Customer segmentation plays crucial role in hospitality marketing. Identification of the right customer segments allows hotel managers to create the most effective marketing strategies. Transactions are great source of behavioral data that can be used in market segmentation. The goal of this paper is to run cluster analysis over transactional data to identify customer segment, identify the best ones of them and propose suitable strategy for them. Used data were exported from channel management tool and then processed using several non-hierarchical clustering methods of IBM SPSS tool (K-means and TwoStep Clustering). The results show that using transaction data for behavioral segmentation can lead to proper segment identification when strategies are being built.