Information retrieval is a research field strongly rooted in experimentation where new and better ways to measure and interpret the behavior of a system are key to scientific and technological advancement. This talk focuses on an innovative visual analytics environment which aims at easing and making more effective the experimental evaluation process. This environment supports and improves two typical phases of the experimental evaluation process, namely performance analysis and failure analysis. These analyses are conducted also via a new metric called Cumulative Relative Position (CRP) which measures the weariness caused to the user by the ranking of a system under exam. User weariness is expressed as the amount of misplacement in the rank position of relevant documents, as this pairs with the idea of having forced the user to deviate from an ideal path which would have provided him/her with the expected flow of information causing no weariness.