Carbon Dioxide Removal (CDR) concepts are crucial for achieving ambitious climate targets by removing carbon dioxide from the atmosphere. Nonetheless, their large-scale deployment is hindered by a wide range of uncertainties, particularly substantial financial barriers. To address this challenge, we employ a comprehensive sensitivity analysis (Variance-based sensitivity analysis- Sobol) to identify key cost components and removal drivers, which can be exploited to develop successful deployment strategies. Our analysis focuses on Bioenergy with Carbon Capture and Storage (BECCS) in Germany. We utilize a detailed techno-economic optimization model (BENOPTex) to assess the impact of various factors, including technological advancements, feedstocks and land availability, and policy incentives such as carbon pricing. In the reference case, the model showed a CO2 removal of ~ 55 million tons for Germany at an average carbon price of 120 €/tCO2. We run various parameter variations and cluster the results in robust and more uncertain contribution of different technologies. The results show that the most important factors influencing CDR deployments are: the availability of biomass for BECCS use, the CO2 price, the availability of land for cultivating energy crops, and the cost of CCS technologies.