Predicting transitions in alcohol buying behaviour

This article uses the Negative Binomial Distribution (NBD) to model alcohol purchase frequency and predict the transitions among non-buyers, light (the bottom 50% of buyers), medium (the middle 30%) and heavy (the top 20%) from 1 year to another. Using purchasing data over 2 years in the United States (49,915 households) and the United Kingdom (9,316 households) including beer, wine and spirits, we find that the NBD accurately predicts these transitions. The model as such provides a useful baseline for evaluating the effects of interventions to reduce heavy alcohol buying. For both ethical and commercial reasons, instead of targeting heavy buyers, companies selling alcohol still can more responsibly strive to increase their sales by acquiring new alcohol buyers as most of them will become light buyers.