RNAi screening in mammalian cells has become a valuable method to identify and describe genetic relationships in both basic biology and disease mechanisms. Multiple efforts are underway to standardize how RNAi screening data are reported, including establishing experimental criteria for defining a validated hit from a screen, and the extent to which the primary screening data themselves are reported. These discussions have identified several key areas that require consistency, or at least understanding, before RNAi screening data can be used generally. Successfully addressing these targeted areas would broaden the use of RNAi screening data beyond advancing one or a few hits into validation experiments, to enable verification of primary screening data, and to facilitate comparisons between sample groups based on screening profiles. Areas for improving RNAi screening include general guidelines for validating hits from screens, the creation of standardized reporting structures for RNAi screening data, such as Minimum Information About an RNAi Experiment (MIARE), statistical methods for analyzing screening data that explicitly account for differences between screening RNAi reagents versus small molecules, and technical improvements to RNAi screening that improve the analysis of gene knockdowns, including multiparametric approaches, such as high-content screening. This review will discuss how these approaches can improve RNAi screening data at the community level and for an individual researcher trying to manage an RNAi screen.