Customer and User Obsession Questions

Demonstrating a deep commitment to understanding and advocating for customers and end users. Candidates should show how they prioritize user needs in decision making, even when it conflicts with other priorities, and provide concrete examples of advocating for users internally. Topics include using qualitative and quantitative research to surface user pain points, validating assumptions with user evidence, designing or improving experiences to solve real problems, maintaining ongoing connection to users through feedback loops, and influencing stakeholders to keep the organization user focused. Examples may range from entry level empathy and direct customer learning to strategic changes driven by user insight.

EasyTechnical

91 practiced

What chart types and visual encodings are most effective to show a conversion funnel (e.g., install -> onboarding -> first purchase) in a mobile app dashboard? Explain why you would choose each, how to show absolute counts vs percentage drop-off, and how interactive filters (segment, device, acquisition channel) help interpretation.

MediumTechnical

147 practiced

Explain different definitions and formulas for churn applicable to: monthly active users (MAU churn), subscription churn (SaaS), and buyer churn for e-commerce. For each, describe advantages/disadvantages, how to handle reactivated users, and how to account for seasonality in churn measurement.

MediumTechnical

70 practiced

Management sets a target to increase Weekly Active Users (WAU) by 20% and product proposes three feature ideas. Describe a data-driven process to estimate each feature's expected impact, the metrics and short-term signals you'd monitor, how you'd design A/B tests or pilots, and how you'd recommend prioritization given limited engineering resources.

HardTechnical

73 practiced

Design an analysis that identifies 'power users' using event and purchase data, quantify their contribution to revenue and engagement, and provide both a rule-based threshold solution (e.g., top 5% by activity or spend) and an ML clustering alternative. Provide example SQL for the rule-based approach and a Python snippet that computes cumulative revenue contribution and visualizes the Pareto distribution.

HardTechnical

73 practiced

You must improve activation rate by 15% for a mobile onboarding flow. Given baseline: 100k new users/month, activation 20% (20k activated). Propose hypotheses for redesign, experiments to validate each (variants, sample sizes), primary and guardrail metrics, segmentation strategy, and ROI calculations that translate a 15% relative uplift to revenue impact. Also explain rollout and rollback criteria.

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