Data Analysis and Performance Measurement Questions

Covers the end to end use of quantitative analysis to track, interpret, and act on business performance across accounts and campaigns. Candidates should be fluent in account level metrics such as customer retention rate, net revenue retention, annual recurring revenue, net promoter score, customer health scores, and customer lifetime value, as well as marketing and acquisition metrics such as click through rate, conversion rate, customer acquisition cost, return on advertising spend, and attribution model outcomes. Expect discussion of data sources and instrumentation, cohort and funnel analysis, segmentation, anomaly detection, attribution approaches, and calculating return on investment for initiatives. Candidates should be able to describe how they used analytics tools and queries, dashboards, and experiments or A B tests to identify at risk accounts or underperforming campaigns, prioritize actions, optimize strategies, and measure the impact of initiatives. Strong answers explain concrete metrics chosen, analysis methods, tools used, how results informed decisions, and how success was measured over time.