DATA ANALYTICS FOR RETAIL LAYOUT DECISONS

Abstract

There is hidden information locked up in the huge of data of the companies' databases. The
unidentified information is potentially important for the companies’ success. The relations
among the products of the retailers can be efficiently extracted from large retail databases which
effects the sales and profitability. The operations managers can alter both with overall
arrangements of the store and the allocation of the space to various products with this hidden
information gathered by the data mining analysis. In this paper association rules are applied to
the data set and rule sets are gathered to achieve a better layout and shelf arrangement for the
retailer. Layout has strategic importance to a firm. Placement of the power items which have a
very high exposure rate, maximize profitability per square foot of the floor space.