Product Management Topics
Product leadership, vision articulation, roadmap development, and feature prioritization. Focuses on product strategy and business alignment.
Impact Beyond Direct Team
Describe how you've influenced product strategy or direction beyond your immediate team. Examples: you shaped the company's approach to a new market, established cross-product standards, elevated the bar for product execution company-wide, or influenced executive strategy. Quantify impact when possible: 'By establishing a shared prioritization framework, the org went from 40 initiatives to 12 strategic ones, increasing focus.' Discuss how you balance your team's needs with company-wide contributions.
Product and Business Impact
Assesses understanding of how technical decisions affect product experience and business metrics. Topics include marketplace dynamics, user needs and behavior, conversion and retention considerations, prioritizing work by impact, experiment and metric design, and connecting engineering trade offs to measurable product outcomes. Candidates should demonstrate curiosity about business drivers and the ability to incorporate product and metric thinking into technical planning.
Prioritization and Stakeholder Alignment
Covers frameworks and practices for prioritizing work, aligning stakeholders, and allocating limited resources across features projects and operational needs. Topics include impact versus effort and weighted scoring models, RICE and similar frameworks, sequencing dependent work, handling competing or conflicting priorities, negotiating trade offs with business and engineering partners, creating governance and escalation paths, communicating deprioritization decisions, and measuring outcomes to validate prioritization. Senior assessments include strategic resource allocation across teams and portfolios and techniques for building cross functional consensus.
Technical Strategy and Roadmapping
Covers defining, communicating, and operationalizing multi quarter to multi year technical and engineering strategy that aligns engineering investments with product and business objectives. Candidates should be able to describe planning horizons, trade offs between near term delivery and long term investment, and how strategic direction maps to architecture and platform decisions. Topic coverage includes migration and modernization planning, assessing current state and technical debt, sequencing initiatives and milestones, prioritization frameworks and cost of delay thinking, capacity and resource planning including hiring and team structure, vendor evaluation and integration, compliance and data considerations, governance and operating model, and execution planning with timelines and review cadences. It also includes balancing feature delivery, reliability, platform evolution, developer experience, and maintenance; making the business case for infrastructure and platform investments; defining success metrics and objectives and key results and measuring outcomes; risk identification, mitigation and contingency planning; and communicating roadmaps and trade offs to engineers, product leaders, business stakeholders, and executives. Domain specific concerns such as cloud adoption, business intelligence roadmaps, and marketing technology integration are included as examples of how technical strategy varies by context.
Metrics and Post Launch Learning
Covers defining success metrics and key performance indicators before launch, instrumenting systems to capture those metrics, tracking performance, and conducting structured post launch reviews or post mortems to extract lessons and inform iteration. Candidates should demonstrate how they choose measurable goals, avoid common metric pitfalls, and translate insights into product and engineering improvements.
Decision Making and Prioritization
Focuses on frameworks and practices for making decisions and setting priorities when information is incomplete and timelines are constrained. Candidates should be able to discuss structured prioritization techniques, trade off and risk assessment, expected value and cost benefit thinking, selection of relevant metrics, hypothesis driven experiments and split testing, and how to communicate and defend prioritization decisions under time pressure.