We present a robust methodology for aggregating Quality of Service (QoS) and Quality of Experience (QoE) scores across multiple criteria in settings where the relative importance of individual metrics (i.e., weights) is unknown or ambiguous. Building on recent advances in relatively robust multicriteria decision theory, we define a Robust Aggregate Score (RAS) based on the worst-case performance ratio with respect to all admissible weight configurations. The method is weight-agnostic, invariant to rescaling of individual metrics, and accommodates criteria with both positive and negative preference direction. We illustrate the approach in the context of video-streaming service evaluation and demonstrate how it enables interpretable and defensible rankings across heterogeneous quality indicators. The proposed framework is broadly applicable to quality assessment tasks that require reliability under weight uncertainty.