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Tuning the multivariate Poisson mixture model for clustering supermarket shoppers, presented at: Statistical Modelling and Inference for Complex Data Structures, poster paper, Louvain-La-Neuve (2002)

by T Brijs, D Karlis, G Swinnen, K Vanhoof, G Wets
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Retail Market Basket Analysis: A Quantitative Modelling Approach

by Tom Brijs , 2002
"... Market basket analysis is a generic term for methodologies that study the composition of a basket of products (i.e. a shopping basket) purchased by a household during a single shopping trip. The idea is that market baskets reflect interdependencies between products or purchases made in different pro ..."
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Market basket analysis is a generic term for methodologies that study the composition of a basket of products (i.e. a shopping basket) purchased by a household during a single shopping trip. The idea is that market baskets reflect interdependencies between products or purchases made in different product categories, and that these interdependencies can be useful to support retail marketing decisions. Recently, a number of advances in data mining (association rules) and statistics (mixture models) offer new opportunities to analyse such data. In this dissertation, the focus is therefore on the development and application of such techniques for two specific problems where product/category interdependencies play an important role, i.e. in product selection and in behaviour-based customer segmentation. From a marketing perspective, the research is motivated by the fact that some recent trends in retailing pose important challenges to retailers in order to stay competitive. In fact, on the level of the retailer, a number of trends can be identified, including concentration, internationalization, decreasing profit margins and an increase in discounting. This growing trend of concentration and increase in scale has a significant impact on the relation with the consumer and presents important challenges for today’s retailers, including the battle against decreased customer service and loyalty. Indeed, the rise of large retail stores and the fact that customers are getting used to self-service resulted in a loss of personalized customer service and creates new challenges to gain and keep customer loyalty, for instance through personalization. Indeed, in today’s large grocery stores, most consumers do not know the manager or checkout clerks, and store personnel hardly know their customers. Additionally, some trends on the level of the consumer can also be identified, such as a decrease in loyalty and a slowdown in consumer spending. Indeed, three out of four customers shop at multiple supermarkets and the average loyalty towards the first store of preference is only about twenty percent. With respect to
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