How to diagnose traffic and measure relevance?

You are a data scientist at LinkedIn evaluating two separate Home-page product questions. 1. **Home Page to Profile Page traffic declined.** The tracked metric is weekly unique visits to the **Profile Page** that originate from the **Home Page**. Available event data includes: `home_impression`, `people_card_impression`, `people_card_click`, `hover_profile_preview`, `profile_view`, `search`, `message_send`, `connection_request`, `session_duration`, `app_version`, `device_type`, `country`, and `member_tenure`. How would you diagnose the decline? Describe how you would distinguish among: - instrumentation or logging issues, - sitewide traffic changes, - changes in navigation or user paths, - product bugs, - and a *positive* UX change where users no longer need to click into the full profile page because they can already get enough information from Home (for example, a hover preview on a member name). What would your interpretation be if overall LinkedIn session duration stayed roughly unchanged while Home → Profile visits fell? 2. **The Home feed ranking changes from "All content" to "Relevant content only."** You need to determine whether the launch is successful. Design an experiment and measurement framework. Specify: - the unit of randomization, - the primary success metric, - viewer-side metrics, - poster-side metrics, - guardrail metrics, - the analysis window, - and how you would handle tradeoffs between relevance, reach, diversity, and quality of engagement. Also address likely poster concerns: if content is shown to fewer people but to a more relevant audience, how would you determine whether the change is actually beneficial overall?