The recent deployment of smart metering networks is opening new opportunities for advancing the design of residential water demand management strategies (WDMS) relying on improved understanding of water consumers’ behaviors. Recent applications showed that retrieving information on users’ consumption behaviors, along with their explanatory and/or causal factors, is key to spot potential areas where targeting water saving efforts, and to design user-tailored WDMS. In this study, we explore the potential of ICT-based solutions in supporting the design and implementation of highly customized WDMS. On one side, the collection of consumption data at high spatial and temporal resolutions requires big data analytics and machine learning techniques...