Leading vs lagging indicators

Leading indicators predict future product performance by measuring current user behaviors that typically result in desired outcomes. These early warning signals, like feature adoption rates or user engagement patterns, help teams proactively address issues before they impact business results. They act as forward-looking gauges that enable teams to make timely adjustments to their product strategy.

Lagging indicators measure the final results of past actions, showing whether previous product decisions were effective. These metrics, such as monthly recurring revenue or customer lifetime value, provide concrete evidence of success or failure but offer limited guidance for future actions. While essential for validating strategy, they're less helpful for day-to-day decision making.^[1]

A balanced analytics strategy combines both types of indicators to create a complete picture of product health. Leading indicators guide immediate actions and help teams stay ahead of problems, while lagging indicators validate whether those actions achieved the desired results. This dual approach enables teams to both predict and verify product success.