Digital spectrographic cross-correlation (SPCC), a technique described by Clark et al. (1987), simultaneously analyses frequency, amplitude and time components of a signal, and returns a single peak correlation coefficient. The procedure is objective and uses all the information in the spectrogram. As such, it is a candidate to replace and/or supplement visual spectrogram comparison and multivariate analysis as the technique of choice for comparing sounds. With the increasing availability of sound analysis software with built-in cross-correlation routines, the procedure is becoming readily available to biologists who may not have extensive knowledge of acoustics. This ease of access increases the potential for misapplication of the technique or misinterpretation of results. To assess the utility of SPCC and to highlight pitfalls that need to be avoided in its implementation, we performed a series of tests designed to reveal the sensitivity of the peak cross-correlation coefficient to a variety of parameters. In general, SPCC provides a good measure of the similarity between simple, continuous signals. However, there is no single best measure of similarity because of the complementarity of frequency and time resolution. More complex signal structures, such as those with overtones or complex vocalizations, will often return misleading coefficients. In all cases, pre-test preparation of signals is of critical importance.