Análise do Impacto Visual da Montra no Comportamento do Consumidor Utilizando Ferramentas de Data Mining

Abstract

Data Mining and Knowledge Discovery from Data are tools that have attracted a great deal of attention in recent years, since every day the amount of data stored increase and tall his data is crucial to management decisions. The goal of the present dissertation is to apply the data mining and the Knowledge Discovery from Data to the analyses of the power that a store window may have to pick up potential buyers. So this work will use the classification to find a model that describes and distinguishes data classes. This model will be represented in the form of decision trees. With this method we will be able to analyze how the behavior of the potential buyers is a consequence of the store window: we want to know if a person goes into the store and buy products as a consequence of the influence of the store window. The data that will be analyzed was collected in the sales season and when the store already presented products of the new season (Fall-Winter). So we also pretend to analyze if the store window as different influence in the potential buyer in this two different moments of time, were different collections are presented in the store. With this Job we will contribute for a better knowledge of the store window as an important instrument of communication, available for all managers of the retail industry, and so help them to obtain the best profitability possible with this instrument.