This question evaluates product analytics and experimentation skills, including metric selection, entity and dimension modeling, cohort and funnel analysis, diagnostic investigation, and experiment design for assessing a privacy feature's impact.

Context: You are designing a social network feature that lets users set their account to private. Private accounts restrict content visibility to approved followers only. Follow relationships require a request/approval flow.
Answer the following:
(a) Define the product briefly and list the primary entities/dimensions you would model (e.g., user type, privacy state, relationship state, follow request state, viewer role, content type, session source, platform, locale).
(b) Propose the north-star and guardrail metrics for this feature. Include metrics that would most clearly reveal a decline in user engagement among private-account users versus public users (e.g., DAU, sessions/user, posts/user, outbound follow requests sent, approval rate, impressions, view-through rate, inbound requests, acceptance latency, replies/messages, creator retention).
(c) Suppose engagement for private-account users drops week-over-week. What is your investigation plan? Specify the cuts, funnels, cohorts, and counterfactual slices you would examine and the hypotheses each would confirm or refute.
(d) Recommend one or two experiments or changes to validate or improve the feature’s value proposition. Define success metrics, guardrails, and expected trade-offs.
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