Data mining of transactional data for sales of dairy products

The purpose of this article is to find out the most important factors for sales of dairy products. Transactional data for sales are used. This article is published for the first time. The results of the analysis will show how transactional data may be used for data mining. SPSS is used to analyze the data. Statistical methods (such as independent samples t-test, Chi-square tests, Mann-Whitney U test, one-way ANOVA test) are applied to find dependencies. We suppose that the quantity of sales depends on the year, month, group, item and average price. At the end of the study we found out that “year” and “group” are factors which mostly influence the quantity of a sale. Factors “month”, “item” and “average sale price” do not affect the quantity of a single sale. Mathematical formulas are derived to predict the quantity of a future sale on the basis of independent variables such as year and group of stock.