Research Communication · Executive Narratives · Children's Gaming Platform via AnswerLab · 2023
Mama, What's an Algorithm?
A research communication system that moved a major children's gaming platform from session notes to a clear product decision about whether and how to integrate coding into its core experience.


The Problem
Researchers had spent weeks in sessions with kids and young adults across different relationships with coding. What they had was rich. What they didn't have was a format that made the differences between groups legible to a client making actual product decisions. Specifically, whether to add a coding mechanic to a large-scale online game, and if so, how to position it for kids who'd never touched a line of code versus kids who already had. The research and the decision were in two different languages.
My Role
I was responsible for the full communication architecture of this deliverable determining which variables were worth comparing across the three groups, designing the segmentation framework, and building the presentation layer that took the work from session notes to a format the client could use to make a
product decision.
What I Built
Three groups emerged from the research: kids who coded, kids who'd tried it, and kids who hadn't at all. The differences in motivation, frustration, and daily schedule weren't subtle — they were the whole story. I built a segmentation chart that mapped each group across friction points, prior experience, and opportunity areas so the client could see at a glance where the product gaps were and who they were actually designing for. That fed into a presentation deck laying out findings, phase maps, and strategic opportunities for how coding could fit or fail inside a child's gaming day.
What Changed
The friction points that had been spread across pages of session notes were now organized by user type and readable in a single reference. Product conversations about how coding gets introduced and positioned for different kids became something the client could actually have without a researcher in the room to translate.
What I Learned
The research wasn't ambiguous. The data was clear about which kids were ready for a coding mechanic and which weren't, and what the friction points were for each group. What was hard was building a communication format where the client could see all three groups simultaneously without collapsing them into a single "kid user." The segmentation chart solved that. What this project clarified was that the most important design decision in research communication isn't visual, but its deciding which distinctions are worth preserving, and how many a stakeholder can hold at once before the research stops being useful.