The pandemic challenged our user research team to adapt what were once primarily in-person research methods to remote-only methods. In many respects, this challenge forced our team to improve our methods and processes for the better.
Beyond better research methods and processes, the pandemic also forced our team to come up with more creative, effective, and collaborative synthesis artifacts. In a world where everyone is working from home, our research artifacts had to stand out amidst an unprecedented amount of competition, all vying for our stakeholders’ attention. Through collaboration with our data science team and an emphasis on data visualizations and compelling comics, our team has developed multi-modal artifacts that are effective in grabbing the attention of our stakeholders, pandemic or no pandemic.
Synthesizing qualitative data using data visualization and data science techniques
Just as having physical space is helpful when it comes to materializing complicated data into clear concepts, having physical artifacts is helpful when it comes to communicating abstract insights and making them more tangible. When we originally thought about deliverables for our user needs research, we immediately thought of physical posters. Without a physical office space to display such artifacts, we had to pivot to an artifact that could be consumed digitally and individually.
There were a few key needs that users mentioned more often than others: strategy, creating communication materials, research, and knowledge management. However, the needs that came up most differed by the kind of job participants had. Analysts, for example, mentioned research-related tasks more often than participants in Government Affairs roles.
We wanted to communicate the key needs users had across roles as well as role-specific needs. In addition, we had insights around the top pain points, tools used, and who users collaborated with according to what need they were talking about.
To empower people across our company to explore this data both at a high level and more granularly, we created an interactive bubble chart that communicated high level needs across roles while allowing people to filter by role. People could drill into specific pain points, tools used, and collaborators associated with each need by clicking the need’s bubble.
The bubble chart transformed 785 distinct qualitative data points into a simple and explorable visualization. Distilling the volume and complexity of data we had into something clear and easily digestible was no easy feat. And yet, while this approach gave us the impact we were looking for in terms of generating interest in our research much like we imagined posters would, it did not tell the story of our research. The bubble chart did a good job of telling you what users talked about needing to do as part of their job, pain points they had, tools they used, and who they collaborated with. It did not do a great job of telling you why those things were important to their jobs or what doing those things looked like in practice.
To better tell the story of our research, we first expanded our research efforts to ensure we were talking with enough participants to represent the different roles we were interested in. After 30 journey mapping sessions with participants from representative roles, we now had 1,521 qualitative data points that we coded with 599 distinct tags, generated using our grounded theory approach.
With the volume of data we had, we didn’t want to lose the ability to easily explore the data through a visualization like the bubble chart. However, we also needed a more sustainable way of generating the chart. Our initial prototype, created in Figma, was just that — a prototype. It wasn’t actually connected to our database of qualitative data and we couldn’t enable rich filtering capabilities through the prototype alone.
This is where our data science partners stepped in. Since our data was coded, and therefore structured, into a centralized database, we were easily able to export and share a .csv export of our qualitative data with our data science team. With this data, our data science team created a live version of our bubble chart, complete with robust filtering capabilities and additional insight into key terms based on a NLP (natural language processing) analysis.
Having our data in an easily explorable format like a filterable dashboard empowers people across our company to use this user data to answer questions like:
- Which needs do users encounter the most?
- Which needs do users associate with more negative experiences?
- Which tools are used for different needs?
- Which needs relate to mentions of key terms like “collaboration?”
There are thousands of ways to filter our qualitative journey mapping data, and our dataset will only grow over time as we continue to complete journey mapping research and feed it into the system. Our dashboard therefore serves as our evergreen source of empirical evidence about our users’ jobs, and anyone in our company is able to query it to inform whatever decisions they are making on any given day.
Typical research initiatives aim to answer a set of limited, defined questions for a limited, defined audience of stakeholders. By democratizing our data through a dashboard, we have unlocked the potential for our data to answer thousands of questions beyond the scope of our initial research initiative, for anyone in the company, regardless of position, department, or level.
Synthesizing qualitative data through comic strips
While our data science-powered dashboard solved our problem of sustainability enabling people across the company to explore and filter our data, it did not solve our problem of not having a method for telling the stories behind the numbers. Inspired by Patti Carlson’s talk, “Level Up the Influence and Impact of Research Insights With an Internal Marketing Plan,” we decided to take an unconventional approach and tell the story of our users’ needs through the medium of comic strips.
For each role we researched, we created a metaphorical character based on the Knights of the Round Table legend. Like the legend, while each of our roles had distinct characteristics, they all congregated and collaborated together in order to achieve shared goals.
For example, one of our target user types is a Researcher/Analyst. It helps to think of the Researcher/Analyst role as “Merlin” from the Knights of the Round Table legend because Merlin has no skin in the game, he’s just there to support the rest of the Round Table. Just as Merlin keeps an eye on the world with his perfect knowledge of everything that’s ever happened in the past and the future, Researcher/Analysts monitor large amounts of information. If you have a question, Researcher/Analysts can find an answer for you.
Using this metaphor as a jumping off point, we created a comic strip that details what a day in the life is like for a Researcher/Analyst, including what examples of their top needs look like and links to the actual video clip examples we have of these needs from our journey mapping research.
Our filterable dashboard democratized our data to the rest of the company. We also created a findings deck to communicate high-level insights. The comic strips, critically, made all of our data and insights memorable.
In an age where our attention is commodified, during a pandemic that has robbed us of the in-person social pressure to be polite and pay attention to people who are talking to you, simply doing good research is not enough. It doesn’t matter how insightful or useful research is if no one makes a conscious effort to consume it.
In order to have the impact our data and insights deserved, we had to package our research in a way that could grab our stakeholders’ attention. Our research had to stand out from all the other stimuli competing for our stakeholders’ attention. Beyond just other tabs and notifications, our research had to, somehow, compete against the puppies, kittens, and toddlers that are now fixtures in our stakeholders’ work-from-home realities.
While perhaps not as compelling as puppies, the response we’ve received to our synthesis artifacts has been phenomenal. When we first introduced our metaphorical characters to the company, we received comments like “I will never forget that Advocacy users are like Lancelot.” When we showed off our filterable dashboard and findings deck, we got responses like “This is the strongest output I’ve seen in my career.” Having that kind of impact and stickiness is exactly what we were looking for. Had we not been pushed by the pandemic to pursue multimodal artifacts that could be consumed digitally and individually, we may have not been challenged creatively to design the array of artifacts that we did.
Sharing and promoting insights from home
If the pandemic has taught us anything, it’s that remote work requires more emphasis on communication, not less. Not only do we need to communicate more to work as effectively as we did in the office, we also have had to find multiple methods through which to communicate. With ad-hoc water cooler encounters, lunches, and social events out of the question, we had to find new ways to continue to communicate with our colleagues outside of the standard email, meetings, and Slack messages that quickly became noise as we all shifted towards remote work.
For us as user researchers, this meant expanding our artifacts beyond what would be helpful in in-person presentations and demos. While our findings deck still serves this purpose for stakeholders who are most engaged and persuaded by oral or written argument, our filterable dashboard allows stakeholders who are more data-driven to explore the data themselves. Our character-based comic strips provide a third, equally important medium for stakeholders who are persuaded by story.
Having these multiple points of entry into our research ensures we are meeting our stakeholders where they are and where their interests lay. It ensures that we aren’t siloing our data and insights into an ivory tower but rather connecting our research to the people and problems it’s meant to empower and inform.
Certainly we’d prefer to go back to connecting with people — our stakeholders, our team members, and our participants — in person. But it’s undeniable that the constraint of working remotely has inspired us to be more creative in how we conduct research with participants, how we analyze data in a way that can be shared and cross-analyzed by others like our data science team, and how we can synthesize that data into artifacts that are compelling enough to retain the attention of our stakeholders regardless of the constant distractions we all have going on these days, digital and otherwise.
The challenge of adapting our primarily in-person processes to be remote, in short, made us more creative, more effective, and more collaborative as a team. We look forward to working in-person one day again, but until that day comes, we’re grateful to have had the opportunity to rise to the challenge of pandemic-friendly user research. We’re better researchers because of it.