The behavior of wind turbine wake is unique and has a distinct pattern that often carries crucial information on the nature of wake propagation. This information plays a vital role in dictating the wind turbine wake model and subsequently in the design and placement of multirotor system. In most cases, either analytical or numerical, the representation of wind turbine wake is expressed as a streamwise flow deficit at different downstream locations. Though the result provides valuable information, the representation often lacks three-dimensional characterization, thus ignoring several influential factors that could potentially define the extent of propagation. In this aspect, an in-depth flow field mapping and assessment have been carried out behind a model horizontal-axis wind turbine using stereo particle image velocimetry (SPIV) under low tip speed ratio conditions. The three-component mapping using the time-resolved SPIV data helped to understand the notion of the wake's helical behavior and its relationship with the velocity deficit. Apart from the Gaussian-like (skew) distribution of the streamwise velocity component, the stereo assessment reveals the formation of two opposite crests supporting the helical analogy. Toward the end, a comparative assessment with the existing analytical models have been carried out.