Connect metrics to business impact

Metrics only matter when they connect directly to business outcomes. This connection manifests through cause-and-effect relationships that teams can test and verify. For instance, higher user retention might directly impact recurring revenue, while increased feature engagement could reduce churn. However, these links are often hard to find, especially for early-stage teams without much data or analytics support. What matters most is building that understanding over time. Keep asking: how do our users create value for the business? Then use each metric to help answer that.

Creating relevance means starting with business goals and working backward. Begin with outcomes like revenue growth, customer acquisition cost, or profitability. Then figure out which user behaviors are most likely to influence those outcomes. Design metrics around those behaviors and not just activity for the sake of tracking. One way to do this is by cohorting users. You can group them by demographics or behavior, then compare business metrics across those groups. For example, look at average revenue for users who activated versus those who didn’t, or lifetime value for users who used a key feature versus those who didn’t. This helps you spot which behaviors actually drive value.

Most companies benefit from establishing a hierarchy of metrics with clear relationships between them. Leading metrics like engagement feed into business metrics like retention, which ultimately support financial metrics like revenue and profitability. This hierarchy ensures everyone understands how their work connects to business success and prevents teams from optimizing for disconnected metrics.