Introduction

This case study shows the process our team used to design a product that helps people have great virtual partys. The Contextual Design method was used to guide ourselves through every aspect of UX, from user research over design iterations to a low fidelity prototype that combines all the insights we gained.
As one of the four team members I was an active part of each stage in the process. Additionally my role as project leader was to ensure that the team’s progress was on track and there was good communication inside of the team as well as towards the client.

Read on to learn more about our systematic way of solving this design challenge. The case study includes the problems we faced and the solutions we came up with, as well as UX deliverables like affinity diagrams, identity models, and prototype iterations.

Disclaimer: This project is still underway so this post is still in the making and will be updated continually.

The problem

The pandemic forces individuals around the globe to stay in and isolate themselves. Creative ideas and work-arounds have sprung up to keep up the spirits between social distancing measures. One of these is the rise of virtual parties: people come together online, celebrate, play games, listen to music and enjoy the company that is becoming a sparse commodity.

Our mission was to design a low-fidelity prototype that helps to make this experience a better one. To keep the development process centered around the user, we used Karen Holtzblatt’s Contextual Design method.

Getting the data

In the field

In order to build up empathy and understand the wants and needs of the user we started the design process with qualitative user research.
This meant that each of the team members conducted their own contextual inquiry, an in-depth and on site interview where the user guides the interviewer through the task at hand. Our goal in each of these inquiries was to acutely listen to the user’s needs. To build a product that would satisfy the user in the end, we needed to find out what they are really trying to say and tease out what they are trying to do that they cannot do (yet).
Somewhat interestingly, there were hardly any virtual parties being hosted in the team’s social network - so we needed to create our own.

Challenges and Solutions

1. The first challenge that came up was being the host of the party and, at the same time, the interviewer. This meant that we were in the role of bringing everyone together without actually participating in the party.
   We solved this issue by making clear in the beginning that we would be in the background and, from time to time, take a little time out with the interviewee every now and then.

2. Half of the team members’ interviews were done on-site, the other half remote. While the on-site ones were no different from the method’s usual procedure, it was clear that doing the contextual inquiry remotely meant we needed to find ways to overcome problems imposed by the physical distance.
   One way we solved this was through establishing an additional channel of communication just for the interview. In my case this meant that the subject and myself were part of the party video call on Zoom, but also had a complimentary WhatsApp video call over our phones. This way I could easily give my subject a signal to mute ourselves on the party channel and switch over to the interview channel to talk privately and without interrupting the flow of the party. Doing this on our phones also made it possible to show each other around the room and view sketches made on paper.

3. Another issue was the way the questions and interruptions could change the social dynamic during the party setting. To keep this as little an issue as possible we used the above described setup and decided to concentrate on observing and asking questions in bulk when talking to the interviewee alone.

4. Mistaking oneself for the user is a general challenge for every product design team. This is especially the case when there is strong overlap between the product’s user and the designer, just like in this instance. It is easy to make unchallenged assumptions about the reasons a subject acts a certain way, even more so when that subject is a friend.
   To prevent this, we made it a point to discuss with the user any hypotheses we had about their reasons and intentions. Another way to moderate the issue would have been to interview subjects outside of our own social networks, but due to project scope and resources that unfortunately was not an option.

Understanding the data

After gathering the user data, we came together to interpret and analyze what we had found. Since corona made any in-person-meetings impossible, we used Miro to collaborate for our online sessions. This tool is pretty amazing: It basically offers an infinite white board on which you can hang sticky notes, draw on, insert images, etc - all in sync at the same time, displaying each others cursors so everybody knows who is working on what. We would be connected over Discord, so a simple “come over here and check out what I found” was enough to share and discuss our findings. Having it all digital was also great in terms of keeping it all neat and organized.

To bring together what we had found out during the inquiries, the interviewer would tell the others basically everything that happened, while the rest of the team would either create models or just note down what was said. One challenge was distinguishing the info that was purely sequential from that which contained relevant insights into the user’s needs. To face and deal with this, we made it a point to continually ask the interviewer why a person did something, and to do the same with the interviewees in the coming inquiries.
After we had interpreted all of the contextual inquiries, we basically had a bunch of models and a huge amount of unorganized sticky notes to work with.

Condensing the data

The start

Now it was time to make sense of all the data we gathered. Those piles of virtual sticky notes soon became an all encompassing affinity diagram. In order to do that, we got together (virtually) as a team, and every member took 10 random notes. At first, someone would start and read one of their notes, so that everybody could look at theirs and groups could be formed on the (virtual) wall. After all 10 were up there, the next 10 came. As time went by, more and more notes formed more and more groups, some as small as a single note and some longer than a dozen. After about 15 groups or so, we continued on our own and only announced whenever we would open up a new group. To remind ourselves of the key principles by which we organized the notes, we hung up a few self-reminders:

1. No keyword matching - sort by true meaning, not by superficial themes
2. What is it really about? What are the implications for design?
3. Be fast, not perfect
4. “Ownership is a problem, not a goal” (Karen Holtzblatt)
5. “No one note is critical”

These reminders all tackle critical challenges when grouping the notes. For example, it can be all to easy to group only by topic (say, all notes that reference a specific feature in a program) or get stuck with very few notes for far too long, causing the whole group to lose momentum. It’s also very important that everybody is allowed to reorganize everything, as the method’s nature integrates natural checks in order to get the truest interpretation out of the data at hand. Eventually, all notes were reorganized into a long string of groups - the first milestone was behind us.

Leveling up

Now that all notes are up on the wall and grouped together, we came up with (blue!) headlines for each group. This crucial headline’s job was to summarize everything below it, so that later on you wouldn’t have to reread the ones below. This way categories emerge inductively rather than coming from preset mindsets. Every blue headline is also written in the user’s language and words. This enables it to capture the true meaning perfectly, be easily understandable and transport this meaning to every one reading it, be it the product owner, marketing specialists or developers.
In order to come up with the best possible headlines, we went through the notes in pairs and tested various possibilities before settling. This was done again with the next level (pink notes), before grouping everything in a few broad categories (green notes). This hierarchical structure is especially useful for stakeholders who want to get a good look at the data without spending too much time - all they need to do is start reading from the top.
It was also super important to us to break apart the really big groups that came about initially, because we knew that this was the only way to gain the insights we were looking for. The result:

Contextual Design Models

We also created contextual design models, namely an identity model and a physical model for every interviewee. Their job was to capture the way the users act in the field, what their surroundings look like, and how they relate to the activity with respect to their own identity. Karen Holtzblatt says “they work together with the affinity notes to offer a 360° view of the activity and the user”. To offer a pleasant deep dive into the data for every stakeholder and team member, we consolidated and condensed the models and redesigned them for the best possible experience. Besides documenting the process, the idea is to create an effective immersion experience through good communication. The appealing design and the natural story and user language act as a way in, to interact with the data and ultimately make the product more data and user based. This is what we came up with:

The identity model, using a customized template

The physical model

Crafting Ideas and Concepts

After we finished creating the models and the affinity diagram, we continued by doing what’s known as a “Wall Walk”: Basically taking a fresh look at all the data we have gathered and trying to come up with new hot ideas and noting down key insights that we need to consider when prototyping later on. To provide you as a reader with a clearer picture of what we came up with, here are some things we came up with.

Key Insights

• Music is important but cannot disturb conversation - tastes and selection is hard to agree on
• Games increase a feeling of connectedness but are hard to get started
• Conversation dynamics are worse than irl due to everyone being afraid to cut in all the time
• There’s a desire to chat with friends individually to have more private conversations
• Good audio is key - video is important but secondary
• General party feeling is worse due to: technical issues, less personal vibes (no rituals or real contact), less alcohol and easy distractions (why wouldn’t you just go and make yourself a toast mid-party)
• People sit where it’s most comfy, sometimes at the desk, on the couch etc
• Different kinds of personalities have to be considered:
  • the more extroverted who want to meet new people and lead the group
  • the more introverted who want to be able to disappear unnoticed, stay in the background, talk to people individually and in subgroups
  • the impatient who dislike too much sensory input (music, games, overloaded interface) and are easily frustrated
  • those who only want to take part without having to decide and do much themselves
  • the talkative ones whose strongest focus is conversation

Hot Ideas

• Create a virtual party environment that is as analogous as possible to the the real deal
• Integrate every step from first plans to execution
• Enable comfy participation on the couch / in the living room / etc by giving the user all device and location options
• Make easy switching between devices a no-brainer
• Offer a mode to “crash other parties” (join public ones)
• Enable time-outs and private talks that do not interrupt the rest of the party
• Integrate automatic tech-checks: the user does not have to worry about a thing
• Combine all activities like gaming, listening to music and talking into one product
• Music is chosen automatically using AI, adapting to the tastes of all users
• The party goes on smoothly wherever you go: kitchen, balcony, it’s all possible
• A kind of “Zen-Mode” to turn off any distractions
• Smart Home devices integrate seamlessly, enabling a full-house-party-experience (we’re thinking funky light effects in turn-up-mode and lower brightness in a more chill setting, music on all speakers, and more)
• “Virtual Parties are the new way to celebrate - no matter the virus!”

It was a challenge for us to really get down to the user experience and not focus on technological aspects, but over time we managed to do quite well. With these hot ideas and key insights in mind, we began…

The Visioning Process

Obviously, we needed to make our ideas a bit less abstract. To do so, we drew up several visions of how people’s lives would change by using our product. After creating 4 or 5 of these visions, we consolidated them all and created this comprehensive vision:

Cool Drilldown

The last step before we started prototyping was to ask ourselves a few questions in a Cool Concept Drilldown, in order to design for key principles. Questions and themes included the following:

• Accomplishment (“Does this design support anytime, anywhere access?")
• Connection (“Who matters in the user’s world? How can the system help users touch their people easily and often - while on the go?")
• Identity (“How does the product help promote and reinforce the user’s identity?")
• Sensation (“How can you add a smile or a bit of play to the activitiy - without getting in the way of use?")

[Karen Holtzblatt]

Some features and ideas that stem from this drilldown include:

• Integrating personal assistants (VUIs)
• “This morning you started to create a party on your phone. Do you want to continue here?”
• An option to join into public parties together with friends
• Showcase music history and achievements, sort video streams by highscores
• Offer random possible topics for conversation
• Option to add recently met friends
• Smart Home lamps change color briefly when a new person enters or dim when someone leaves
• Get the party on the phone so people can show personal things with a mobile camera
• Include a “RoboDJ” to deal with the music choices
• Use video backgrounds that create the illusion of everyone being in the same room

We started with a gazillion ideas and possible products in our heads and narrowed it down to only a few million. Now it was time to really make some decisions, create, and test everything in the field.

Paper Prototypes

[to be continued]