I went top-down through the funnel stages which felt right but I think I rushed past acquisition metrics too fast and spent too long on activation.
Start by mapping the Premium subscription funnel into distinct stages (e.g., ad impression → landing page → sign-up → free trial → paid conversion) and identify the key metrics for each stage. Then prioritize metrics that reveal where the largest drop-off occurs, focusing on conversion rates, time-to-convert, and user segments. Finally, propose a data-driven approach to validate hypotheses and suggest potential experiments.
Pro tip: Emphasize that you would first check if the drop-off is uniform across all user segments or concentrated in specific cohorts (e.g., by device, geography, or acquisition channel), as this often reveals the root cause faster than aggregate metrics.
Break down the Premium subscription journey into clear stages from initial awareness to paid subscription, ensuring each stage has a measurable event.
For each stage, define the key metrics such as conversion rate, drop-off rate, and time spent, to quantify performance.
Focus on metrics that show the largest drop-off or have the highest potential impact on the overall conversion rate, using a funnel visualization.
Analyze metrics across different user segments (e.g., new vs. returning, device type, region) to pinpoint if the issue is widespread or isolated.
Based on the prioritized metrics, propose hypotheses for the drop-off and suggest A/B tests or further data analysis to confirm and address the issue.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.