The problem
People often watch movies together, either at home or by going to the cinema together. However, there is so much choice of film with all the available streaming options and releases in cinemas.
The challenges:
- Different people have different tastes
- Some people will have already seen some films
- Tastes vary based on current mood or environment
- Availability of movies to watch varies
- Time available to watch may affect the choice of movies
- Critical and popular opinions influence choices
- AI recommendations can be overly predictable and rely on knowing personal tastes
The solution
To address these issues, I designed a mobile app to help curate movie watchlists and find films to watch.
Key features
- Curate a watchlist and track watched/unwatched films
- Search for and filter films based on mood/experiential criteria and availability
- Suggestions based on previously chosen films, mood, experience, or availability
- View information about each film
Benefits
- Track the films you intend to watch and mark them off as you watch them
- Learn about the films you watch or are interested to watch
- Find new films to watch based on what you previously liked
- Find films to watch based on the audience, their collective mood or desired experience, rather than simply genre/cast/crew
- Know what films are actually available for you to watch and where to watch them
Learning about users & the problem space
I interviewed 5 people of different backgrounds and levels of interest in film.
Levels of engagement with film:
Film buffs
These are people that use specific criteria/sources for recommendations. They follow specific filmmakers and trusted experts, curate watchlists, see film as a way to teach culture, and analyse more deeply.
Casual watchers
These are people for whom trends/popularity & social media drives the selection of films. They judge films on the basis of genre and analyse the positives, rather than dwell on the negative aspects.
Other observations:
Mood & mindset
The time of day, environment & current feelings influence choice of film. In addition, subjective expectations of a film can influence the reception of that film.
Availability
The availability of films on streaming services or in physical cinemas drive a lot of film watching decisions.
Social dynamics
People may watch films they otherwise wouldn't when with friends. They may even enjoy bad movies ironically in such a situation. Furthermore, most like to discuss the films afterwards.
Understanding the existing market
I examined 5 different products, including streaming services and movie recommendation apps:
Characteristics
- Tinder-style interfaces: common but inefficient for new users
- Personalisation: recommendations based on past choices
- Categorisation: often excessive and not particularly meaningful
- Demographics: apps vary in level of information provided about films, providing either too much or too little information for the different cohorts
- Social curation features: often tailored for specific social groups like couples or friends
- Streaming availability: most apps indicate where films can be streamed
Who are the users and what are their goals?
Based on my research, I was able to define two archetypal personas, each with challenges, frustrations and goals.
These are their goals:
Hoss, the film buff
- Wants to more easily curate a list of interesting films to watch and select an appropriate film from it to watch at any given opportunity
- Wants to deepen and broaden his knowledge of film and film history
- Wants to broaden his film watching horizons, as feels like he is missing out on potential gems
- Wants to find more films by filmmakers whose work he has enjoyed
- Wants to share his film suggestions and knowledge with his immediate friends
Amy, the social movie watcher
- Wants to find new, popular/trending movies or TV series that would provide a good social watching experience with her friends
- Wants to find interesting new movies and TV series that are popular/trending so she can be part of the conversation
- Wants to understand what her friends are interested in watching together, so she can organise mutually satisfying group watches with them
- Wants to bond with her friends over group watching experiences
How do we address the opportunities?
I identified some key challenges to address based on my research.
From research I knew that The Movie Database (TMDB) offered APIs that provide film data required to implement many basic features. I took that into consideration when prioritising features for MVP.
For the key challenge:
For the key challenges I brainstormed some solutions:
...I brainstormed the following solutions:
Helping users to curate and track watchlists
Solution:
- Save films to watchlist and mark as watched/unwatched
Helping users to find interesting and satisfying films to watch that they haven't seen before
Solution:
- Basic info about each film
- Suggestions based on previously curated films
- Explore films by cast/crew/genres
After MVP:
- Contextual info about films, such as history & film movements
- Explore films by movement/history
Helping users to find films to watch that fulfil the audience's current psychological wants and needs
Solution:
- Filter movies by genre/mood/experience
- Suggestions by genre/mood/experience
- View film availability
After MVP:
- Watchlist sharing & collaboration
- Automatic suggestions based on time/mood
Validating initial concept with users
I initially designed a sitemap, user flows and some simple low fidelity wireframes to illustrate the concept.
Testing with users & other designers revealed minor issues:
- The lack of a first-time experience for new users
- Confusion about terminology
- Confusion about the relationships between UI elements on the search screen
- More information wanted for the films displayed in the UI
Design progression
Crafting the product identity
For this project I created a brand & design system, which I iterated concurrently with the final designs of the product. Feedback from other designers informed the development.
Identity development
Creating and validating the polished product
With the initial feedback, I combined the wireframes & design system into a high fidelity interactive prototype.
Flows created:
- Adding first film to watchlist
- Looking up a specific film to add to watchlist
- Getting suggestions for a film to watch based on watchlist
These flows were tested with 5 potential users.
Enhancements from feedback
Users indicated it was important to retain a watch history and not remove watched films from watchlist
- Toggle films on watchlist between watched/unwatched using a gesture
- Filter films on watchlist by watched/unwatched
Users were confused about what “Suggest” did — were they suggesting films or was the app?
- Revised “Suggest” to be “Suggestions”
More information was important to make decisions about films to watch
- Added information about runtime and critical ratings to each item in watchlist
Some users wanted a more efficient means of viewing suggestions as they knew a lot of films already
- Added toggle to see suggestions in a list view
More information was important to make decisions about films to watch
- Added information about runtime and critical ratings to each film
Outcomes
The solution was rated relatively high for ease of use
5 – 7 out of 7
Users felt it would make a good replacement for the fragmented interfaces of streaming services
However, it could be further enhanced:
- Inclusion of sharing & group curation (as mentioned earlier)
- More information about each film
- Lift trending/popular categories and filters