Personalised Disney+ Viewing Onboarding

A work product showing how I would improve content discovery on Disney+ by solving a common user problem.

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Executive Summary

• Problem: Choosing what to watch on Disney+ is overwhelming. The current system doesn’t personalise content well, which leads to frustration and disengagement.
• Solution: A simple, personalised onboarding flow where users quickly select their favourite genres, shows, and characters. This will immediately improve content recommendations, providing a tailored experience from the start.
• Impact: The new onboarding will reduce decision fatigue, improve the relevance of suggestions, and increase user engagement. It will also reduce churn and position Disney+ as a leader in personalised content, driving long-term loyalty.

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Context and Problem

Understanding the Disney+ viewer

Disney+ attracts a diverse audience, with Millennials and Gen Z making up a large portion of users. In the US, 55% are male, 45% female, and 51% have a college degree (Tech Report 2023; Statista 2024) The platform’s success comes from its exclusive content and a simple interface that personalises recommendations based on viewing history (Forbes, 2022). 

The Problem 

Whenever I open Disney+ to watch something, I find myself asking the same question: What should I watch? And I’m not alone. Friends and family often say the same thing. Despite a clear recommendation, we often suffer from stream fatigue and frustration, especially when Disney+ misses the mark with its suggestions. (Disclaimer: Talking to a five friends and two family members cannot and will not replace actual user research.)

The problem is that there’s so much content that it’s overwhelming. Earlier this year, I wiped my account clean and started fresh, liking shows and films I enjoyed to train the algorithm from scratch. While the recommendations improved slightly, the process was tedious, and I still felt disconnected from the recommended content. This is the problem I want to solve.

Pain Points and Opportunities

Pain Points:

1. Users feel overwhelmed and struggle to find something to watch.
2. Recommendations are too general and don’t reflect niche interests.
3. Training the algorithm is slow and tedious.
4. The homepage feels disconnected and not tailored to personal preferences.

Opportunities:

1. Personalise suggestions by capturing preferences right from onboarding.
2. Introduce curated lists or mood-based suggestions to reduce scrolling.
3. Allow users to tweak their homepage based on their interests.
4. Build a quick, engaging flow to capture preferences and deliver relevant content immediately.

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Proposed Solution: Personalised Disney+ Viewing Onboarding

To tackle streaming fatigue and deliver tailored content, the Personalised Disney+ Viewing Onboarding simplifies user preferences and improves recommendations. 

What it is
An engaging onboarding experience where users pick their favourite genres, shows, and characters.

How it works

• Users swipe or tap to pick favourite genres, shows, and characters.
• Include trending Disney+ franchises and niche favourites.
• Preferences feed directly into the recommendation engine, curating a personalised homepage instantly.

Why it works

• Users focus on what they love instead of scrolling endlessly.
• Skips the manual algorithm training and delivers relevant recommendations from Day 1.
• A personalised experience from the start increases satisfaction and reduces churn.

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Implementation Plan

Phase 1: Minimal Viable Product (MVP)

Objective: Quickly build a simple onboarding flow to personalise recommendations from Day 1.

Features:

• A swipe-based interface lets users pick favourite genres, franchises (e.g., Marvel, Pixar, Star Wars), or specific titles.
• Generate a personalised home screen based on preferences.

Technical Overview:

• Use Disney+’s current recommendation engine to filter content immediately after setup.
• Integrate user selections into the existing Amazon Kinesis-backed data infrastructure for real-time updates (Databricks, 2020).

Phase 2: Scale and Optimise

Objective: Deepen personalisation and make content discovery seamless.

Features:

• Add mood-based content carousels like “Relaxing Evenings” or “Family Favourites.”
• Refine recommendations using machine learning and data analytics.

Technical Overview:

• Enhance metadata tagging for better content categorisation.
• Use Databricks on AWS to analyse real-time user engagement.

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Product Metrics

• Engagement: Measure time spent browsing, how often users finish shows, and the number of clicks to choose a title (goal: under 5 clicks).
• Recommendation Quality: Measure how often content matches user preferences (goal: over 75%) and how often users skip auto-played recommendations (goal: less than 20%).
• Onboarding Success: Track onboarding completion (goal: >80%) and time spent during onboarding (goal: ❤ minutes).
• Churn Risk: Measure the percentage of users who stop using Disney+ within three months and the number of inactive days before drop-off.

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User Insights and Validation

We’ll start by testing early prototypes in focus groups to gather feedback and refine the experience. After that, we’d roll it out to a select group of users in a pilot test.

The real validation is performed by tracking our metrics. We’d compare users with and without the onboarding flow to track engagement, churn, and how well recommendations land. Key product outcomes: 80%+ completion rate for onboarding and 75%+ relevance for suggested content.

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Competitive and Market Analysis

Competitive Advantages

Disney+ has an opportunity to stand out by offering a personalised onboarding experience that simplifies content discovery from Day 1. This approach sets it apart from competitors like Netflix, Max, and Apple TV+, which mainly rely on generalised recommendations after initial use.

Market Trends

Streaming platforms are increasingly using AI to personalise recommendations (Streaming Wars, 2024). While platforms like Netflix rely heavily on algorithms to predict preferences, others, like Max and Apple TV+, focus on curated experiences and refine recommendations over time based on user behaviour (The Strategy Story, 2024).

Disney+ can capitalise on these trends by learning user preferences upfront and delivering relevant content right away.

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Next Steps

• Align leadership on strategy and metrics.
• Conduct usability tests to prioritise features and refine designs.
• Collaborate with engineering teams on technical dependencies.
• Build and test a prototype with a pilot group.
• Plan phased rollout to key markets.

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Final Words

This is just the beginning. By creating the Personalised Disney+ Viewing Onboarding , Disney+ can transform how users discover content, setting a new standard for streaming services.

This initiative tackles immediate user challenges while positioning Disney+ as a frontrunner in personalised content, paving the way for stronger engagement and long-term loyalty. Trust me, I know at least five friends and two family members who would love it.