be achieved in the framework of concepts like the Internet of Things where the monitoring of each appliance is made possible using embedded power sensors. However, the implementation of such solutions in the near future will be very difficult due to the costs generated by the modification of existing appliances. Another more elegant solution to provide people with useful information about their electricity consumption consists in a single recording unit measuring the entire consumption coupled with a system able to disaggregate the appliance load curve. This is better known as non-intrusive appliance load monitoring (NIALM). The aim of this study is to investigate the feasibility of a load curve disaggregation based feedback system for consumer service development. For that purpose, a low-frequency recording unit was developed to record the global electricity consumption of fifty Swiss households. The recorded data, as well as simulated data, have been used to develop and validate a simple appliance detection technique with low computational requirements as this is a key issue for a potential future use in real-time remote feedback systems. This paper shows that the developed disaggregation technique, although simple, provides satisfactorily detection performances and could be used to provide consumers with useful information about their electricity consumption.