Details sanitized and shared with appropriate discretion. Specific metrics and artifacts available upon request.
Continuous Generative Research Program for a Mobile App at Scale
Built an always-on qualitative research program for United Mobile (70M+ users), pioneering continuous generative research aligned to OKRs across six platform touchpoints.
Detailed case study available on request
This project contains confidential process details and internal metrics. The full case study — including methodology decisions, process documentation, stakeholder artifacts, and specific outcome data — is available to hiring managers and recruiters.
Summary
United Mobile serves 70M+ users across a sprawling multi-platform ecosystem — iOS, Android, mobile web, desktop, airport kiosk, and in-flight entertainment. When I joined as Sr. UX Researcher, there was no continuous research practice: studies were reactive and episodic. I built an always-on generative research program that maintained a live stream of qualitative insight and aligned it to company OKRs, giving product teams the longitudinal understanding of user behavior that episodic studies can’t provide.
Role: Sr. UX Researcher → Lead UX Researcher · Timeline: Dec 2022–Present · Team: Cross-platform product organization · Methods: generative qual, IDIs, continuous discovery
Problem & context
[PLACEHOLDER: describe what “no continuous research” looked like in practice — what decisions were being made without insight, what the team was asking for that the research function couldn’t provide, and what the stakes were for a 70M+ user app]
The challenge with multi-platform research at United’s scale isn’t finding participants — it’s structuring insight so that it’s legible and useful to six different platform teams simultaneously, each with their own OKRs and release cadences.
My role
I designed the continuous research program, built the recruitment and scheduling infrastructure, defined the research cadence and templates, and socialized the insight outputs with cross-platform product leadership.
Approach & decisions
[PLACEHOLDER: describe the core design decisions — cadence (weekly? biweekly?), how you structured screeners for platform-specific vs. cross-platform cohorts, how findings were synthesized and distributed, how you kept research aligned to OKRs without over-scripting the generative work]
The central tension in continuous generative research is between structure (enough to make findings comparable over time and across platforms) and openness (enough to actually surface what you don’t know). I resolved this by separating the standing research questions (aligned to OKRs) from the platform-specific probes (adjusted each cycle).
Process
[PLACEHOLDER: describe a representative research cycle — recruitment, session design, facilitation, synthesis, distribution. Note the cadence and any workflow tooling that made it sustainable at scale]
Deliverables
- Continuous research program design and cadence documentation
- Platform-specific screener and discussion guide templates
- Synthesis framework for cross-platform insight comparison
- Regular insight briefs distributed to platform product teams
- OKR-aligned research findings across 500+ qualitative sessions
- [PLACEHOLDER: sanitized example of an insight brief or synthesis artifact]
Impact & outcomes
- Sustained an always-on stream of qualitative insight across all six platform touchpoints.
- Qual from 500+ users aligned to company OKRs, giving product teams a shared language for user needs.
- [PLACEHOLDER: specific decisions influenced, feature changes driven by continuous research, stakeholder adoption metrics]
- Pioneered a research model that the team continued and scaled after the initial program design.
Reflection
[PLACEHOLDER: what did you learn about sustaining a continuous program without burning out the team or participants? What would you design differently?]
The hardest part of continuous research isn’t the research — it’s the synthesis and distribution. If findings don’t reach the right people at the right time in the right format, the research might as well not have happened. I’d invest even more in the dissemination infrastructure from day one.