Feedback and Continuous Improvement Questions

This topic assesses a candidate's approach to receiving and acting on feedback, learning from mistakes, and driving iterative improvements. Interviewers will look for examples of critical feedback received from managers peers or code reviews and how the candidate responded without defensiveness. Candidates should demonstrate a growth mindset by describing concrete changes they implemented following feedback and the measurable results of those changes. The scope also includes handling correction during live challenges incorporating revision requests quickly and managing disagreements or design conflicts while maintaining professional relationships and advocating for sound decisions. Emphasis should be placed on resilience adaptability communication and a commitment to ongoing personal and team improvement.

MediumTechnical

0 practiced

Design an operational closed-loop system for collecting, triaging, and routing product feedback from multiple sources (in-app, NPS, support tickets, social). Include components for ingestion, deduplication, prioritization rules, SLAs for response, and metrics to measure impact and responsiveness.

HardTechnical

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Your product's NPS is improving for long-term power users but falling sharply for new users. Provide a data-driven plan to investigate root causes (funnel, onboarding, UX), prioritize remediation efforts, design experiments to validate hypotheses, and update the roadmap to address the divergent segment needs without regressing power-user satisfaction.

EasyBehavioral

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Tell me about a time you changed a product feature after collecting user feedback that contradicted your assumptions. Describe what you learned, the iteration you implemented, how you tested it (if applicable), and the concrete metrics that improved as a result.

MediumTechnical

0 practiced

Outline a blameless postmortem process to run after a feature launch fails to meet SLA expectations. Include timeline, required artifacts (logs, dashboards, timelines), roles (PM, Eng, Ops, Support), and how you'd convert findings into concrete improvement actions and verification steps.

MediumTechnical

0 practiced

You're launching a new recommendation feature. Describe the event taxonomy and instrumentation plan you would propose for analytics: which events and properties to capture (exposure, impression, click, conversion), naming conventions to use, and how you'd structure funnels and cohorts to drive continuous improvement.

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