Abstract
Residential water demand is strongly shaped by showering behaviour, yet quantifying drivers at the event level remains rare. We first explored and identified key patterns across 8550 sensor-logged showering events from 319 German households collected during winter. We then combined this high-resolution smart-meter data with time-stamped post-shower surveys to analyse shampoo-shower duration. The Gamma mixed model (14 predictors spanning demographics, context, in-shower behaviour and hair characteristics) explained 68.4% of deviance (AIC = 4281.6). Behavioural predictors showed the clearest associations: showers with two or more shampoo applications were 27% longer than those with one, while showers with three or more water pauses were 28% longer than those with one. Some contextual and demographic predictors also mattered: soft water areas were linked to 23% longer durations, and younger/mid-age adults had durations up to 31% longer than adults 50+. Other factors (gender, employment, household composition/size, home type, bills responsibility and most hair characteristics) showed small or uncertain effects after adjustment. Findings demonstrate how smart metering, event-level behavioural data and robust modelling can reveal actionable levers for demand-side management, behavioural interventions and product design.