Kiosk
Ruby GmbH · Self Check-in · 2025
A full redesign of the Ruby self check-in kiosk, built to close one gap: the original made guests work the way the system works, not the way they think. Three friction points, sharpest in data collection, where guests from nine countries each face different legal requirements, all validated through comparative testing across 180 tests.
Year
2025 — 2026
Role
Lead Product Designer · Research · Interaction Design
Team
Product Designer · Product Manager · Engineers
Platform
Web Kiosk
The problem
One interface. Nine countries. Guests couldn't see where they were, what came next or how long it would take.
Every friction point traced back to the same root: the interface served the database, not the person using it. One field per screen, no progress indicator, uncertainty from the first screen. Three surfaced in testing: a data collection flow structured the way the system stores information rather than the way guests think about their own; a business invoice flow that caused guests to enter personal home addresses where company addresses were required; and guest list controls buried so far below the primary action they were effectively invisible.
How I tested it
I built a functional prototype using AI-assisted tooling, close enough to the real product that guests could complete the full flow without assistance. I then ran 180 moderated usability tests, split evenly between the current version and the redesign, across three check-in scenarios — 30 per version each — including business guests and groups.
The flow presented one field per screen with no way to gauge scope. Business guests entering company address details would frequently enter their personal address instead. The field structure gave no cue that a different address was expected.
Fields grouped by type — personal info, ID, address — with conditional logic per nationality and legal requirement. The right fields appear. The irrelevant ones don't. Breadcrumbs show exactly how many steps remain from the first screen.
Before
After
Results
AI in the process
I integrated AI tools into both the research and design phases. For research: synthesising guest feedback and support data faster than manual analysis allows. For prototyping: generating a functional, testable version of the redesign in a fraction of the time a coded prototype would take. The design decisions are mine. The speed to validate them wasn't.
Outcome
Measured on real Ruby Hotel guests — full check-in from first screen to confirmation. Solo guests: 3m36s (v2.0) to 2m53s (v3.0). Groups of two: 5m02s to 3m56s. Across 180 tests with real hotel guests.
Solo check-in time
first implementation - july 2026
