In the realm of streaming, Disney Plus competes with top platforms like Netflix and Hulu. Subscriber loyalty is crucial for growth, but with the recent loss of 2.4 million users due to content issues underscores the need for user-friendly features. To avoid further setbacks, Disney Plus must address user frustrations and enhance essential features, recognizing that content availability is just one piece of the user experience puzzle.
The problem: Within the diverse base of streaming platforms, there's a common need for essential features to personalize and navigate user experiences. Disney Plus, however, lacks some of these standard features, affecting users' overall satisfaction and potentially influencing their subscription decisions. Addressing these missing features is crucial for enhancing the platform's appeal and retaining subscribers.
During my exploration of Disney Plus, I couldn't help but notice the scarcity of personalization features on user homepages. Apart from a single recommendation section, the majority of the page is dedicated to showcasing new or exclusive Disney offerings.
This lack of personalization drove the start of my project.
Selecting a particular feature to focus on proved to be challenging, making this initial step feel quite significant.
Research goal: I want to know how users would utilize an editable watching list so I can understand how this play into elevating the user experience through more customized recommendations.
Objectives:
Methodologies:
Major insights: I analyzed the recommendation personalization structures of 3 competitors to gain insights into how other streaming platforms operate:
Strengths:
Weaknesses:
Who?: User interviews were conducted with 5 participants who are:
Interview method: Zoom
Interview duration: 20-30 minutes
Link to affinity map FigJam fileMajor insights: Valuable insights emerged from these interviews, addressing my initial concerns about adding complexity to the project. I realized that my design solution may be too simple, but the provided insights reinforced my confidence in continuing with the project:
Insight 1
Users often try different content on streaming platforms to see if it's something they would enjoy, but find they don't.
POV
Users need to be able to removed content from their "Continue Watching" list because they're unwanted titles that user won't watch further.
HMW
How might we make the removal process smooth and simple so users can remove unwanted content from their list?
Insight 2
Users have trouble deciding what to watch because of vast amounts of content streaming platforms provide.
POV
Users need a way to filter content, as browsing too much at once becomes overwhelming and makes it hard to choose what to watch.
HMW
How might we help users figure out what they want to watch by narrowing down their content while maintaining relativity?
Insight 3
Users aren't always satisfied with the content streaming platforms recommend to them.
POV
Users need access to well-rounded and personalized content as they grow frustrated having to manually search for content themselves.
HMW
How might we improve the recommendation section so content is better well-rounded and personalized to the user?
These personas serve as a valuable reminder of the target audience and the purpose behind the features I'm designing.
Remembering my users: Personas were created from major insights I found in my interviews which included explorative, indecisive, and unsatisfied tendencies when looking for content to watch on any streaming platform.
From my insights, I found that Insight 1 had an easy fix: a removal features within the "Continue Watching" list.
Hitting two birds with one stone: However, with Insights 2 and 3, I needed to think a little more about the solution.
Reflecting on both, I realized they could merge where more meaningful recommendations (Insight 3) in higher volume will narrow down the content users have to sift through (Insight 2).
Removing a title from the "Continue Watching" list: Although being relatively simple, this feature would allow users to remove content from their "Continue Watching" list, something that Disney has yet to implement to their streaming platform.
Editing personalized recommendations within a profile: To address Insights 2 and 3, I aimed to implement a content selection flow where users can indicate both their likes and dislikes, leading to better recommendations.
I struggled to determine the best placement for Flow 2. After researching other streaming platforms, I noticed that they typically include this feature in the onboarding process when the user first signs up.
The issue for me was I was catering to existing users.
Digging a little deeper, I discovered Hulu allows users to change recommended content through their profile. While this placement wasn't by first choice for recommendation settings, I found it difficult to find a better location. I decided to initially place it here and made note to test this during usability testing.
Knowing I had to stay within the existing design system made sketching ideas for my feature much simpler, especially coming from completing an end-to-end app.
On my mind: To keep within the constraints of Disney Plus's current platform, I matched my design to its existing style. While digitizing my sketches, I thoroughly examined the platform to align every element as accurately as possible.
Hover Component: To integrate this simple feature seamlessly, I determined that the most appropriate location was within the hover state of a title card in the "Continue Watching" list.
Recommendation Flow: Disney Plus is unique in that they have so many major brands within their platform including Disney, Pixar, Marvel, Star Wars, National Geographic, and Star.
By first asking users which of these brands they watch, I aimed to break down recommendations from general to specific.
The next 2 steps involve users choosing up to 5 titles they enjoy and don't enjoy watching.
During user interviews, a notable comment highlighted that while most streaming platforms, like Netflix and Hulu, ask what users enjoy watching, they rarely ask about content users dislike. Addressing this gap could significantly improve how recommendations are tailored to each user.
An interesting setup... : After making an edit in the profile, users must navigate extensively to return to their homepage, including reselecting their profile. This felt like a very roundabout and unecessary way, but I retained this flow to stay consistent with Disney's current platform. However, another thing to note while conducting usability tests.
Who?: User testing was conducted with 5 participants in the target demographic who were given broad instructions for each flow and completed navigation through Figma's prototyping.
Interview method: Zoom (shared screen)
Interview duration: 20-30 minutes
High expectations... : As I began user testing, I anticipated no issues with the first flow, removing titles from the "Continue Watching" list.
... And low expectations: The primary focus was on the second flow, where users change their recommendations settings. Unsatisfied with the current placement, I was curious to see what users expected. Additionally, I wanted to determine if users were satisfied with the flow and their navigation back to the homepage.
Expectations exceeded: As expected, all 5 users navigated the first flow without issues and found the feature to work well. Their satisfaction was due to the flow being intuitive, seamless, and informative from start to finish.
Despite its simplicity, users appreciated that the process mirrored other streaming platforms, eliminating the need to learn something new.
Where things started going wrong: When users were instructed to access their recommendation settings, they had no idea where to go. All agreed that their profile wasn't their first choice. Some suggested placing it in another part of settings or directly within the homepage.
While navigating the flow, a few other suggestions included adding more titles and genre options for users to choose from. There were some raised eyebrows at the overly complicated navigation back to the homepage after editing settings.
First and foremost: The most pressing issue was how users located and used the recommendation settings. Feedback from my tests showed most users expected the settings to be accessible from the homepage.
It made sense to embed the settings within the "Recommended for You" section. Research, guided by Hick's Law, showed that users who scroll across too many choices become dissatisfied with their final decision. Offering fewer options can lead to a more satisfying decision-making process, and therefore user retention.
Fixing the flow content: Users noted a lack of options and variety when selecting what they enjoy and don't enjoy watching. To address this, I added another row of titles, group them into major categories like animation, live action, movies, and shows, with each title representing a different genre.
With iterations done, I felt much more satisfied with how my flow worked. There was a greater sense of ease knowing that users have validated the structure and content that drove my iterations.
Throughout the process, there were many things I would've changed if I started again and with more time.
Future iterations: Although I couldn't get it done within the time I had, there are some iterations I would've loved to play around with more:
This project has taught me a lot, from managing scopes to working within a pre-existing design system. There were a lot of hurdles that I got through to get to my final iterations, but I'm grateful for the experience of overcoming each challenge.
Moral of the story:
