Thesis (PhD)--University of South Australia, 2013. Includes bibliographical references (pages 72-84) The negative binomial distribution (NBD) has been widely used in marketing for modelling purchase frequency counts, particularly in packaged goods contexts. A key managerial use of this model is Conditional Trend Analysis (CTA) - a method of benchmarking future sales based on past performance utilising the NBD conditional expectation. CTA allows brand managers to identify whether the increased sales in a second period are accounted for by previous non-buyers, light buyers or heavy buyers of a brand. By comparing the actual sales during the growth period with the expected sales predicted by the conditional expectation of the NBD model under the stationary condition (i.e. the no change condition), the manager is able to identify the sources of growth. This thesis proposes a method to identify the mechanism of change. The method is based on the distribution of changes in buyer purchasing behaviour in two sequential time periods. The distribution of changes describes the stochastic nature of changes in purchase frequency: some buyers purchase the brand one, two, three… x units more, some buyers purchase less, and some others purchase the same amount from one time period to another. Thus, the method identifies those consumers who change their buying behaviour from those who do not change; and those who make small changes from those who make large changes. Importantly, the method creates theoretically expected benchmarks of the extent of changes in purchasing behaviour. Comparison between the observed data and the predicted distribution of changes allows brand managers to determine if a sales increase or decline is due to a small shift in purchase propensity of a large group of buyers or a big change in purchase propensity of a small group of buyers. This thesis derives the distribution of changes for the negative binomial distribution and the Poisson lognormal distribution. Practical examples of the method are also presented.