How to Evaluate Sales Performance
A framework for measuring what matters across the sales org
When someone asks "how is the sales team doing?" the temptation is to answer with a single number: . But attainment alone tells you the outcome without explaining why. A team at 85% attainment with a healthy pipeline looks very different from a team at 85% that got there through heroic last-minute deals.
Evaluating sales performance properly requires looking at three layers: output metrics, process metrics, and efficiency metrics. Together they tell a complete story.
Layer 1: Output Metrics
Start with what the team produced. tells you whether reps hit their number. tells you how often they close when given a shot. tells you the value of what they close. And tells you the raw output per person.
These metrics are lagging indicators. By the time they move, the quarter is already over. They are essential for measuring results but useless for changing them in real time.
Layer 2: Process Metrics
Process metrics tell you whether the machine is working. Are there enough deals in the funnel? answers that. Are deals moving at a healthy pace? and tell you. Is the team generating enough at-bats? and reveal whether reps are doing the work.
The is particularly powerful because it isolates sales execution from lead quality. If SQL-to-close is dropping while MQL-to-SQL is steady, the problem is in the sales process, not the funnel.
Layer 3: Efficiency and Predictability
The third layer asks: are we getting better? Is the sales team improving, or are we just adding headcount? tells you how quickly new hires become productive. The tells you whether quotas are set sustainably. tells you whether the team can predict its own outcomes.
Qualification matters too. Teams using structured frameworks like tend to have higher win rates and shorter cycles because they disqualify bad deals earlier.
Putting It Together
No single metric evaluates sales performance. The right approach is a dashboard that layers output on top of process on top of efficiency. When output dips, process metrics explain why. When process metrics are healthy but output lags, look at efficiency and qualification. The RevOps team owns this system -- building the data model, the dashboards, and the cadence of review that turns metrics into action.