This article describes the analysis of heterogeneous market data. For this purpose, the most relevant methodological aspects are discussed and analyses using a hierarchical linear model and multiple regression are presented. In the first step, the applied data set is presented, and the assumed hierarchical two-level structure is shown. The data are then prepared for the analysis. The data are checked for outliers, a multicollinearity check is conducted, a new variable introduced, missing values are replaced by estimated values, a transformation procedure is conducted in order to obtain normality, the data are aggregated for each hierarchical level and a sample size test is performed. The results of both methods are discussed. Finally, it is concluded that whereas the application of a hierarchical linear model appears to be one option, a multiple regression analysis can be employed instead if the quality of the data, especially the sample size, is not sufficient.