Marko Svetina, Jože Zupančič Merkur d.d. C. na Okroglo 7, Naklo, Slovenia marko.svetina@merkur.si University of Maribor, Faculty of Organizational Sciences Kidričeva cesta 55a, Kranj, Slovenia joze.zupancic@fov.uni-mb.si Abstract: This paper investigates market basket analysis as an important component of analytical CRM in retail organizations. It presents the case of the company Merkur d.d., Slovenia, a trading company dealing in items for home improvement. The business intelligence system and market basket methodology used in Merkur are described. Use of market basket analyses in Merkur is explained and analysed. In particular, the paper addresses issues such as sales promotion campaigns, placement of goods in retail stores, education of salespeople, offering system solutions and segmentation of customers. The discussed topics are explained using practical examples and guidelines for adequate business decisions. Our study demonstrated that market basket analyses are useful for Merkur, but a better direct marketing strategy must be defined and implemented. Keywords: business intelligence, market basket analysis, cross-sell, up-sell, related sales, retail, merchandising, sales campaign, CRM
1 Introduction
One of the challenges for companies that have invested heavily in customer data collection is how to extract important information from their vast customer databases and product feature databases, in order to gain competitive advantage. Market basket analysis (also known as association rule mining) is one of the data mining methods (Berry and Linoff, 2004) focusing on discovering purchasing patterns by extracting associations or co-occurrences from a store’s transactional data. Several aspects of market basket analysis have been studied in academic literature, such as using customer interest profile and interests on particular features of the product for the product development and one-to-one
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