The practices by which actions are accomplished in interaction are invariably sensitive to context, as it is not only through their composition but also their position that they are recognisable as practices. This means that practices are not readily identifiable through straightforward searches for linguistic units in large datasets of spoken interaction. In this paper, the authors propose that through an explicitly combinatorial approach to search, the procedural basis of which is grounded in a specific array of compositional and sequential features associated with the candidate practice in question, we can more readily find potentially relevant examples of that phenomenon across large tracts of data, which can then be subjected to rigorous sequential analysis. The authors argue that this combinatorial search procedure enables us access to data from multiple different sources. The paper illustrates this combinatorial approach through an analysis of laughter that co-occurs with lapses in the ongoing progressivity of talk-in-interaction in various conversational settings. Careful analysis of post-lapse laughter in a dataset of initial interactions suggests that such laughter often occurs subsequent to silences greater than 500 ms and co-occurs with speaker change. The authors use these compositional and positional features to construct searches across different spoken corpora held within the Australian National Corpus in order to identify further possible examples of this candidate practice, thereby demonstrating the relevance of this approach for accessing data in conversation analytic research. The authors suggest that the advantage of an explicitly combinatorial approach to identifying practices, and the actions accomplished through them, is that it enables us to go beyond analysing them in single, isolated datasets, as well as opening up hitherto understudied practices for further investigation.