I spent probably too long on the user segmentation piece and then rushed the actual feature design at the end.
Start by clarifying the goal and scope of the job search product within Facebook's ecosystem, then segment users and identify their pain points. Prioritize features based on impact and feasibility, and outline how you would measure success and drive adoption.
Pro tip: Leverage Facebook's unique social graph and existing user behaviors to create a differentiated job search experience, rather than replicating LinkedIn. Focus on how the product can drive engagement and monetization for Facebook.
Ask clarifying questions to understand the objective: Is this a standalone product or integrated into Facebook? What user segments are we targeting? What are the success metrics?
Identify key user segments (e.g., job seekers, employers) and their pain points in the job search process. Consider how Facebook's data and social connections can address these.
Generate potential features (e.g., social referrals, skill endorsements, job matching) and prioritize using a framework like RICE or impact/effort matrix.
Outline key metrics (e.g., applications per user, successful hires) and propose a go-to-market plan, including launch partners and growth loops.
Discuss potential risks (privacy, competition) and how you would mitigate them. Suggest an iterative approach with MVP and user feedback.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.