← Microsoft Interview Insights
I jumped straight to view counts and completion rates, which felt obvious in retrospect.
Start by clarifying what 'engagement' means in the context of Instagram Stories—whether it's views, replies, taps, or completion rates—and then segment the metrics by user cohorts, content types, and time periods to pinpoint where the decline is occurring. Use a funnel-based approach to diagnose the drop-off and prioritize improvements based on impact and feasibility.
Pro tip: Don't just list metrics; show how you'd triangulate them to form a hypothesis. For example, if completion rate drops but views stay flat, it might indicate longer stories or less engaging content, not a reach problem.
Clarify which engagement metrics matter most for Instagram Stories, such as completion rate, replies, taps forward/back, and exit rate. Align these with business goals like ad revenue or user retention.
Break down metrics by user cohorts (new vs. existing, demographics), content types (photo vs. video, length), and time (daily/weekly trends) to isolate the decline.
Map the Stories consumption funnel: impression → view → completion → interaction. Identify where the biggest drop-off occurs and compare with historical benchmarks.
Based on the funnel analysis, generate hypotheses (e.g., algorithm change, content fatigue, UI update) and prioritize which to test based on potential impact and ease of implementation.
Suggest specific product changes (e.g., algorithm tweaks, new creative tools) and define success metrics (e.g., increase completion rate by X%) to measure improvement.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.