I spent the first few minutes trying to define the problem space and nearly talked myself into a corner debating whether to focus on discovery (finding opportunities) or commitment (following through).
Start by clarifying the goal and scope of the product, then segment users and identify key barriers to volunteering. Brainstorm solutions that leverage Meta's strengths (social graph, events, groups) and prioritize based on impact and feasibility, defining success metrics and potential risks.
Pro tip: Anchor your solution in Meta's existing ecosystem (e.g., Groups, Events, Fundraisers) to show you understand how to leverage platform strengths and drive adoption. Also, proactively address privacy and trust concerns, which are critical for social good products.
Ask clarifying questions to understand the objective: is it to increase volunteer hours, number of volunteers, or retention? Define the target audience and any constraints (e.g., regions, causes).
Segment potential volunteers (e.g., students, professionals, retirees) and identify their motivations and barriers (time, awareness, trust, ease of access). Use empathy to ground your solution.
Generate ideas that leverage Meta's platform: social proof, event integration, group volunteering, matching algorithms, gamification, and partnerships with nonprofits. Focus on reducing friction and increasing motivation.
Evaluate ideas based on impact (potential to increase volunteering) and feasibility (technical, resource, adoption). Select a minimum viable product to test core assumptions.
Establish success metrics (e.g., number of sign-ups, volunteer hours, retention rate) and consider potential risks (privacy, safety, unintended consequences). Outline a measurement plan.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.