Company Context

Meta operates products at global scale, and Instagram is one of its flagship consumer platforms with hundreds of millions of daily users across creators, casual users, and businesses. New features can create meaningful engagement upside, but shipping the wrong feature can add complexity, fragment the experience, and consume scarce research and engineering capacity.

Problem

The Instagram team is considering a new feature: a Close Friends Reels feed that lets users share short videos only with a smaller audience and browse those private Reels in a dedicated surface. Product leadership wants to know whether users actually want this feature, which user segments value it most, and whether it solves a real unmet need versus duplicating Stories, DMs, or existing Close Friends behavior.

Early signals are mixed. Internal brainstorming suggests the feature could increase sharing among users who feel uncomfortable posting publicly, but prior launches on Instagram have shown that adding new sharing surfaces can confuse users and reduce content creation if the value proposition is unclear. The team has 6 weeks to recommend whether to build an MVP, refine the concept, or stop investment.

Deliverables

1. Define the core user problem and the hypotheses you would test before deciding to build.
2. Create a research plan to determine whether Instagram users want this feature, including methods, target segments, and sample strategy.
3. Explain how you would distinguish between stated interest and real user demand.
4. Recommend what evidence would be sufficient to move forward with an MVP versus deprioritize the feature.
5. Identify the key trade-offs and risks in researching a feature that overlaps with existing Instagram surfaces.

Constraints

• Research decision needed within 6 weeks.
• Limited ability to build a fully functional prototype; lightweight concepts and clickable mocks are feasible.
• Must consider global users, but initial research budget only supports deep qualitative work in 3 markets.
• The team wants a recommendation before committing engineering resources to a full build.