While Netflix is positioned as the quintessential platform for streaming content, the corona crisis has highlighted one of its shortcomings: there is no easy way to recreate the intimate social experience of watching a movie with someone who either lives far away or for safety reasons cannot be visited. My group saw this shortcoming as an opportunity to make Netflix’s service better by being more inclusive, and promoting greater social interaction.
We completed this project in a two week sprint, and presented our research and development to the General Assembly Instructional team.
Our team used Slack and Zoom to communicate, Miro for assembling user flows and interview data, and Figma for mockups and prototyping.
We began our project by conducting competitive analysis on Netflix’s greatest competitors, essentially getting the lay of the land for their platform’s offerings. It turns out many of them do offer options for simultaneous viewing. Hulu, Disney+, and Amazon Prime Video all have this functionality, as well as a built in chat feature. There is a third party extension for Netflix that provides these features, but it doesn’t always work well, and isn’t widely known.
And so our position was clear. Netflix is currently lacking a feature than many of its competitors offer, and one that will likely become increasingly demanded as we have become more and more accustomed to a world where social experiences happen remotely. I familiarized myself with the Watch Party features that other platforms offered and realized Netflix has the opportunity to make these social experiences more enjoyable.
Understanding and evaluating Netflix’s competition was crucial to building a better product, and so I set out to test the Teleparty extension and mapped this user flow using my own experience. This flow looks fairly simple, and masks the pain points of using Teleparty, namely:
Our team wanted to dig deeper into the highs and lows of the watch party experience, and so we mapped that experience into a user journey map. This map covers the entirety of the user’s process, from making plans with friends, to when the movie is over. This process was useful in highlighting which parts of the journey were positive for the user, and which ones were in need of improvements.
My next major role in this project was writing a script of interview questions to ask potential users. I wanted to know what it was about watching content with other people that was so enjoyable. I then conducted a series of user interviews that asked questions about their watching habits. We used affinity mapping to sort the information we gathered from our various subjects into categories such as: shared emotion, group dynamics, how to decide what to watch, and their impressions of other watch party platforms.
Our interviews taught us a great deal about our users, and gave us a clear path for our design. It was clear that there was a demand for our idea; almost everyone we talked to described watching things together as an activity they enjoyed doing, and importantly, they gave us insight as to why. It is the interactions between people that make group viewing so fun. Laughing with your friends, looking over and catching their expressions as they watch your favorite part. These are the aspects of social viewing we needed to bring to Netflix’s version of watch party. For this to be successful, a group chat would not be enough, we would need video chat.
In addition to user interviews, our team crafted a series of survey questions designed to further illuminate the behaviors and desires of our potential users. We collected data from 15 different users which highlighted not only potential wants and needs, but hard data as well, detailing both demographic information, and platform usage. The data we collected was very useful in determining potential platforms for our product. We could see that most users streamed content on their desktop computer or their smart TV. Both of these platforms would be ideal for our product, which because it relied on multiple sources of video simultaneously, was going to require a lot of screen real estate to work comfortably. Computers also have the distinct advantage of being easily connected to microphones, webcams, and of course keyboards, making the social goals of our project much more achievable. For these reasons we decided to focus our efforts on a desktop experience first, with the goal of expanding to smart TVs in the future.
The next step in our process was synthesizing the data we collected into a user persona. We conducted an affinity mapping exercise to collect our thoughts. Affinity mapping led gave us a clear picture of the potential user for our project. Meet Zach Miller: A 28 year old bartender living in LA, who misses the social interactions he had watching movies together with his friends before the pandemic.
With our research complete, and our user well defined, we now had a clear direction for our design. We then crafted a few statements that would act as the guiding principles for our work:
Our team began the process by conducting a design studio. We each separately sketched out our ideas for the functionality of Watch Party, and then reconvened to share our sketches. It was clear that our team was on the same page because the essential parts of our designs were there: from the overall flow to the layout of the Watch Party window. The next step was converting our sketches to a medium fidelity mock up in Figma. It was important to fully integrate the new Watch Party feature into Netflix’s existing design, so I created a skeleton of Netflix’s platform. From this basic shell we would integrate our watch party feature, making sure that it fit nicely within the existing framework.
The next step in our process was user testing. We had to make absolutely sure that our flow would make sense to any users, and would feel intuitive and fun. We devised a test plan for our users to follow in which they would complete two simple tasks: Create a watch party room, and invite friends. We reached out to some potential users and began testing.
I was pleased with the results of our tests, which mostly validated the flow and design of our watch party feature. The users were able to quickly follow the steps to create a watch party room and invite friends. Nothing is perfect however, and with our testing notes in hand we set out to create a high fidelity prototype.
One of our main goals in this project was to match Netflix’s aesthetic and design language as much as we possibly could. To achieve this we made use of a UI kit. We wanted to integrate our Watch Party feature right into Netflix’s existing framework, hopefully making it appear as though it had always been there. One drawback to this approach is that something so well integrated might be overlooked by a user who is accustomed to the way things are. To avoid this, we added a callout to the homepage which highlights the Watch Party feature and guides any new users.
We used this strategy of “guiding copy” throughout our project, using words that bring attention to specific areas or features, and encourage specific user behavior, such as opening the chat and sending messages to start a conversation or selecting a movie to watch. For example, the image below appears once a Watch Party has been created by the user, and helpfully guides them through the process of selecting a movie, and explains how their friends can add movies to the suggested list.
Another goal of the iteration process was to increase the overall legibility of our Watch Party feature. The “guiding copy” went a long way in improving this, but our user testing also uncovered another area for improvement: our icon. Users reported that the original icon we used in the mid-fidelity prototype was not being read as a group watch function, but rather some sort of broadcasting feature. We quickly developed a new icon that was more appropriate, and also highlighted the social element that we felt was most important to our project.
The ability to customize the experience of Watch Party was very important to the success of the project. We understood through our research that users had very different wants and needs when it came to watching movies with friends. Some users prefer the text chat, while others preferred seeing their friends faces and hearing them laugh. We wanted to build Watch Party so that it could be used by many different users in any way they prefer. To best suit any situation, we designed both the chat and the webcam windows to be collapsible, allowing users to tuck them away when they aren’t being used. In this way users can fully customize their viewing experience to match their own individual preferences.
From our research we gathered that users crave social experiences. In this increasingly fragmented world it is not always safe or possible to be together physically. Watching movies with friends remotely is a safe and accessible alternative. But as it stands there isn’t an ideal method for allowing remote social viewing. Herein lies an opportunity: by crafting the best possible social experience through their own version of Watch Party, Netflix would position itself as the premier platform for film culture and allow users to get even more value out of their subscriptions.
Many thanks to my teammates, Alex Deatherage and Bora Yuh, who were instrumental to the success of this project, and to Kemal Salih Carfi, who provided the Netflix UI kit.