Toward a new supermarket layout: from industrial categories to one stop shopping organization through a data mining approach

This paper proposes a new grocery store layout based on the association among product categories. The very first grocery stores displayed their products in an industrial approach, which have produced the present day grocery store layouts based on “sectors” as fruits, vegetables, magazines, cds, and so on. This approach is company oriented and it fails to respond to the needs of the time-pressured consumer. Some retailers are trying to move from this organization to something new, and are struggling to become ̈consumer oriented ̈ in their layout approach. For example, Tesco has rethought their store layout with ̈plan-o-grams ̈ to try to reflect local consumers needs (Shahidi, 2002). Other French retailers have used consumption universe layouts to make it easier for consumers to find their product in a more hedonic environment. One possibility to do so is to make the store layout construction through the introduction of the market basket analysis, improving one stop shopping experience. This allows retailers to cluster products around the consumer buying habits, avoiding time search spending, and then creating a very strong appeal for today’s busy consumers. We use 1,7 million transaction database to measure the buying association and to create a category correlation matrix. Then we applied the multidimensional scale technique to display the set of products in the store space. We will imply that the buying association, measured through the market basket analysis, is the best way to find product organization that are better suited to one stop shopping.