Skip to content
B2B Prestige AwardsPremium B2B recognition across the United States and Asia

Guide · Sales

Pipeline Coverage Ratio: How to Calculate and Use It

· By the B2B Prestige Awards editorial team

Pipeline coverage ratio is the value of your open sales pipeline divided by your sales target for the same period. If your quarterly quota is $500,000 and you have $1,500,000 of open deals, your coverage is 3x. A higher ratio gives you more room for deals that slip or are lost.

Many sales teams use 3x as a default goal. This guide shows the formula, why 3x is only a rule of thumb, and how your win rate and sales cycle change the number you should aim for. The math is simple and needs only a calculator.

The pipeline coverage ratio formula

The basic formula has two inputs:

Pipeline coverage ratio = total open pipeline value ÷ sales target

Use the same time period for both. If the target is for one quarter, count only the deals that you expect to close in that quarter. Here are three examples with a $1,000,000 target:

Open pipelineCoverage ratioWhat it means
$1,000,0001xYou must win every dollar to hit target
$2,000,0002xYou can lose half of the pipeline
$3,000,0003xYou can lose two thirds of the pipeline

Clari, a revenue software vendor, makes the same point with a $1 million target. At 1x, a team would need to close every dollar to make quota.

Sources: Clari, "Sales Pipeline Coverage Ratio - Everything You Need To Know" (published December 2019, updated November 2023)

Where the 3x rule comes from

Ask a sales team how much pipeline it needs, and the usual answer is three times the target. The rule is old and rarely backed by data. Clari quotes software CEO Dave Kellogg, who joked that 2x seems tight, 4x seems rich, and so 3x became the answer.

The rule is a fair starting point. It is not a law. Clari says its own data showed that about 3.2x coverage at the start of a quarter worked well for deals the sales team had partly vetted. Clari also warns that this figure may not fit companies or products unlike its own.

Sources: Clari, "Sales Pipeline Coverage Ratio - Everything You Need To Know" (published December 2019, updated November 2023)

How win rate changes the target

The 3x rule only works if you win about one deal in three. Win rate is the share of pipeline value that turns into closed revenue. The link is plain math:

Needed coverage = 1 ÷ win rate

Win rateCoverage needed
50%2x
33%3x
25%4x
20%5x
10%10x

Salesforce made this point in an April 2023 article. A rep who wins 10 percent of pipeline revenue needs 10x coverage. A rep who wins 50 percent needs only 2x. Use revenue win rate, meaning dollars won divided by dollars in the pipeline. Do not use the count of deals, because large and small deals close at different rates.

Sources: Salesforce, "Why 3x Pipeline Coverage Is a Terrible Strategy" by Jason Jordan (April 25, 2023)

How sales cycle length changes it

Win rate is only half the story. Sales cycle length matters too. A team with a one-year cycle fills its pipeline once and works it all year. A team with a two-week cycle refills its pipeline many times in a year, so it needs less pipeline at any one moment.

Salesforce gives this formula for one rep:

Pipeline needed = annual quota ÷ win rate ÷ (365 ÷ sales cycle in days)

Here is a worked example. A rep has a $100,000 annual quota, a 25 percent win rate and a 60-day sales cycle. The pipeline turns over about 6.1 times a year (365 ÷ 60). So the rep needs about $65,750 in the pipeline at one time ($100,000 ÷ 0.25 ÷ 6.08). That is less than the quota, and it still works, because the pipeline refills every two months.

Notice that the answer changes with the inputs. Short cycles and high win rates need less coverage. Long cycles and low win rates need more.

Sources: Salesforce, "Why 3x Pipeline Coverage Is a Terrible Strategy" by Jason Jordan (April 25, 2023). The worked figures are our own arithmetic on the formula shown there.

Pipeline coverage versus forecast coverage

These two terms are easy to mix up. Pipeline coverage counts every open opportunity, from new leads to deals near close. Forecast coverage is narrower. It applies past win rates to each deal to get a weighted forecast.

Clari gives an example. A team has a $1 million quarterly target and 3x pipeline coverage. After applying past win rates, the forecast is $700,000. Forecast coverage is then 70 percent of target, which flags a gap even though the raw pipeline looks healthy.

Sources: Clari, "Sales Pipeline Coverage Ratio - Everything You Need To Know" (published December 2019, updated November 2023)

How to use the ratio each week

  1. Pick one period. Match the pipeline and the target to the same quarter or month.
  2. Count only real deals. Remove stale opportunities with no recent activity, or the ratio will look better than it is.
  3. Find your own win rate. Use the last four to eight quarters of closed revenue, by rep or by segment if you can.
  4. Set the target. Use 1 ÷ win rate as a floor, then adjust for sales cycle length.
  5. Check early. A low ratio at the start of a period leaves time to add pipeline. A low ratio in the last weeks leaves little to do.

Salesforce suggests a better coaching talk than "your pipeline is not three times your quota." Look at the data instead. The team may need more deals in the pipeline, a higher win rate, or a faster cycle. Each of those calls for a different fix.

Keep in mind that coverage does not predict revenue by itself. It is a health check. Pair it with deal stage, deal age and forecast coverage.

Sources: Salesforce, "Why 3x Pipeline Coverage Is a Terrible Strategy" by Jason Jordan (April 25, 2023); Clari, "Sales Pipeline Coverage Ratio - Everything You Need To Know" (published December 2019, updated November 2023). The weekly steps are our own practical summary.

Sources

  1. Salesforce, "Why 3x Pipeline Coverage Is a Terrible Strategy," Jason Jordan, April 25, 2023. salesforce.com
  2. Clari, "Sales Pipeline Coverage Ratio - Everything You Need To Know," Michael Lowe, published December 10, 2019, updated November 27, 2023. clari.com (archived copy)