Search

Purpose This paper aims to extend the known boundary conditions of the negative binomial distribution (NBD) model, and to test the applicability of conditional trend analysis (CTA) – a key method to identify whether changes in overall sales are accounted for by previous non-buyers, light buyers or heavy buyers – in industrial purchasing situations.Design/methodology/approach The study tested the NBD model and CTA in an industrial marketing context using a 12-month data set of purchases from an Australian supplier of a range of industrial plastic resins.Findings The purchase data displayed a good NBD fit; the study therefore extends the known boundary conditions of the model. The application of CTA provided second-period purchasing frequency estimates showing no significant difference from actual data, indicating the applicability of this method to industrial purchasing.Research limitations/implications Data relate to just one supplier. Further research across several industries is required to confirm the generalizability and robustness of NBD and CTA to industrial markets.Practical implications Marketing decisions can be improved through appropriate analysis of customer purchasing data. However, without access to equivalent competitor data, industrial marketers are constrained in benchmarking the purchasing patterns of their own customers. The results indicate that use of the NBD model enables valid benchmarking for industrial products, while CTA would enable appropriate analysis of purchases by different classes of customer.Originality/value This paper extends the known boundary conditions of the NBD model and provides the first published results, indicating the appropriateness of CTA to predict purchasing frequencies of different industrial customer classes. [ABSTRACT FROM AUTHOR]

Purpose - This study responds to the call of Fader and Hardie for more research on buyer behaviour toward stock keeping units (SKU). This paper aims to examine whether different SKU-based product variants appeal to buyers with different demographic characteristics. Design/methodology/approach - This study examines the product variants (such as size, formulation, type) of a range of brands in six consumer goods categories. The authors calculate and compare the market share of each variant within each demographic group. If a variant has a higher market share within a specific demographic group than the overall average, this indicates segmentation at the product variant level. Findings - The findings show that there are many differences in the market shares of product variants among different demographic groups of buyers. The largest differences are found extensively within the age and employment status variables. Originality/value - Functionally different product variants tend to draw different demographic-based segments of buyers, which has not been previously shown. [ABSTRACT FROM AUTHOR]