← Microsoft Interview Insights
My first instinct was to jump straight to solutions, which is exactly the wrong move.
Start by clarifying the scope and validating the data, then segment the traffic drop to isolate the cause. Prioritize hypotheses based on impact and likelihood, and propose a response plan that addresses both immediate mitigation and long-term prevention.
Pro tip: Show that you can balance data-driven analysis with business acumen by considering external factors like seasonality or competitor moves, and always tie your investigation back to user impact and business metrics.
Ask clarifying questions to understand the context (e.g., time frame, metrics, business impact) and confirm the data's accuracy by checking analytics tools and data pipelines.
Break down the traffic drop by dimensions such as device, browser, geography, user type, and acquisition channel to identify where the drop is concentrated.
Brainstorm potential causes across internal factors (e.g., site changes, bugs, content updates) and external factors (e.g., seasonality, competitors, algorithm changes).
Rank hypotheses by impact and likelihood, then validate them using data analysis, A/B tests, or user research to confirm the root cause.
Implement fixes or mitigations, communicate with stakeholders, and set up monitoring to track recovery and prevent future drops.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.