With 360° video streaming, the user's field of view (a.k.a. viewport) is at all times determined by the user's current viewing direction. Since any two users are unlikely to look in the exact same direction as each other throughout the viewing of a video, the frame-by-frame video sequence displayed during a playback session is typically unique. This complicates the direct comparison of the perceived Quality of Experience (QoE) using popular metrics such as the Multiscale-Structural Similarity (MS-SSIM). Furthermore, there is an absence of light-weight emulation frameworks for tiled-based 360° video streaming that allow easy testing of different algorithm designs and tile sizes. To address these challenges, we present REEFT-360, which consists of (1) a real-time emulation framework that captures tile-quality adaptation under time-varying bandwidth conditions and (2) a multi-step evaluation process that allows the calculation of MS-SSIM scores and other frame-based metrics, while accounting for the user's head movements. Importantly, the framework allows speedy implementation and testing of alternative head-movement prediction and tile-based prefetching solutions, allows testing under a wide range of network conditions, and can be used either with a human user or head-movement traces. The developed software tool is shared with the paper. We also present proof-of-concept evaluation results that highlight the importance of including a human subject in the evaluation.