Watchit
Designed a social application to make at-home movie/show watching an easier and more enjoyable experience
Agile Design Process
Working in an agile setting allowed for rapid iteration, testing and feedback
Research
Our initial research consisted of analyzing various social technologies related to movie/ show streaming as well as other apps that do a good job of connecting people with their friends. Some of the apps that we researched and analyzed were Good ol’ games, Youtube, Netflix, Amazon Prime, Disney Plus, and Spotify. This research consisted of looking at customer reviews, interviewing friends and family to understand their experience and opinions on some of these apps, and researching unique features offered on each of the apps.
Key Findings:
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Users being overwhelmed by choice
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Users taking a long time to find something that they like
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Friend’s recommendations have a large impact on their choices and their selection of a movie.
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Contextual Inquiry
Contextual Inquiry Based Interviews
From those initial understandings, we conducted contextual inquiry based interviews with four participants to understand how they choose what to watch and how they navigate their favorite streaming services. We gave them the task of finding a show or a movie to watch on whatever streaming service they please and prompted them to explain their thought process along the way.
Key Findings:
The findings from these interviews aligned with the online research.
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People took quite a while to choose what to watch (ranging from 10-45 min)
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They were overwhelmed with the choices
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They frequently based their final choice on preference and recommendations.
More user testing sessions were conducted throughout the design process
These findings contribute to a less enjoyable movie streaming experience
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Iteration Phases
We designed our prototype in an iterative process. Building a low-fidelity, medium-fidelity then a final product allowed us to conduct user testing sessions, research, and heuristic evaluations between each prototype design. This allowed us to ensure that all of our design choices along the way set out to solve our user problems and all assumptions were addressed.
Problem
Watching shows and movies can be a great way to relax and rewind but many people find it very difficult to quickly find something to watch depending on what they are feeling, what will satisfy all of the individuals watching and what is available on their streaming services. The key problem that we have set out to solve with the use of social technology is:
How might we make at-home movie/show watching an easier and more enjoyable experience?
This problem was a hypothesis that was validated through user testing.
Familiar Functionality
Our design of the app Watchit, draws on familiar functionality from Netflix and Spotify. The combinations of the best aspects of both of these platforms have allowed us to create the best possible experience.
Easy Integration
Our platform allows users to easily integrate all of their streaming services, and find something to watch that suits their mood.
Community
The ability to follow friends and see their ratings allows users to get show or movie ideas from their friends more easily. Making folders allows users to easily group movies that they enjoy and share them with their friends.
Quick Choices
The quiz feature allows users to easily be given shows or movies based on what they are feeling without being bombarded with long lists of choices to choose from.
Low Fidelity Prototype
From all of the research compiled and analyzed, we diverged to create rough wireframes of what we thought an ideal solution would look like. We then brought our ideas together to be critiqued and pulled the best aspects from each design to compile our low fidelity prototype. All of our ideas revolved around creating an app that would allow users to connect their streaming services and follow friends.
The ability to follow friends and see what movies or shows they like and watch was a key finding from our user research and influenced a large portion of our design.
Our design allows users to more easily gather friends’ recommendations and will therefore increase the ease of choosing a movie. Users are able to follow friends, see friends’ folders which they have created, rate the movies which they have seen, see their friends’ ratings, chat with friends and get personalized movie recommendations based on their mood. Users are able to link up the streaming services that they have such as Netflix or Amazon Prime Video so that they are able to search from their complete selection all at once.
Wizard of Oz Testing:
The feedback from our Wizard of Oz testing was used to make various changes in layout and minor functionality. We went through many iterations on colour and UI to come up with a visual design that would best portray the purpose of the app.
Findings:
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Choice overload still remained. More filtering capabilities need to be implemented
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There was confusion around the roles of friends within the platform
Reflection:
This prototype was tested with a few participants to influence the design of the medium fidelity prototype. This testing however was limited and not all assumptions were addressed. If the school project allowed I would have liked to complete more testing before moving onto the next prototype.
Left: Some initial idea sketches and screens from the low fidelity prototype.
Medium Fidelity Prototype
For our medium-fidelity prototype, we added colour, graphics, images, icons, and more to make the app look like a fully functioning app and allow for more realistic testing.
The design of a quiz was added that would allow a user to complete a series of questions that would supply them with six best-suited movies. We chose to show six movies at a time based on a person's capacity to process information and the 7+/- 2 principle.
Heuristic Evaluation
Error Prevention
We chose to focus on the heuristic of error prevention by screen recording and contextual interviews with three users.
Findings:
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Users felt the medium-fidelity prototype version of our app was familiar and they understood the user interface fairly well.
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Some users taking the quiz liked to find new genres and suggestions than what they were used to.
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The main preference for finding movies was based on the genre.
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There was confusion around the ratings of the stars as they thought movie critics rated them and not their friends.
In our final design, we made this clearer. We also tracked where they were most likely to click and navigate through showing where their eyes were drawn to the most. Eyetracking software would have been helpful to gain more insights on this. We had to rely on vocalization from the participants for the scope of this project.
This showed that our app did a good job at error prevention as it was easy to understand, so there were low memory burdens, and the user’s mental model matched with the app’s model.
Timeline
09.20 - 12.19
My Role
UX designer + UX researcher