Measuring the impact of new features is essential for understanding their effectiveness in user engagement. Vitaly Friedman introduces the TARS framework, which focuses on tracking metrics across four key phases: Target Audience, Adoption, Retention, and Satisfaction. By analyzing how users interact with a feature, teams can pinpoint where they drop off and gauge the feature's success. The framework encourages looking beyond traditional metrics like click-through rates, emphasizing meaningful engagement instead. The first metric, Target Audience, measures the percentage of users facing a specific problem that the new feature aims to solve. This is often underestimated; for example, a feature used by 5% of users may actually have a much larger target audience. Next, Adoption rates assess how many of those users engage with the feature successfully. High adoption rates for core features (over 60%) indicate a significant problem being addressed, while lower rates (below 20%) suggest that users might rely on simpler alternatives. Retention tracks whether users continue to use the feature over time. A retention rate above 50% signals strong utility, while lower rates might indicate usability issues. Finally, Satisfaction is gauged using the Customer Effort Score (CES), which asks users about their experience after repeated use. This metric helps identify any hidden issues that may not be apparent from adoption or retention alone. By calculating an S÷T score—that is, the percentage of satisfied users compared to the target audience—teams can visualize the performance of each feature in a 2x2 matrix, revealing which features are underperforming or exceeding expectations. This structured approach enables teams to make informed decisions about feature development and adjustments.