How long does it take to
choose a movie to watch?
Turns out it’s not that easy when you have plenty of movies on your Netflix home screen.
Despite all the smart algorithms that Netflix uses to suggest you most relevant movies, still,
according to the studies, 75% of the users are struggling with the choosing process.
More precisely, according to The Wrap, Netflix users spend on average 18 minutes on a given day
deciding what to watch, or twice as much as cable television viewers.
The scope of this project is to investigate Netflix users’ interaction
with the website and suggest possible UX improvements.
Project Statement
Busy people of age 25-45 need a way to quickly find a TV Show/Movie to watch on Netflix,
because they have limited time on media entertainment, which is an important part of people’s
relaxation and stress release procedure at the end of a busy day.
Hypothesis
In any kind of decision-making process, people do value their friends and colleague’s opinion.
They discuss movies in the workplace or on hangouts, they suggest to each other good movies, knowing that the person will like them, based on their personal awareness of the friend’s mood and preferences.
We believe that the functionality to get and give suggestions to friends about the movie directly from Netflix will narrow down the choices for the user and will make those more relevant and personalized.
The KPI (Key Performance Indicator) will be the time that users spend on searching, we want the users to spend less than 7 minutes on the searching process.
Research
Goals:
- Find out how the watching time integrates with people’s day or week live cycle.
- What are the main obstacles or inconveniences?
- How people deal with or overcome obstacles?
The method of in-person interviews was used for this research.
- Random people ages 25-45
- 20-30 minute
- 12 people
Research Findings
- The user research shows that the majority of users have very limited time for TV entertainment.
- Having a relaxing session is highly valued by users
- They spend more than 15 minutes searching for what to watch.
- People are struggling with the decision-making process.
- 90% of users said that first, they look for the movie that a friend suggested the other day.
“Watching Netflix before bed is like my sleeping pill. I need it.”
– Diana T.
“Sometimes I search on Netflix, then I try google, and if I don’t find something really worthy, I just turn off the TV.
– Shana M.
“I have to check the real people’s reviews on a certain movie, to make sure it’s really a good one.
– Harry J.
Conclusion
So the user research showed that there is an issue with spending too much time searching for a movie and making a decision on what to watch.
In reality, people do use their friends’ suggestions, so the idea of
projecting it from the face-to-face discussions into an in-app functionality could be a good solution.
User Persona
Sitemap
User Flow
Feature Prioritization
Initial Sketches
During the brainstorming and design studio sessions was proposed to have the “Continue watching” section in a more prominent position- the right section.
Wireframes
After the first iteration (sketching) several improvements were implemented on the wireframed prototype:
- Show the friends’ avatars with the names and ratings.
- Have the ability to type a specific text with the suggestion.
Further, there were 2 hypotheses regarding the location of the “Suggest to friend” button.
- on the bottom with the video playback controls.
- on the top right side with the “like” and “dislike” buttons.
Hence, I created 2 different interactive prototypes for usability testing.
Usability Testing
As mentioned above, based on the usability tests of 2 hypothetical prototypes the findings were as follows:
- 80% of users stated that the “suggest to a friend” button is more intuitive to be on the bottom with the controls.
- 95% of users confirmed that they find “continue watching” section very convenient and easily accessible on the right section of the screen (in what Netflix currently has on the website)
- Some users suggested that it would make sense if they could make multiple selections on a friend list when sending a suggestion. Which I did implement on the next iteration.
High Fidelity Interactive Prototype
Link to the Final Hi-Fi Prototype
Summary
