Netflix
Netflix Reimagined: Designing a Personalized & Immersive Streaming Experience
This self-initiated project explores how Netflix could evolve from a content library into an emotionally aware, personalized entertainment experience. I led the end-to-end design process from research and ideation to high-fidelity prototyping and usability testing applying the Double Diamond framework and strategic UX thinking.
Project Overview
Netflix plays a role in millions of daily routines, yet its interface often overwhelms users with choice especially when they’re tired, emotionally drained, or watching with others.
This project explores how Netflix can move beyond passive content delivery to become a smarter, more human-centered platform. Through mood-based discovery, smart home integration, shared profiles, and a conversational AI assistant, This redesigned experience is designed to:
Reduce decision fatigue
Improve emotional alignment with users’ daily states
Enhance shared viewing without disrupting personal recommendations
I designed a personalized system that adapts to users’ moods, context, and environment by turning passive watching into an immersive, intelligent experience.
Problem Statement & Goal
Netflix is a go-to destination for winding down, connecting with loved ones, or escaping into a story. But today’s experience isn’t keeping pace with changing user expectations. The platform lacks emotional responsiveness, intuitive discovery, and support for shared use cases.
As user routines, technologies, and emotional needs evolve, the opportunity is clear: Netflix must go beyond content delivery to offer intelligent, mood-aware, and frictionless experiences.
Goal
Reimagine the Netflix platform to:
Enable mood-based content discovery
Introduce a shared profile system for households
Integrate with smart home devices to enhance ambiance
Add an AI assistant to support real-time interaction and content insight
Process: Blending Emotional Insight with Product Strategy
I followed a modified Double Diamond framework:
Discover: Research into user behaviors, frustrations, and current competitor offerings
Define: Synthesis of insights into opportunity areas and UX goals
Develop: Low- and high-fidelity wireframes and flows for new features
Deliver: A polished conceptual prototype and feature set with UX rationale
Discover: Uncovering Emotional Gaps in Streaming
began with qualitative interviews and a global survey to understand how emotional states influence streaming behavior.
Methods Used:
15 user interviews
Survey (6 countries, ages 22–45)
Informal conversations + competitor analysis
Key Pain Points Identified:
Emotional mismatch: Users wanted shows based on how they felt
Smart home readiness: Users expected environmental sync (“movie mode”)
Shared viewing friction: Watching with others disrupted recommendations
Lack of interaction: Users sought lightweight, in-the-moment assistance
Deliver: Bringing the Vision to Life & Reflecting on Impact
After prototyping and validating core features, I refined the product into a cohesive experience designed to feel intuitive, emotionally supportive, and aligned with Netflix’s product voice.
Final Outcome
The reimagined Netflix experience introduces:
Mood-Based Discovery that makes finding “what to watch” emotionally intuitive
Shared Profiles that adapt to group dynamics without muddying personal preferences
Smart Home Integration that enhances immersion with voice-activated and context-aware controls
The concept balances advanced personalization with a calm, human-centered interface — prioritizing ease, emotion, and contextual relevance.
Strategic Takeaways
Human-centered AI is no longer a novelty it’s expected.
I designed for trust, transparency, and opt-in control to keep AI helpful, not intrusive.
Context > Content.
Personalization that adapts to mood, time, and social context leads to deeper engagement than traditional algorithms.Clarity over complexity.
Small interactions (like shared PINs or ambient dimming) made a surprising difference in how users felt about control and comfort.
What I’d Do Next
If handed off to engineering and product teams, I’d continue by:
Expanding accessibility support (screen reader, contrast-friendly UI for night use)
Partnering with data science to fine-tune mood-based recommendation engines
Running A/B tests on user opt-in for Smart Home features