The authors give a stepwise detail of questionnaire design, planning and implementation of a socio-economic survey, digitization of collected data and principal components analysis (PCA) of asset variables. This survey of 400 households using biogas as a source of renewable energy was conducted in three different rural settings of Nepal during September to November 2010. Biogas plants running mostly on cattle dung can to some extent make up for energy scarcity with up to 16 hours power outages from the national grid in the lean season. Out of 467 variables studying various socio-economic and performance parameters in the consumer profile database 47 proxy asset variables are identified. They indirectly estimate the socioeconomic status of the family. In an agrarian economy where many economic transactions take place outside the market, these methods provide more accurate data. The socio-economic status is thus objectively quantified. In developing agrarian economy socio-economic status is a very sensitive topic and direct questions to the respondents are least likely to furnish correct data. The data on assets ownership (television, refrigerator, motorcycle, bicycle etc) and type of house (type of house, type of toilet, type of water source etc) owned called assets indicators are used in constructing asset index by using PCA. The dimension is reduced to ten orthogonal variables explaining 60 percent of the variability. This paper aims to stimulate interest in the interdisciplinary applications of statistical methodologies to problems from renewable energy in general and the application of PCA in differentiating the socio-economic status in particular.