A timed design test: reimagine how commuters buy and refill transit cards on a 10-inch kiosk. I treated the clock as the brief — real riders at Grand Central, decisions scored on a matrix, and a tested hi-fi prototype, all inside ten hours.
00 Overview
The brief: design a transit-stop kiosk where regular commuters buy and refill their cards — show the flow, the reasoning, and at least one hi-fi mockup. Ten hours, start to finish. My reframe: with a hard time-box, the deliverable isn't just screens — it's showing exactly where evidence, decisions, and craft each earn their minutes.
Lines pile up behind whoever is decoding fare plans at the screen. Locals fly through; first-timers stall on plans and payment. Two HMWs: reduce that anxiety, and make buying a card intuitive.
A fast default-value purchase, a one-click preset refill, and a card account — chosen from nine candidate flows on a user-value × engineering-effort matrix, then validated with click heatmaps and an 8-rider survey.
Field observation at Grand Central during the morning rush, six intercept interviews, affinity mapping, flows, sketches, hi-fi prototype, and usability testing — every step time-boxed.
01 Context
Ten hours forces the question every real project asks eventually: where does evidence matter most, and what are you willing to decide without it? I planned the time like a budget — research where the risk was highest, craft where the evaluation would happen.
The line behind you is the real pressure. Speed for the person at the screen is calm for everyone behind them.
Fare plans are policy documents rendered as buttons. First-timers shouldn't need to understand the MTA to ride it.
02 Clarify Problems
Instead of designing from memory, I went to the machines. Thirty minutes of observation at four kiosks during the 8am rush, then six intercept interviews — enough signal to know exactly which problems deserved the remaining hours.
Field Observation · Grand Central, 8am
20+ riders, 4 kiosks: each person took 1–5 minutes, and the queue never shrank. Locals tapped through on muscle memory. Travelers stalled on plan choices; cash payers panicked mid-flow and switched to card. The kiosk wasn't slow — uncertainty was.

6 Interviews · Affinity Mapping
Interview notes clustered into payment methods, time, plans, refill, receipts, and language. Three findings carried the weight: nobody wants to wait in line just to refill; locals know the drill while first-timers drown in plans; and multiple payment methods are non-negotiable.

Persona · The Target Commuter
Shandra, an insurance agent who rides daily and refills weekly, became the yardstick: independent, busy, mildly anxious about the queue behind her. Every flow decision was tested against her patience.

03 Shape Concept
For each scenario — buy a new card, refill an existing one — I drew three candidate flows, then scored them the way a product team would have to: user value against engineering effort. Opinions argue; matrices decide.
New riders get a one-tap default-value card; anyone who wants specific passes finds the full catalog one level deeper. High user value for both audiences, justifiable build cost.
The ideal flow lets riders save a preset (amount + payment) and refill in one tap. I recommended it — and explicitly priced the fallback: if engineering can't fund the account feature, option two still captures most of the value. Recommendations should come with their own plan B.
Each card carries a number and a lightweight account holding the preset. It is the infrastructure bet behind the one-click promise.
04 Design & Validate
Ten hours don't allow a full design cycle — so the cycle was compressed, not skipped. Four moves, in order: sketch everything, build only what testing needs, put it in front of riders, and let the data pick the answer.
A full screen-by-screen pass in pencil. At this fidelity iteration is free — layouts, payment states, and dead ends were all resolved before a single pixel was spent.
No decoration passes. Only the two flows under evaluation were built at high fidelity — buying a new card, and the one-click refill.
The prototype went straight back to users: first-click heatmaps on the critical payment step, with eight riders voting with their fingers.
Usability · Click Heatmaps + Survey
Heatmaps on the payment screen confirmed the three-method layout worked — card dominated, but cash and mobile earned their buttons. The 8-rider survey split exactly as the research predicted: in a new city people want a default value; in their own city they want their plans. "The simplest would be a default value for new clients," one tester wrote — the design already agreed.

The plan question went to a preference survey. New-city riders leaned to a quick default; home-city riders wanted their own plans — confirming one flow had to serve both.
05 Outcome
Not just screens — a defensible argument. Every design decision in the final prototype traces back to something a real rider did or said that week.
The submission didn't just show a favorite — it showed the runner-up and the conditions under which the team should choose it instead. Design recommendations that respect engineering capacity get built; ones that don't get shelved.
06 Reflection
Looking back from the Booking.com years, this little challenge is where the habits began: measure before designing, score options instead of debating them, and ship every recommendation with its trade-offs attached.
Spending the first fifth of a tight budget on real users felt expensive at hour two and cheap by hour ten. The value × effort matrix from this challenge became the same muscle behind the impact × confidence prioritization I later ran at Booking.com.
Accessibility would be a first-class requirement, not an afterthought — reach ranges, language switching, and screen-reader flows for a public kiosk. And I'd recruit beyond convenience sampling: eight testers taught me directions, not confidence intervals.