In Japan, the popularity of DIY stores has been growing rapidly. In comparison with typical large retail chain stores, DIY stores have a wider variety of products mostly with lower prices and broader store spaces. In many cases, they are located in suburban areas with huge parking lots. Because of these unique features, customer behaviors for DIY stores could be quite different from those for ordinary large retail chain stores, and some special attentions may be needed for sales promotion. The purpose of this paper is to establish a framework for developing recommendation engines for DIY stores so as to enhance their sales. More specifically, useful recommendation rules are derived from two different perspectives: a vertical approach from a point of view of pairs of products across product categories with significant sales contributions, and a horizontal approach focusing on excellent customers who are ranked in a top segment in terms of both the purchasing amount of money and the purchasing volume of products. Assuming that certain marketing campaigns are conducted along the derived association rules, a computational procedure is developed for assessing the economic impact of each of such recommendation rules.
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