CASPER : cross-platform automated space planning engine for retailers

Abstract

Retail space planning is an accurate and complex process affecting the overall performance of a retail environment. Such task, confronting large retailers consisting of huge malls and hypermarkets, appears infinite in the absence of a complete automated process, starting from the store plan generation, passing by the optimal product assortment and finishing with the product-to-shelf allocation problem. Moreover, the ever-changing factors affecting the retail space planning process, such as merchandising rules, competitive strategies and consumer behavior require continuous follow-up and optimization of the overall process. Based on the previous requirements, we propose an automated engine which initiates by generating a store plan based on the results of the market basket analysis, selects the optimal item assortment for each item category and finally allocates the resulting items on their respective shelves. Moreover, a service oriented architecture is proposed to ensure interoperability between the engine and the corresponding external modules.