Interviewer performance with respect to convincing sample members to participate in surveys is an important dimension of survey quality. However, unlike in CAPI surveys where each sample case 'belongs' to one interviewer, there are hardly any good measures of interview performance for centralised CATI surveys, where even single contacts are assigned to interviewers at random. If more than one interviewer works one sample case, it is not clear how to attribute success or failure to the interviewers involved. In this article, we propose two correlated methods to measure interviewer contact performance in centralised CATI surveys. Their modelling must take complex multilevel clustering effects, which need not be hierarchical, into account. Results are consistent with findings from CAPI data modelling, and we find that when comparing effects with a direct ('naive') measure of interviewer contact results, interviewer random effects are largely underestimated using the naive measure.