Experimentation programs are vital for enabling data-driven decision-making within product development. However, evaluating their overarching success remains a significant challenge. Current metrics, such as conversion rates, primarily focus on individual experiments, leaving a gap in assessing broader program efficiency and impact. This paper addresses this gap by presenting a structured overview and analysis of 18 program-level metrics, categorized into six domains: Volume, Outcome-Based, Quality, Engagement, Process Efficiency and Strategic Alignment. Metrics such as experimentation throughput, time-to-decision and experimentation coverage are examined for their implications on operational efficiency, cultural adoption, and strategic alignment. Based on interviews with 48 experimentation practitioners, this work provides a description of these metrics and discusses their benefits and challenges. The results offer actionable insights for advancing experimentation practices and aligning them with organizational goals.