Overview · full case study under NDA
Large-scale human factors research for the AirPods product line — designing the study, building the instrument, running the analysis, and turning it into direction that hardware and design teams can act on.
This is a public overview of how the work is done — study design, methods, and tools. Findings, internal materials, and product-specific detail are covered by NDA. The full case study is available on request; details at the end of the page.
01 / Overview
I lead large-scale human factors studies for the AirPods product team, evaluating device fit, comfort, and motion stability under real-world usage conditions. With 400+ participants across 3-hour sessions, the work sits at the intersection of physical ergonomics and behavioral research — translating large, complex datasets into actionable direction for hardware and design teams.
The goal is to move from anecdote to rigorous, quantified evidence — the kind that settles a spec decision instead of starting another debate. What that evidence showed, and what changed because of it, is the part that stays behind the password.
02 / Methods at a glance
What I designed
Purpose
Key methodological choices
Survey instrument
Purpose
Capture preference, attribution, and behavioral intent post-session
Key methodological choices
Question logic, scaling standards, bias controls, pilot iteration
Session protocol
Purpose
Structure 3-hour participant sessions consistently across 400+ people
Key methodological choices
Objective measures before subjective scales; order controls
Synthesis framework
Purpose
Translate mixed-methods data into executive narratives
Key methodological choices
Qualitative + quantitative integration; R for survey analysis
Password-protected · shared case by case
Full case study · access
The gate isn't a gimmick. Findings, internal materials, and product-specific detail sit under NDA, so the full write-up is shared case by case rather than published openly.
The protected version is the actual write-up: how the 120-question instrument was designed and pressure-tested, the R analysis and the automation built around it, how findings were carried into product and engineering decisions, the follow-on AirPods Max study, what the research found, and what changed as a result. If you're evaluating me for a research role, that's the version worth reading — and I'm glad to share it.
Email. Use the Email me button below and mention the Apple study — I'll send the password over.
LinkedIn. Or message me there instead — the link is in the footer. A line about your role and what you're hiring for helps me point you at the sections that matter most to you.
apoorvarev.designs@gmail.com