To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to actively adjust the timing, mode, and frequency of their appliance usage to curtail or shift in time energy consumption. Therefore, overlooking the dynamic intricacies of these adjustments and assuming uniform consumption patterns across households can lead to inaccurate and untargeted recommendations in DSM programme design. This study aims to contribute to DSM research by introducing a novel methodology for analysing energy demand and flexibility. Our primary goal is to uncover patterns in volume, timing, and mechanisms of demand management across the population. Drawing insights from engineering and social science studies, we conducted a comprehensive quantitative survey (N = 1188) focusing on laundry and dishwashing habits in German households. Employing statistical methods, such as hierarchical clustering, multinomial logistic regression, and analysis of variance, we identify distinct patterns, explore their determinants, and assess variations in load-shifting potential and perceived inconvenience. Our findings reveal three key insights: 1) significant and meaningful patterns can be identified among the large diversity of dishwashing and laundry habits, 2) pattern membership is influenced by multiple and complex factors that resist a narrow categorisation and 3) households with more energy-intensive patterns tend to perceive load-shifting as more inconvenient, revealing a misalignment between flexibility potential and readiness. Importantly, our approach enables the identification of appliance usage patterns easily applicable in energy demand models. Furthermore, by integrating insights from various disciplines, this pattern-oriented methodology can inform more targeted and effective DSM interventions, thereby supporting the transition towards a highly electrified renewables-based energy system.