I started with user segmentation, which felt right, but I spent too long listing disability types instead of picking one and going deep.
Start by clarifying the scope—focus on a specific LinkedIn feature like the feed or job search—and define the target disability segments (visual, auditory, motor, cognitive). Then, apply a user-centered design process: identify pain points through research, prioritize solutions using frameworks like RICE, and propose inclusive features that benefit all users. Emphasize accessibility as a core product value, not an afterthought, and discuss how you'd measure impact and iterate.
Pro tip: Demonstrate awareness of WCAG 2.1 AA standards and mention that designing for accessibility often improves usability for everyone (e.g., captions help in noisy environments). Also, highlight the importance of involving users with disabilities throughout the design process to avoid assumptions.
Ask clarifying questions to narrow the focus to a specific LinkedIn feature (e.g., feed, messaging, job search) and user segment (e.g., blind, low-vision, deaf, motor impairments). This shows structured thinking and avoids boiling the ocean.
Describe how you'd research pain points: conduct interviews with users with disabilities, analyze support tickets, and review accessibility audits. Identify key barriers such as screen reader compatibility, keyboard navigation, and color contrast.
Brainstorm features that address the pain points (e.g., alt-text for images, captions for videos, voice navigation). Prioritize using a framework like RICE (Reach, Impact, Confidence, Effort) or MoSCoW, considering both user impact and technical feasibility.
Propose metrics to measure success, such as task completion rate for users with disabilities, accessibility compliance score, and engagement metrics. Include qualitative feedback from usability testing.
Outline a plan for iterative testing with users with disabilities, gathering feedback, and refining. Discuss how to scale successful features across LinkedIn and ensure ongoing accessibility compliance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.