I went straight to segmenting users by commute patterns, which felt right, but I spent too long on the obvious stuff like availability and bike condition before getting to anything interesting.
Start by clarifying the goal of the bike system (e.g., reduce campus congestion, promote sustainability, improve employee/student mobility) and segment users (commuters, visitors, facilities staff). Then prioritize 2-3 key user needs based on impact and feasibility, and translate each into concrete design decisions (e.g., app features, bike placement, maintenance).
Pro tip: Anchor your answer in Google's culture: emphasize data-driven decisions, user empathy, and scalability—show how you'd measure success with metrics like ride frequency, wait time, and user satisfaction.
Ask clarifying questions to understand the system's purpose (e.g., reduce car usage, improve health) and constraints (budget, campus layout, regulations).
List primary user groups (e.g., employees, interns, visitors) and their distinct needs (speed, convenience, accessibility).
Use a framework like impact vs. effort to select 2-3 critical needs (e.g., quick access, reliable bikes, safety).
For each need, propose specific features (e.g., mobile app for real-time availability, solar-powered stations, ergonomic bikes).
Suggest metrics to validate design choices (e.g., average wait time, rides per day, user satisfaction scores).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.