Sum the days between start date and close date for every deal that closed in the period, then divide by the count of those deals.
Average sales cycle length = total days to close / number of closed deals
Everything difficult about the metric lives in two inputs: which start date counts, and which deals qualify for the average. Both can be wrong while the formula still returns a confident-looking number, which is how weak cycle reporting survives for years.
Pick a start date and hold it
Opportunity creation date is the standard choice for a sales cycle, because it marks the point where a seller owns the process. Lead creation date measures the marketing span as well and yields a much larger figure.
Either definition works. Switching between them does not. A team that computes from opportunity creation and then compares itself to a benchmark built from first touch will conclude it sells fast when it sells at par. ORM's position on data quality applies directly here. Consistency matters more than cleanliness, because a consistent definition still supports accurate prediction.
Decide what happens to open and lost deals
Report won-deal cycle time as the headline and put lost-deal cycle time beside it. The deals that quietly distort the calculation are the ones nobody ever closed. An opportunity that has been open for a year is excluded from the average by definition, so a pipeline carrying many of them makes your cycle look shorter than it is. ORM applies a twelve-month rule for most customers, treating an opportunity with no meaningful change for that long as something other than active pipeline.
Report the median next to the mean
Cycle-length distributions run long on the right. ORM's close-timing curves span 1 to 80 weeks, with most of the expectation landing before week 12 and very few groups carrying meaningful expectation past 52 weeks. A small number of slow deals pulls the mean well above what a typical deal does.
When the mean and median sit far apart, the average is describing your tail rather than your motion.
Where the number gets used
Cycle length is the denominator in velocity math and the check that tells you whether pipeline created this month can close this quarter. A deal created 40 days before quarter end inside a motion that averages 95 days is not in-quarter pipeline, whatever its close date claims. Running that check improves pipeline coverage quality faster than raising a coverage target, and it feeds sales forecasting that reflects timing instead of optimism. The sales velocity framework shows how one cycle number compounds through every other metric.
Frequently Asked Questions
What is the sales cycle length formula?
Add up the days between start date and close date for every deal that closed in the period, then divide by the number of those deals. Both dates already sit in the CRM, so the whole calculation is date arithmetic on existing fields.
Which start date should you use?
Opportunity creation date for a sales cycle, because that is when a rep took ownership of a buying process. Lead creation date measures a wider span and produces a much longer number. Both are defensible. Comparing one against a benchmark built on the other is the common mistake.
Should lost deals be included in the average?
Measure them, then report them separately. Won deals and lost deals close on different clocks, so blending them produces a figure that describes neither and swings with loss volume rather than with sales performance.
How often should the number be recalculated?
Every quarter, on a rolling trailing window. Cycle length moves with market conditions such as pricing pressure and buyer indecision, so a figure computed once a year describes a market that has already changed.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like how do you calculate sales cycle length? into prescriptive action for your team.
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