Vanity metrics like total revenue can be misleading. A startup might acquire many low-priced, low-usage customers without solving a core problem. Deep, consistent user engagement statistics are a much stronger indicator of genuine, 'found' demand than top-line numbers alone.

Many founders mistakenly define Product-Market Fit by revenue (e.g., "$1M ARR"). The correct measure is the ability to predictably create customer value. This is best quantified by a leading indicator for long-term retention, not sales figures, as revenue can be achieved without true market fit.

Elias Torres argues that revenue is not the ultimate validator of a product. He has seen founders with $50 million in revenue who are "delusional" that their product truly works or is sticky. This time, he is prioritizing user obsession and product stickiness over early monetization to avoid this trap.

Executives and investors care about lagging business indicators like ARR and churn, not leading product indicators like user engagement. It is the PM's job to connect the dots and clearly articulate how improvements in product metrics will directly result in moving the high-level business needles.

To bridge the communication gap with leadership, reframe common product metrics into financial terms. Instead of reporting daily active users (DAU), calculate and present average revenue per daily active user (ARPA-DAU). Similarly, frame quality initiatives not as ticket reduction but as operating expense (OPEX) savings.

During a product launch, top-line revenue can be a lagging indicator. The most critical real-time metric is sessions. If site traffic is significantly below forecast, it is the earliest and most urgent sign of a problem, allowing for quicker intervention.

Revenue is a lagging indicator and is too slow for validating major strategic shifts. To get an early signal, establish checkpoints using leading indicators. For a decision aimed at acquiring more customers, track metrics like sales team win rates on a monthly basis to see if the hypothesis is proving correct before revenue numbers reflect the change.

Don't jump directly to optimizing for high-level business outcomes like retention. Instead, sequence your North Star metric. First, focus the team on driving foundational user engagement. Only after establishing that behavior should you shift the primary metric to a direct business impact like revenue or retention.

Focus on what customers value (e.g., delivery speed, order accuracy) rather than internal business metrics like ARR or user growth. This approach naturally leads to a better product roadmap and a more defensible business by solving real user problems.