Quality of Experience (QoE) of applications is highly important sinceapoor application performance and a low QoEmay cause a user to stop using it (e.g., shift to a “better” one), or change the network operator due to misinterpretation of the underlying reason.Assessing video QoE in-the-wild is highly challenging, and the challenges have to be identified earlier to overcome and prevent any circumstances that new comers, e.g., new researchers in the area, may experience. In this thesis, a set of challenges in assessing video QoE in the wild, and user behavior during video streaming, are presented. Ultimate goal of this thesis is to provide newcomers and researchers a practical view on our conducted video QoE studies with real users in the wild. Moreover, the adapted solutions for the challenges are presented. We used a video streaming tool, VLQoE that is able to display and in parallel quantify temporal impairments. A user study consists of auser survey, face-to-face interview, and a data collection via VLQoE. In this thesis, only the results of the first two are presented and we discuss on the challenges.