Figuring out a movie to watch in a group setting induces great stress for many people. They worry that if they choose the wrong movie, the hang out will end up being a waste of time as people are left unsatisfied. This leads to people wasting a lot of time, trying to figure out what movie to watch that will satisfy everyone's preferences.
How might we create a feature that can be used to help groups choose a movie to watch and thus, save time and reduce stress?
I designed a feature that recommends movies quickly and easily while considering individual preferences and tastes. This manifested in a mobile app and companion TV app that uses a questionnaire to suggest movies.
I conducted 5 interviews with participants who regularly watch shows/movies. I asked questions regarding motivation, decision processes, and watching habits in regards to shows and movies respectively. I also did a survey via Google Forms which had 22 participants.
I found that choosing a movie to watch in group settings was the biggest and most common pain point for those watching movies.
“It feels like it has to reach expectations for both people because you’re spending your weekend watching it and like you know, time is money”
Casey wants a solution to finding good movie recommendations when she hangs out with her friends. They waste so much time trying to find a movie that everyone wants to see.
This feature is intended as a PWA (progressive web app) so that friends are not required to download the app, saving time. There are two main flow types: the first only uses the mobile app and the second type uses both the mobile and TV app in tandem (able to watch trailers together).
I determined feature roadmap based on user interview insights.The questionnaire, the star of the task flow, was designed to be quick to complete but consider all the important factors involved in choosing a movie. For instance, a question regarding rewatching movies was included as this was a factor some participants felt very strongly about.
I developed a UI Kit, drawing inspiration from other products within the entertainment industry like Hulu and HBO Max that use gradients.
I used Figma to develop the high-fidelity wireframes. To illustrate my design thinking, here are different screens from the user flow.
The testing was conducted with three participants who all identified having difficulty choosing movies in group settings. The participants were directed to host a session and complete the questionnaire to receive movie recommendations.
An affinity map was created to summarize points made by participants during usability testing. As a huge win, all the participants found that the questionnaire was quick to complete with no confusing questions! Additionally, responses confirmed that having a TV companion app was helpful to watch trailers together. They also liked the ability to have a self-session for individual use.
I entered this project thinking that research would show participants wanting to keep track of movies/shows that they want to see or have seen, similar to Goodreads. However, research proved me wrong, giving me an opportunity to learn how it's important to not have a pre-conceived solution before conducting research.
Due to time constraints, I didn’t redo my competitive analysis or provisional personas after user research and survey insights changed the focus of the project. I could’ve done more secondary research to help inform my designs.
Another round of usability testing should be conducted on the newly added screens (the tie-breaker, the screens with ratings) to see if they are usable and intuitive for our users. Also, there should be research done to see if users will want to revisit questions in the questionnaire. Right now, they could use the progress bar at the top to go back to the previous questions but this may not be intuitive enough. Also, the progress bar doesn't currently communicate the question content of previous questions answered.