BRACKETS is a movie rewards extension that rewards viewers with tickets (Brackets Tickets) when they complete select series and movies. Once the viewer has collected an allotment of tickets, the tickets can then be traded in to unlock premium or unreleased shows and movies. This service is designed to be applied to any preexisting streaming service or can become its own identity. For demonstration purposes, I designed BRACKETS to be its own application.
PROBLEM: It is no secret that streaming services are all in competition to captivate their audiences with the best series and movies. As an active viewer myself, I grow tired of spending the majority of my time on these applications just scrolling looking for new things to watch. I've also find grief with the recommended streams and reels that I've already completed watching. It extenuates the browsing process, increasing the lack of interest within each application.
DESIGN GOAL: My goal for this project is to create a tickets based reward system to incentivize the interest of viewers and reward them for their time spent. I hypothesize that this will increase the watch time of the service and increase the frequency of return. This application will also queue viewers completed series to improve the searching experience.
• Movie lovers
• Binge watchers
• Streaming services
DELIVERABLES: High-Fidelity Prototype + Brackets Tickets
TOOLS: AI, XD, PS
DURATION: OCTOBER 21, 2020 – TBD
ROLE: LEAD DESIGNER, ENTREPRENEURIAL PROJECT
TAGS: #UX #UI #APP #STREAMING
USER RESEARCH + PERSONAS
I created two personas based on one-on-one interviews and survey results.
COMPARATIVE + COMPETITIVE ANALYSIS
I compared my potential product to three popular streaming platforms, Netflix, Hulu, and Disney Plus. Each streaming platform has user-specific content, however, none of the applications obtain a rewards system for completed series and movies. Another note, and a pain-point from my focus groups, was that none of the streaming applications have a queue where they can access listed streamed that they've completed watching. Having listed streams recommended in repetition causes a disruption in the browsing exper-ience which creates aggregation about time-wasted, often leading to a user leaving the application. With this information, I created a composite of each application experience from the collected data.