← Anthropic Interview Insights
I started with metrics and probably spent too long on the obvious stuff like sign-up rate and CAC before getting to the more interesting ones like activation rate and 30-day retention.
Start by defining clear success metrics that align with the campaign's goal, such as CAC, LTV, and conversion rate. Then design a controlled experiment (e.g., A/B test) to measure the campaign's impact on these metrics, ensuring statistical power and proper randomization. Finally, analyze results to make a data-driven decision on whether to continue or shut down the campaign.
Pro tip: Consider the long-term impact and potential network effects, especially in a company like Anthropic where user acquisition might have compounding benefits. Also, be mindful of novelty effects and ensure your experiment runs long enough to capture steady-state behavior.
Identify primary and secondary metrics that reflect the campaign's objectives, such as Customer Acquisition Cost (CAC), Lifetime Value (LTV), conversion rate, and ROI. Ensure they are measurable and aligned with business goals.
Set up a randomized controlled trial (A/B test) with a control group (no campaign) and treatment group (with campaign). Determine sample size, duration, and randomization unit to achieve statistical power.
Run the experiment, ensuring data quality and monitoring for any anomalies or external factors that could bias results. Collect data on the defined metrics.
Perform statistical analysis to compare metrics between groups, calculate confidence intervals, and determine if differences are significant. Consider segment analysis for deeper insights.
Based on the analysis, decide whether to continue, modify, or shut down the campaign. Consider both statistical significance and practical significance (e.g., impact on overall business).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.