Market delineation is a fundamental tool in modern antitrust analysis. However, the definition of relevant markets can be very difficult in practice. This preliminary draft applies a new methodology combining a simple price correlation test with hierarchical clustering -a method known from machine learning- in order to analyze the competitive situation in the German retail gasoline market. Our analysis reveals two remarkable results: At first, there is a uniform pattern across stations of the same brand regarding their maximum daily prices which confirms the claim that prices are partly set centrally. But more importantly, price reactions are also influenced by regional or local market conditions as the price setting of gasoline stations is strongly affected by commuter routes.