UX Concept Project | 4 days | Individual
The below case study showcases a summary of the project. To read my full UX process please click here.
Overview
This app makes it easier to discover super tailored recommendations of shows to watch, without needing to browse through all your streaming services.
I created this concept project as part of General Assembly’s UX design course, whereby I needed to solve a problem for a classmate by creating a simple mobile app. This project undertook a lean UX method of working and focused on rapid prototyping, with end deliverables of a paper prototype and a final presentation.
Research Methods + Deliverables
User interviews
Experience mapping, storyboarding, user flow
Ideation, low fidelity screens, usability tests and a paper prototype.
Software
Marvel for prototyping the paper screens.
Highlights + Challenges
My favourite part of this project was thinking out of the box to conceptualise an array of ideas to help address my user’s problem, from famous soundtracks to gamification. My original idea of creating a survey-based solution had a complicated user flow that would have taken days to build. Although it answered my user’s frustrations and would have technically worked well, I had to sadly let the idea go due to the short time span of the project.
Constraints
Considering this was a 4-day project, I had to find a quick and easily implementable solution to the problem - which was my classmate, Ciaran, not being able to find something suitable to watch across his streaming services. Any idea which would take more than a day to map out and prototype couldn’t be used.
Understanding the problem through exploratory research
After conducting two interviews with my classmate Ciaran, I absorbed his frustrations about his movie watching habits which were difficult for him to shake off. He feels like he watches the same movies and shows repeatedly because it’s easy to — he would love to watch new shows, but to find one that he really liked would take a big chunk of time from his evening.
I also understood his plea for wanting a more streamlined searching experience when looking for recommendations, with suggestions that were actually relevant to him so he didn’t have to waste time browsing.
While this exploratory research uncovered a variety of Ciaran’s needs, I focused on the three main takeaways.
He can’t keep track of all the streaming services he’s subscribed to.
He comes home from work and watches the same movies and series over again — therefore, he wants to be inspired.
He spends a large chunk of time scrolling through irrelevant recommendations when what he really wants to do is find something quickly to watch while he eats dinner, knowing that he has a high chance of enjoying it.
Lastly, a point that wasn’t crucial but worth noting, was that movies directed by certain trusted film directors are important to him.
After ideating on potential solutions, I ensured to answer the problem statement and deliver the idea in the given timeframe.
The solution was an app where Ciaran could sync his desired streaming services, create a profile, and generate a super tailored movie to watch for that evening according to his exact preferences. This would be all be done through an algorithm, so there’s an assumption that this technology already exists.
The paper prototype incorporated key pieces of feedback received from the usability tests and provided solutions for Ciaran’s main frustrations
Ciaran said that he could not keep track of all his streaming services, so the sync feature in the app will combine all his services into one and conduct a search through them all. He also wants to be inspired and find more tailored movie recommendations. Creating a personalised profile will allow him to express his personal choices in more detail so the algorithm can find a suitable movie for him to watch. Please note that not all features are functional within the prototype.
Measuring success
With a higher frequency of use, the app’s algorithm will be able to provide more relevant and useful suggestions. Success would therefore be measured by the number of times the “watch now” button was selected per use, and the number of times "save for later” was selected. This would indicate if the app was doing its job, considering the user’s profile information was correctly entered. Other trackable metrics would include the number of downloads, uninstalls, retention rate and reviews.