Pipeline stages should mean the same thing to Marketing, Sales, Finance, and leadership. Consider whether stage definitions are documented, enforced, and consistently used in reviews and forecasts.

Managers should be able to clearly explain why performance changed, not just that it did. Think about whether explanations rely on metrics and drivers, or anecdotes and gut feel.

Segmentation should be shared and consistent across the entire revenue organization. Ask whether “enterprise,” “mid-market,” priority accounts, or ICPs are defined identically everywhere.

Short-term forecasts should be reliable enough to guide hiring, spend, and board-level decisions. Consider how often forecasts change materially in the final weeks of the quarter.

Expansion should be guided by data, not intuition or reactive account coverage. Think about whether you can point to specific segments or account traits tied to expansion outcomes.

Marketing performance should be measurable, timely, and tied directly to revenue impact. Consider how long it takes today to answer, “What’s actually working, and why?”

Revenue metrics should reconcile cleanly across CRM, finance, and analytics systems. Ask whether different teams ever present different numbers for the same metric.

AI should help anticipate risk and opportunity, not merely summarize past performance. Think about whether AI is informing forward-looking decisions like forecast risk, expansion, or prioritization.

Coaching should focus on performance drivers and decision quality, not just effort or volume. Consider how often 1:1s revolve around insights versus calls made, emails sent, or meetings booked.

Leadership confidence in revenue data is the ultimate test of trust. Ask whether executives defend the numbers, or caveat them, in board and investor discussions.