The main objective of this paper is to present a set of non-parametric tests that allow the analyst to detect the presence of purchase-event feedback. The principle is to set aside the potential impact of heterogeneity by analysing data at the individual level, i.e. consumer by consumer. The null hypothesis is that each person has a constant, personal, likelihood of purchasing a brand. If this hypothesis is true, then the purchases would be allocated randomly over time. On this basis, distributions can be computed for quantities such as the total time span separating the first and last of a series of purchases, the time between the initial trial and the first repurchase, the time between the initial product trial and the last repurchase. The observed values for these quantities can be then be compared, consumer by consumer, to the hypothesized distributions. Rejecting the hypothesis implies that probabilities are affected by purchase-event feedback and tend to be higher, for a given consumer, just after a purchase. One can combine test results at the individual level (thus avoiding the heterogeneity problem) into an overall assessment of the hypothesis.