I started with time-on-screen which felt obvious, then they pushed back asking how I'd distinguish someone who left the tab open versus someone who actually read.
Start by defining an 'effective read' as a user consuming content in a way that delivers meaningful value, then propose a multi-layered measurement strategy combining engagement, satisfaction, and long-term retention metrics. Validate the definition through experiments that test whether optimizing for these metrics improves overall user well-being and platform health.
Pro tip: Acknowledge the tension between short-term engagement metrics (like clicks) and long-term user value, and propose using holdout groups or long-term impact studies to avoid optimizing for vanity metrics that harm user experience.
Articulate a clear, user-centric definition of an effective read, such as when a user finds content valuable enough to spend meaningful time on, engage with (like, share, comment), and return for more.
Choose a combination of metrics: depth (time spent, scroll depth), breadth (posts read, unique authors), engagement (likes, shares, comments), and satisfaction (surveys, sentiment). Include counter-metrics like bounce rate or negative feedback.
Establish thresholds for what constitutes an 'effective read' based on historical data or user research, e.g., minimum time spent (e.g., >10 seconds) and at least one interaction, while avoiding arbitrary cutoffs.
Propose A/B tests that manipulate feed ranking or content to see if changes in the defined metrics correlate with improved user retention, satisfaction, or well-being. Include long-term holdout groups to measure lasting impact.
Analyze experiment results to confirm whether the metrics truly capture user value. If not, refine the definition and metrics, and consider qualitative feedback or causal inference methods to strengthen the link.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.