CBS All Access:
Reducing the Cost of Choice
Helping viewers make confident viewing decisions with less time spent searching.
As streaming libraries continue to grow, having more content doesn't always make choosing what to watch easier. For this ViacomCBS product hackathon, I explored how CBS All Access could reduce decision fatigue by helping viewers move from “What should I watch?” to “Let's watch this.”
Role: Product Designer
Project: CBS All Access Product Hackathon
Focus: User Research · UX Strategy · Interaction Design · Visual Design
Research: 6 qualitative interviews with subscribers and non-subscribers
Project: CBS All Access Product Hackathon
Focus: User Research · UX Strategy · Interaction Design · Visual Design
Research: 6 qualitative interviews with subscribers and non-subscribers
The solution
01
can't decide what to watch? We've got you.
Curated recommendations, crafted just for you. Let your next favorite find you.
02
One episode isn't enough -let's go deeper.
Loved what you just watched? We've gone and handpicked more episodes and shows that match your vibe. With Suggest Content assistance, browse a curated list of content that reflects your interests.
03
stay in the loop with friend approved picks.
Turn solo streaming into a shared immersive experience. See what your friends are loving with FriendCast and dive into the stories they can’t stop talking about.
Project Snapshot
The Challenge
Explore how the Paradox of Choice could be applied to the streaming experience and determine whether reducing decision effort could help viewers choose content more confidently.
Approach
I began by interviewing users about how they currently decide what to watch, synthesized recurring behaviors, translated those findings into design opportunities, and iterated on multiple concepts with feedback from my team.
My Role
I contributed across the design process, including qualitative research, research synthesis, UX strategy, wireframing, interaction design, prototyping, and visual design.
Focus
Rather than giving users more ways to browse, I focused on helping them make a decision with less effort.
Key Target Metrics & Impact Goals
* Time-to-Playback: Target a 30% reduction in average browsing time before pressing "Play."
* Session Abandonment: Decrease user drop-off during prime browsing windows.
* Social Discovery: Measure engagement via click-through rates on friend-curated recommendations.
The Challenge
More content was creating more decisions
Streaming platforms give viewers access to an enormous amount of content. While that variety creates opportunity, it can also make the process of choosing something to watch increasingly difficult.
The Paradox of Choice suggests that an abundance of options can increase the effort required to make a decision. I wanted to understand whether that behavior existed within streaming and, more importantly, what users actually needed when they felt overwhelmed by their choices.
The question
How might we help CBS All Access viewers make a confident viewing decision without spending more time searching than watching?
Research
Understanding how people choose what to watch
To understand the problem beyond the interface, I conducted qualitative interviews with 6 participants between the ages of 25–40, including both CBS All Access subscribers and non-subscribers.
I focused on how people discover content, what influences their decisions, and what they do when they don't immediately know what they want to watch.
Rather than asking participants what features they wanted, I focused on understanding their existing behaviors and decision-making patterns.
What I wanted to understand
* How do people decide what to watch?
* How much time are they willing to spend searching?
* What makes a recommendation feel trustworthy?
* When do people abandon the search?
* How do friends, family, ratings, and algorithms influence their decisions?
Behavioral Patterns
Designing for confident decisions
Key users from the interviews
Three behavioral patterns emerged
The research led to three principles that guided the concept.
01 — Time is scarce
When users have limited time, they don't necessarily want to explore the entire catalog. They want to find something good enough, quickly.
“I don't have much time, so I just throw something on.”
02 — Trusted opinions reduce decision effort
Recommendations from friends, family, and familiar sources can act as shortcuts when users aren't confident about what to choose.
“Whatever my friends suggest, I'll probably watch it.”
03 — Validation creates confidence
Ratings and recommendations give users additional reassurance that the content they're choosing is worth their limited time.
“On some apps they suggest things that I might like, so I'll give it a try.”
The Insight
The problem wasn't finding content. It was deciding what was worth watching.
The research shifted my perspective on the challenge. Users weren't necessarily asking for more content or more recommendations. They needed help reducing the uncertainty that comes with making a choice.
When time is limited, every additional decision adds friction to the viewing experience.
Reframed problem
How might we help viewers make confident viewing decisions before the time they have available to watch disappears?
The Problem Redefined
Based on the results from the 1-on-1 interviews, I gathered that streaming platform users, with limited time to browse, want to quickly find the right content to watch.
Design Principles
Designing for confident decisions
01 — Reduce decision effort
Help users narrow their options without creating another browsing experience.
02 — Increase confidence
Use relevant information and trusted recommendations to make choices feel more certain.
03 — Preserve the viewing experience
Support content discovery without unnecessarily interrupting playback.
The Solution
Visualizing the Solution
In the initial wireframing phase, I identified solutions to my "How Might We" questions, focusing on ways to reduce browsing time and help viewers quickly find something to watch. For the final solution, I integrated a single key feature that allows viewers to make all their choices within minutes, without ever leaving the streaming window.
After the first iteration, I reviewed the flows with my team leader to identify any adjustments or additions that could simplify my solution further.
By the end of the second iteration, I developed two versions of my design solution, which I refined further to create the final screens.
A decision-support system for CBS All Access
I explored three complementary features addressing different sources of decision uncertainty.
01 — Best Match - Algorithmic assistance
Focused recommendations based on the viewer's preferences and behavior.
“What might I like?”
02 — Suggest Content - Contextual assistance
An active recommendation experience for moments when users don't know what to watch.
“Help me decide”
03 — FriendCast - Social assistance
Recommendations from friends provide an additional layer of confidence.
“What are people I trust watching”
Together, the concepts were designed to help users move from uncertainty → confidence → play.
Highlighted Solution Elements
The key feature, Suggest Content Component, is located in the top navigation bar of the CBS ALL ACCESS homepage so that it can be accessed immediately by the user.
Final Screens
Design Exploration
The experience needed to coexist with active video playback, so I explored both vertical and horizontal interaction models.
Vertical
More content remained visible, but the interaction required greater visual attention and created more potential interruption.
Horizontal
The experience preserved more of the viewing context and made recommendations easier to compare.
Constraints & Next Steps
Technical & Prototyping Constraints
Active Video Rendering: Prototyping interactive UI components over live-rendered video streams presented high tooling friction during the short hackathon window.
Social Privacy: Implementing FriendCast requires transparent opt-in frameworks and granular privacy controls to ensure users control their viewing visibility.
Proposed A/B Testing Plan
To validate this solution in a live environment, the feature should be tested against the following plan:
01 - Toggle Interactivity: Measure ease of switching between algorithm-based Best Match and peer based FriendCast.
02 - Time-to-Selection: Track user velocity from clicking Suggest Content to launching a video stream.
03 - Retention Cohorts: Compare 30-day retention between users exposed to the module vs. the baseline control group.
Validation
Because this was developed within a hackathon environment, the concept was evaluated through qualitative research, design exploration, and iterative critique rather than formal usability testing.
The next step would be testing the prototype with streaming users.
Questions I'd test
* Can users immediately understand Suggest Content?
* Can they make a decision faster than through traditional browsing?
* Does Best Match feel meaningfully different from a recommendation carousel?
Reflection
This project changed how I think about the relationship between choice and usability.
My initial guess was that smarter suggestions would solve decision fatigue. The research shifted my thinking: the bigger opportunity was reducing the effort required to make a decision.
The strongest experience isn't always the one that gives users more options.
It's the one that helps them feel confident about what to choose next.
