Pretty open-ended and I wasn't sure how narrow to go.
Start by clarifying the product or funnel and the specific conversion event, then outline a data-driven method to compute conversion rates, including data sources, instrumentation, and analysis. Emphasize how you would validate the data, segment results, and use the insights to drive improvements.
Pro tip: Demonstrate that you think beyond the raw number by discussing how you would handle edge cases like multi-touch attribution, time windows, and statistical significance to avoid misleading conclusions.
Clarify what constitutes a conversion (e.g., sign-up, purchase) and map out the sequential steps users take. Ensure alignment with business goals and stakeholders.
Determine where the data comes from (e.g., logs, analytics tools, databases) and how events are tracked. Discuss the importance of consistent event naming and data quality.
Compute conversion rate as (number of conversions / number of opportunities) * 100 for each stage. Explain how to handle time windows, unique users, and attribution.
Check for data anomalies, missing events, or bot traffic. Segment by dimensions like device, geography, or user cohort to uncover actionable insights.
Interpret trends, compare against benchmarks, and identify drop-off points. Propose experiments (e.g., A/B tests) to improve conversion rates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.