Pipeline velocity

Pipeline velocity is the rate at which revenue flows through your sales pipeline, expressed as currency earned per day. It multiplies the number of qualified opportunities by the average deal value and the win rate, then divides by the average sales cycle length. The numerator is the expected revenue sitting in the pipeline. The divisor is how long it takes to realise that revenue.

The value of pipeline velocity is that it folds four separate sales metrics into a single number. A team can hold a large pipeline yet move slowly if win rates are weak or cycles are long. A smaller team can move faster if it wins more deals and closes them quickly. Velocity captures that compounding relationship in one figure you can track month over month.

Because it is a rate, pipeline velocity is well suited to forecasting. If velocity is ten thousand pounds per day and you need to close one million pounds this quarter, you can see at a glance whether the current engine clears the bar or whether one of the four levers has to improve.

Multiply the number of qualified opportunities by the average deal value and by the win rate, then divide by the average sales cycle length in days. The output is revenue per day.

Worked example: 80 qualified opportunities, an average deal value of 30,000 pounds, a 25 percent win rate, and a 50-day cycle. Velocity = (80 x 30,000 x 0.25) / 50 = 12,000 pounds per day. Over a 90-day quarter that projects to 1,080,000 pounds in closed revenue at current performance.

1. 1

   Count qualified opportunities

   Take the number of opportunities that have passed qualification and sit in an active stage. Exclude anything unqualified or stalled past your dead-deal threshold, because they distort the rate.

2. 2

   Find the average deal value

   Use the average won deal value for the same segment and motion. Mixing SMB and enterprise deals into one average produces a velocity that describes neither.

3. 3

   Calculate the win rate

   Divide deals won by deals that reached a decision in the period, then express it as a decimal. A 25 percent win rate enters the formula as 0.25.

4. 4

   Measure the sales cycle length

   Average the days from opportunity creation to close across recently closed deals. This is the divisor, so a shorter cycle raises velocity directly.

Each input can be measured by team, by rep, by segment, or by lead source. Calculating velocity at each level shows where the engine runs fast and where it drags. A blended company-wide figure hides more than it reveals.

Pipeline velocity decomposes cleanly into a metric tree. The four formula inputs form the first level, and each one breaks down into the operational drivers that real teams control. The tree turns a composite number into a set of levers with names against them.

Composite velocity has no single industry benchmark because it depends on your sales motion. The practical approach is to benchmark each lever against its own motion, then derive a target velocity from the formula. The ranges below give realistic input bands for three common motions.

Because the four levers multiply, a 20 percent gain in any one of them lifts velocity by roughly 20 percent. The discipline is to find the weakest lever and fix that one first, rather than improving the lever that happens to be most visible.

1. 1

   Optimising one lever in isolation

   The levers interact. More pipeline from looser qualification drags win rate down and often lengthens cycles. Watch all four together so you can see the trade-offs.

2. 2

   Blending motions into one figure

   A single velocity across SMB and enterprise is meaningless because the inputs differ so widely. Calculate velocity separately for each motion and segment.

3. 3

   Ranking individual reps on raw velocity

   Reps with different territories and pipeline mixes will show different velocities for reasons outside their control. Compare reps only within the same segment and motion.

4. 4

   Forgetting that velocity is a rate

   Twelve thousand pounds per day only means something over a defined window. Keep the timeframe consistent when you compare one period with another.