Computational studies of semantic change are often wide in scope, aiming to capture and quantify semantic change in language at large in a data-driven, ‘hands-off’ way. Case-driven, corpus-linguistic studies of semantic change, by contrast, generally aim to tackle questions about the development of specific linguistic phenomena. Due to its narrower scope, case- driven research is more restricted in terms of the data it may employ, and at the same time it requires a more fine-grained description of the targeted linguistic developments. As a result, case-driven studies face particular methodological challenges that are not at play in more wide- scoped approaches. The aim of this paper is to set out a ‘hands-off’ computational procedure to study specific cases of semantic change. The case we address is the development of the phrasal expression to death from a literal, resultative phrase (e.g. he was beaten to death) into an intensifier (e.g. We were just pleased to death to see her). We deploy hierarchical clustering algorithms over distributed meaning representations in order to capture the evolution of the semantic space of verbs that collocate with to death. We then describe the arising diachronic processes by means of monotonic effects, providing a more accurate picture than customary linear regression models. The methodology we outline may help tackle some common challenges in the use of vector representations to study similar cases of semantic change. We end the discussion by pinpointing (remaining) challenges that case-driven research may encounter.