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This paper aims to present an approach to detect interrelations among product categories, which are then used to produce a partition of a retailer’s business into subsets of categories. The methodology also yields a segmentation of shopping trips based on the composition of each shopping basket.

This work uses scanner data to uncover product category interdependencies. As the number of possible relationships among them can be very large, the authors introduce an approach that generates an intuitive graphical representation of these interrelationships by using data analysis techniques available in standard statistical packages, such as multidimensional scaling and clustering.

The methodology was validated using data from a supermarket store. The analysis for that particular store revealed four groups of products categories that are often jointly purchased. The study of each of these groups allowed us to conceive the retail store under study as a small set of sub-businesses. These conclusions reinforce the strategic need for proactive coordination of marketing activities across interrelated product categories.

The approach is sufficiently general to be applied beyond the supermarket industry. However, the empirical findings are specific to the store under analysis. In addition, the proposed methodology identifies cross-category interrelations, but not their underlying sources (e.g. marketing or non-marketing interrelations).

The results suggest that retailers could potentially benefit if they transition from the traditional category management approach where retailers manage product categories in isolation into a customer management approach where retailers identify, acknowledge and leverage interrelations among product categories.

The authors present a fast and wide-range approach to study the shopping behavior of customers, detect cross-category interrelations and segment the retailer’s business and customers based on information about their shopping baskets. Compared to existing approaches, its simplicity should facilitate its implementation by practitioners.

In recent years there has been a marked increase in the consumption of bottled wine in the United States. Associated with this phenomenon, there has been a substantial rise in the number of vineyards from foreign countries entering this competitive market. The study examines the factors that influence wine prices. Specifically, the article proposes that the country of origin, the perceived quality and the varietal of the wine have an effect on wine price in favour of countries with greater wine traditions. These premises were tested by means of a multiple regression model estimated using a sample drawn from the North American market. The study concluded that this market recognises differences in country of origin, quality and varietal. Specifically, these factors significantly influence wine prices, with price premiums being awarded to wines of varietal Pinot and to wines produced in France.