Free tool

Pipeline Velocity Calculator

How much revenue your pipeline generates per day, and which of the four inputs is actually worth improving. Most teams pull the wrong lever.

One set of numbers, plus a breakdown of which input is worth improving first.

Your numbers

Pull these from the last two closed quarters. Averages from a single month move too much to plan against.

Count of open deals past qualification right now, whole deals only
First-year contract value per deal, not lifetime value
Closed won divided by closed won plus closed lost, over the last two quarters
25%1% to 100%
Calendar days from qualified to signed, including the dead time between stages
days

What moves the needle most

Each row improves one input of the numbers above by 10% and leaves the other three alone. Ranked by revenue added over one quarter.

Cut sales cycle 10%+$73,750
72 to 65 days · 10.8% more revenue per day · +$808 a day
Add 10% more qualified opportunities+$68,483
120 to 132 open deals · 10% more revenue per day · +$750 a day
Raise average deal value 10%+$68,483
$18,000 to $19,800 per deal · 10% more revenue per day · +$750 a day
Raise win rate 10% relative+$68,483
25% to 27.5% win rate · 10% more revenue per day · +$750 a day
$7,500
Revenue per day
Qualified opportunities x deal value x win rate, divided by cycle days
Revenue per calendar month
$228,300
Revenue per quarter
$684,825
Revenue per year
$2,737,500
Expected wins per sales cycle
Whole deals this pipeline should produce over one 72 day cycle
30
Weighted value of open pipeline
Open opportunities x deal value x win rate, before dividing by time
$540,000
Work on cycle length first
Cutting the cycle from 72 days to 65 adds $73,750 a quarter, more than any other 10% move. Cycle length sits in the denominator, so every day you remove compounds across every deal in the pipeline. Attack the dead time between stages, not the selling time: start by pulling the ten longest stage transitions from your last twenty closed deals.

How this works

The formula

Pipeline velocity equals the number of qualified opportunities, multiplied by average deal value, multiplied by win rate, divided by average sales cycle length in days. The result is revenue per day. Multiply by 30.4 for a month, 91.3 for a quarter. It is the only common sales metric with time in it, which is why it catches problems that pipeline value alone hides: a pipeline that doubled while the cycle also doubled has produced exactly nothing.

Why cycle length is usually the strongest lever

Three of the four inputs sit in the numerator, so a 10% improvement gives you 10% more velocity. Cycle length sits in the denominator: cutting it 10% divides by 0.9, which is an 11.1% gain rather than 10%. The ranking above works in whole days, so the exact figure lands near 11% depending on your cycle. The gap looks small on paper and is large in practice, because shortening the cycle costs nothing. More opportunities means more spend or more headcount. Bigger deals means moving upmarket. Faster cycles means removing dead time you are already paying for.

Where the dead time actually is

Measure the gap between stage changes, not the selling time. In most B2B funnels the cycle is mostly waiting: three days to send the follow-up, nine days chasing a scheduling reply, two weeks in a security review nobody chased. Reps rarely lose deals during meetings. They lose weeks between them. Pull the ten longest stage transitions from your last twenty closed deals and you will usually find a third of the cycle sitting in two of them.

How to use the before and after mode honestly

Change two inputs at most. Plans that improve all four by 10% are not plans, they are wishes, and they make it impossible to tell afterwards which change worked. Pick the lever this tool ranks first, commit to one number, and measure velocity again in a quarter. If it did not move, the intervention failed, and you will know that instead of guessing.

Velocity is a measurement problem before it is a sales problem

Dalil timestamps every stage change, message, and reply across email, LinkedIn, and WhatsApp, so your cycle length and win rate come from what happened rather than from what you typed into a calculator. Then its workflows chase the gaps that create the dead time.