Product Management Topics
Product leadership, vision articulation, roadmap development, and feature prioritization. Focuses on product strategy and business alignment.
Product Metrics and Strategy
Emphasizes connecting metric design to product strategy and business outcomes. Covers metric taxonomy such as north star metric, outcome metrics, driver metrics, and leading versus lagging indicators, governance and ownership of metrics, and preventing metric gaming. Includes thinking about long term versus short term trade offs, how to influence product direction through metric design, attribution challenges, prioritizing instrumentation and data science investment, and communicating metric driven insights to stakeholders. Appropriate for senior level discussions where metrics inform strategy, roadmap decisions, and organizational alignment.
Product Metrics and Key Performance Indicators
Covers designing, implementing, and governing metric frameworks for products. Topics include defining a north star metric that aligns the organization, identifying supporting and diagnostic metrics that drive and explain the north star, and understanding metric types such as engagement, retention, monetization, and quality. Candidates should be able to discuss metric hierarchies, instrumentation and data pipeline considerations, segmentation and cohort analysis, and the use of metrics for experimentation and decision making. Governance topics include ownership, alerting and anomaly detection, preventing metric manipulation, establishing thresholds and statistical rigor, retiring obsolete metrics, and balancing business and product analytics needs across stakeholders.
Metric Selection & Product Instrumentation
Techniques for turning vague business questions into measurable, actionable product metrics. Includes identifying leading vs. lagging indicators, upstream vs. downstream metrics, aligning metrics with company strategy, balancing multiple stakeholders (user satisfaction, business growth, content value), and recognizing when metrics can be misleading or require multiple signals to capture impact.
Core Product Metrics and KPIs
Deep understanding of key product metrics (DAU, MAU, retention, churn rate, engagement, NPS, ARPU, conversion funnels) and how they relate to business objectives. Ability to define appropriate success metrics for different product initiatives and tie them to business goals. Understanding of leading vs. lagging indicators.