Prioritizing software requirements helps to determine which requirements that are most important,and in which order requirements should be developed and tested throughout the development lifecycle. By prioritizing the requirements, software engineers can put focus on a subset of all requirements, and implement these in a particular release. This thesis aims to analyze two ratio scale prioritization techniques in a controlled experiment.The experiment was designed to compare time consumption, scalability, accuracy, ease of use, and ease to learning between the two techniques. All these evaluation parameters are combined together to find out which technique is more suitable to use when prioritizing software requirements. The two techniques investigated in the study presented in this thesis are: Analytical Hierarchy Process (AHP), which is based on pair-wise comparisons; and Cumulative Voting (CV) which is based on distributing points between requirements. The results of the experiment indicate that CV is less time consuming than AHP, which makes it more scalable. Further, CV is regarded as easier to use, and easier to learn than AHP. In addition, the results show that CV is more accurate than AHP while measuring the perceived accuracy. However, no conclusions could be made regarding actual accuracy due to misinterpretations by the study participants.