Let’s chat about my work and how I think about user research.
While my professional work is bound by confidentiality, I've created the following examples to demonstrate my process and analytical capabilities. These projects replicate the frameworks I use to tackle research challenges related to onboarding, early user experience, and behavior over time—using myself as the primary case study.
We'll start with a look at my approach to longitudinals, then dive into some projects focused on video games. While I do have extensive experience in video game research, I used them as they are also well suited for self-reported, small case studies such as these. If you're interested in a more extensive games research project, I invite you to review my in-depth analysis of Dead by Daylight.
First, let’s get into longitudinals. It’s a method that lends itself well to understanding entertainment and creates product impact when trying to understand behavior over time.
While I’ve run many types of longitudinal studies over the years—varying in length, format, and visualization style—my most recent approach was inspired by the classic Napoleon’s March, the piece of information design that first drew me into this work back in grad school.
The chart shown here is a generic recreation of a visualization I developed at Meta to represent a specific type of longitudinal study I’ve designed and led multiple times.
The foundation is a 30-day daily survey completed by 100+ participants. They’re compensated regardless of whether they use the product each day—the only requirement is that they complete the survey. (The first three days include mandatory use so participants can form an informed opinion.)
The survey is lightweight (under 4 minutes) and asks what they did in the app or game and how they felt about it. If they didn’t use it, they’re asked why not and what they did instead. Throughout the study, I layer in 1:1 interviews with selected participants.
IMPACT: In this particular instance, I conducted a dozen studies across similar live-service games and apps. While each product gained value from its individual insights, the greater impact came from aggregating the data—revealing broader patterns and cross-product truths that directly informed and improved future live-service design strategies.
Now, let’s look at how a user researcher (me) might spend their time when they have a plethora of it.
Over the course of 20 continuous weekdays, I tracked if I was listening to listening to something, watching something, or playing something. Every day, I marked a 1 or 0 in each 3-hour segment in an Audio, Game, or Video column. I then analyzed the data via Excel and Claude Opus 4 AI, and crunched it into what a typical weekday looked like. I did it because quantifying behavior and visualizing it is just fun. The results revealed distinct, routine-based patterns for each type of media:
Audio: Consumption of music and podcasts was highest during task-oriented activities that allowed for passive listening, such as cooking and commuting for my child's school run.
Gaming: Engagement with video games was characterized by intermittent sessions throughout the morning and early afternoon, typically concluding around 3 p.m. as the focus shifted to family activities.
Video: Video consumption followed a consistent bimodal pattern: a morning session for solo viewing of daily shows, and a dedicated evening session for communal watching of movies and series with my family.
CONCLUSION: When work is not an impediment, my media consumption is not random, but is instead highly structured and dictated by the context of my daily obligations. The data reveals a clear segmentation of media types: Audio serves as a companion to routine tasks, Gaming occupies periods of personal free time, and Video is reserved for dedicated moments of relaxation, both individual and shared. Ultimately, my engagement with different media is a direct reflection of my daily schedule and social environment.
Next up, the first 15 matches of FORTNITE.
The below chart of 15 matches represent a new player’s experience with this incredibly popular and influential title. Extrapolated out, it illustrates what I might create based on dozens or hundreds of players.
I rated multiple aspects and took multiple metrics. I created this chart to visualize some of the main points and to tell a quick story of my experience.
I analyzed this data (and all other data on this page) as I would if it was a larger data set. I crunched the numbers in Excel and then used, among other methods, Claude Opus 4 AI to dig deeper. If I were at a company, I’d collaborate with a data scientist to help me massage the numbers and compare to telemetry.
I’ve found that one of the prime indicators in any type of game is whether or not the player feels like they had a fighting chance. For Fortnite, I always did, even if I died and even if I died early. In fact, statistically, the strongest predictors of fun were 1) feeling like I had a fighting chance, 2) if the match was on the longer side, and 3) if the challenge was high, but not frustrating.
CONCLUSION: The data suggests that increasing match times in the initial rounds could boost players’ feeling that they had more of a fighting chance, which in turn could encourage longer play sessions. This effect may be driven by increased awareness of weapon placement, enemy movement/skirmishes, and/or overall map awareness.
Next up, the first 120 minutes of ELDEN RING versus those of THE WITCHER 3.
Both are open-world, third-person fantasy games—but with very different design philosophies. While I tracked more variables than are shown in the charts below, the visualized data tells a clear story. Additional metrics included learning how to play, feeling like quitting, and how often I died.
Elden Ring delivered high challenge and high frustration, paired with low clarity and minimal onboarding—conditions that only worsened over time. I rarely understood what I was supposed to be doing, and died frequently and easily. It felt as though the game was designed to punish rather than guide, making progress feel earned but exhausting.
MEANWHILE, The Witcher 3’s design consistently set me up for success. From the start, I had clear direction, minimal deaths, and strong, consistent guidance. I always knew what I needed to do and where to go. Any dips in fun were typically due to long, unskippable cutscenes rather than gameplay issues.
CONCLUSION: Assuming FromSoftware’s goal is to broaden Elden Ring’s appeal and increase long-term engagement among newer or more casual players, the data suggests that playtime could be improved with the addition of optional, clearer in-game guidance.
This might include better cues for the alpha path, reminders that running away is a valid strategy, and brief pop-ups to reinforce combat basics/strategy. These could ease early frustration without sacrificing the game’s core challenge.
To put a cap on this analysis, let’s compare one more rating: wanting to stop playing.
I also tracked my desire to stop and quit playing at regular intervals. When charted, this metric reinforces the broader analysis—though it’s compelling to see the same story unfold through a different emotional lens.
Over the course of two hours with Elden Ring, my urge to quit steadily increased. Despite the time invested, I had learned very little and still didn’t understand what I was supposed to be doing (and no—I didn’t look up tips online). The game offered minimal guidance, which compounded my frustration.
In contrast, The Witcher 3 rarely made me want to stop. When I did feel that urge, it was typically during long cutscenes that I couldn’t easily skip—not because the gameplay lacked clarity or momentum. In fact, the frustration came from the game insisting I focus on its story, rather than giving me the agency to dive into the experience on my own terms.