---
title: "Sales Pipeline Metrics: 12 to Track, With a Calculator"
description: "Track 12 sales pipeline metrics computed on one worked quarter, with formulas, what skews each one, and a free sales velocity calculator."
canonical: "https://derrick-app.com/b2b-marketing/sales-pipeline-metrics"
category: "B2B Marketing"
updated: "2026-10-02"
---

# Sales Pipeline Metrics: 12 to Track, One Worked Quarter, and a Velocity Calculator

> Sales pipeline metrics describe the deals a sales team is working, from the moment a qualified opportunity is created. The 12 worth tracking fall into three families: volume (opportunities created, pipeline value created), conversion (win rate, stage conversion rate, sales cycle length, time in stage, loss reasons) and open pipeline (pipeline coverage, weighted pipeline, sales velocity, slippage rate, stalled deals). In an illustrative quarter, 40 open deals at 12,000 with a 25% win rate and a 60-day cycle give a velocity of 2,000 per day and a coverage of 1.9x, against the 4x that a 25% win rate requires.

*Canonical: https://derrick-app.com/b2b-marketing/sales-pipeline-metrics* · *B2B Marketing*

---

## What sales pipeline metrics are, and the quarter we will use

**Sales pipeline metrics are the numbers that describe the deals a sales team is working: how many opportunities enter, how they convert, how long they take, and whether the open pipeline is big and healthy enough to reach the target.** They start where lead generation stops. Everything before a lead becomes a sales opportunity (leads generated, cost per lead, lead-to-opportunity rate) belongs to our guide on [lead generation KPIs](https://derrick-app.com/b2b-marketing/lead-generation-kpis). This page covers what happens after.

Most lists of sales pipeline metrics give each formula its own example, with its own numbers. That makes each metric easy to read and the whole impossible to see: you never watch coverage follow from the win rate, or velocity follow from four other numbers. So every metric below is computed on the same illustrative quarter. The numbers are round and fictional; what matters is how they connect.

**The worked quarter.** A B2B sales team works a 91-day quarter. During the quarter it creates 60 qualified opportunities, closes 48 deals (12 won, 36 lost, including 9 that ended without a decision), and wins an average of 12,000 per deal. Its average sales cycle, measured on won and lost deals, is 60 days. At the end of the quarter it holds 40 open opportunities, valued at the average won deal of 12,000, and next quarter's target is 250,000. Hold on to these numbers: the twelve metrics come out of them, and the [sales velocity calculator](#sales-velocity-calculator) in metric 10 lets you swap in your own.

The metrics are grouped in three families: **volume** (what enters the pipeline), **conversion** (what comes out, and how), and **open pipeline** (what is left to work, and whether it is enough).

## Volume metrics: what enters the sales pipeline

The handover from marketing sits just before this family: the lead-to-opportunity rate measures how many leads become opportunities, and it is the last of the [lead generation KPIs](https://derrick-app.com/b2b-marketing/lead-generation-kpis). From here on, the unit is the opportunity.

### 1. Opportunities created

**The number of new qualified opportunities opened in the period.** Formula: count of opportunities whose creation date falls in the period and that passed your qualification step. Worked quarter: **60**. It is the first number to watch each week, because every other metric is a fraction of it, a quarter or two later.

What makes it lie: opportunities created to log a call, then left open. If your CRM lets anyone open a deal without a qualification step, this count measures activity, not pipeline.

### 2. Pipeline value created

**The total amount of the opportunities created in the period.** Formula: sum of the amounts of opportunities created. Worked quarter: 60 opportunities at an average expected amount of 11,500, so **690,000**. Read it next to opportunities created: the same count with a falling value means the team is opening smaller deals.

What makes it lie: default amounts. A deal opened with the price list's standard figure, never updated after discovery, inflates the value created and every coverage number built on it.

## Conversion metrics: how deals come out of the pipeline

### 3. Win rate

**The share of closed opportunities that were won.** Formula: deals won ÷ deals closed (won plus lost) in the period. Worked quarter: 12 ÷ 48 = **25%**. It is the metric most other ones depend on, including the coverage you need (metric 8).

What makes it lie: leaving out the deals that ended in "no decision". Counting them as neither won nor lost turns the same quarter into 12 ÷ 39 = 31%, and every plan built on that rate will be short.

### 4. Stage conversion rate

**The share of opportunities that move from one stage to the next.** Formula: opportunities that reached stage N+1 ÷ opportunities that reached stage N, on the same cohort. Worked quarter: of the 60 opportunities created, 39 reached the demo stage, so **65%** from discovery to demo. It tells you where deals stop, which the win rate alone cannot. To find the leaking step across your whole funnel, our free [sales conversion rate calculator](https://derrick-app.com/free-tools/sales-conversion-rate-calculator) computes every stage at once, and the guide to [sales funnel management](https://derrick-app.com/b2b-marketing/sales-funnel-management) explains how to read it.

What makes it lie: deals that skip stages. If reps move a deal from discovery straight to proposal, the demo stage looks like it converts at 100% on fewer deals.

### 5. Sales cycle length

**The average number of days between the creation of an opportunity and its close.** Formula: sum of (close date minus creation date) ÷ number of closed deals. Worked quarter: **60 days**, on won and lost deals together. It sets the rhythm of everything else: the opportunities you create this quarter mostly close next quarter.

What makes it lie: measuring it on won deals only. Won deals often close faster than lost ones, which can drag on for weeks before they die, so a cycle measured on wins alone tends to look shorter than it is.

### 6. Time in stage

**How long deals stay in each stage before they move or die.** Formula: average days between entering a stage and leaving it. Worked quarter: deals spend an average of **18 days** in the proposal stage, against 9 in discovery. A stage where time grows quarter after quarter is where your cycle gets longer.

What makes it lie: stage dates that are never logged. If your CRM does not record when a deal enters each stage, this metric does not exist; the guide to [sales pipeline stages](https://derrick-app.com/b2b-marketing/sales-pipeline-stages) lists the fields each stage needs.

### 7. Loss reasons

**The distribution of the reasons why deals were lost.** Formula: count of lost deals per reason ÷ total lost deals. Worked quarter, on 36 losses: no decision 9 (25%), price 8, another supplier chosen 7, timing 6, poor fit 6. It turns a win rate into a list of things to fix.

What makes it lie: a free-text field. Reasons typed by hand cannot be counted; a short pick-list, filled at close, can.

## Open pipeline metrics: is what is left enough?

### 8. Pipeline coverage

**The value of the open qualified pipeline divided by the revenue target for the period.** Formula: open pipeline value ÷ target. Worked quarter: 40 open opportunities at 12,000 is 480,000, against a target of 250,000: about **1.9x**. Is that enough? With a 25% win rate, no: the coverage you need is 1 ÷ win rate, so 4x, or 1,000,000 of pipeline. The team is 520,000 short before the quarter starts. More on the ratio in our glossary entry on [pipeline coverage](https://derrick-app.com/glossary/pipeline-coverage).

What makes it lie: zombie deals. Every opportunity nobody has touched in months still counts in the numerator.

### 9. Weighted pipeline

**The open pipeline value, with each deal multiplied by the probability of its stage.** Formula: sum of (deal amount × stage probability). Worked quarter, with 10%, 25%, 50% and 75% for the four open stages: 15 deals in discovery (18,000), 12 in demo (36,000), 8 in proposal (48,000), 5 in negotiation (45,000), so **147,000**. It is a rough forecast; its quality depends on whether the stage probabilities come from your own history. See our glossary entry on the [weighted sales pipeline](https://derrick-app.com/glossary/weighted-sales-pipeline).

What makes it lie: probabilities copied from a template. A 50% probability at proposal stage is only true if half of your past proposals were won.

### 10. Sales velocity

**The revenue the pipeline produces per day at its current pace.** Formula: open qualified opportunities × average deal size × win rate ÷ sales cycle length in days. Worked quarter: 40 × 12,000 × 25% ÷ 60 = **2,000 per day**, about 182,000 per quarter, against a target of 250,000. The definition sits in our glossary entry on [sales velocity](https://derrick-app.com/glossary/sales-velocity), and the developed formula in the entry on the [sales pipeline velocity formula](https://derrick-app.com/glossary/sales-pipeline-velocity-formula). The calculator below is loaded with the worked quarter: change any of the four numbers, add your target, and it shows what each lever is worth and the coverage you need.

[Open the sales velocity calculator full page](https://derrick-app.com/free-tools/sales-velocity-calculator)

What makes it lie: the same things that distort its four inputs. Zombie deals inflate the opportunity count, default amounts inflate the deal size, and a cycle measured on wins only shortens the denominator.

### 11. Slippage rate

**The share of deals expected to close in the period whose close date was pushed to a later period.** Formula: deals with a close date moved out of the period ÷ deals that had a close date in the period at its start. Worked quarter: 20 deals were expected to close; 8 were pushed, so **40%**. A high slippage rate means the forecast is built on dates nobody believes.

What makes it lie: close dates that are moved quietly, one week at a time. Measure against the date recorded at the start of the period, not the current one.

### 12. Stalled deals and deal age

**The open deals with no activity for longer than a set threshold, and the average age of open deals.** Formula: open deals with no logged activity in N days ÷ open deals; average of (today minus creation date) on open deals. Worked quarter, with a 30-day threshold: 9 of 40 open deals are stalled (about **23%**), and open deals are 74 days old on average against a 60-day cycle. Deals older than your average cycle are less and less likely to close.

What makes it lie: automatic activity. If an email sequence logs a touch every few days, nothing ever looks stalled. Count only activity that involves the buyer.

## The 12 sales pipeline metrics on one page

The cheat sheet gathers the twelve metrics, their value in the worked quarter, how often to look at them, and the CRM field each one reads. The field is where to look first when a number surprises you.

| Metric | Formula | Worked quarter | Review | Field it reads |
| --- | --- | --- | --- | --- |
| 1. Opportunities created | New qualified opportunities in the period | 60 | Each week | Creation date, stage |
| 2. Pipeline value created | Sum of amounts created | 690,000 | Monthly | Amount |
| 3. Win rate | Won ÷ closed | 25% | Monthly | Outcome |
| 4. Stage conversion rate | Reached N+1 ÷ reached N | 65% (discovery to demo) | Monthly | Stage history |
| 5. Sales cycle length | Average days from creation to close | 60 days | Quarterly | Creation and close dates |
| 6. Time in stage | Average days in each stage | 18 days (proposal) | Monthly | Stage entry dates |
| 7. Loss reasons | Lost per reason ÷ lost | 25% no decision | Quarterly | Loss reason |
| 8. Pipeline coverage | Open pipeline ÷ target | 1.9x (4x needed) | Each week | Amount, stage |
| 9. Weighted pipeline | Sum of amount × stage probability | 147,000 | Each week | Amount, stage |
| 10. Sales velocity | Opportunities × deal size × win rate ÷ cycle | 2,000 per day | Monthly | Amount, outcome, dates |
| 11. Slippage rate | Pushed ÷ expected to close | 40% | Each week | Expected close date |
| 12. Stalled deals and deal age | Inactive ÷ open; average age | 23%; 74 days | Each week | Last activity date |

The fields each stage must hold before a deal moves are listed stage by stage in our guide to [sales pipeline stages](https://derrick-app.com/b2b-marketing/sales-pipeline-stages); this table only names the one each metric depends on.

## Leading vs lagging: which sales pipeline metrics predict and which report

A lagging metric tells you what already happened. A leading metric moves before the result does, early enough to act on it. Teams that review only lagging numbers find out about a bad quarter when it is over.

| Metric | Type | What it warns about |
| --- | --- | --- |
| Opportunities created | Leading | Revenue one cycle from now |
| Pipeline value created | Leading | Revenue one cycle from now |
| Pipeline coverage | Leading | Whether next period's target is reachable |
| Weighted pipeline | Leading | The likely result of the period |
| Stalled deals and deal age | Leading | Coverage that is weaker than it looks |
| Slippage rate | Leading | A forecast built on dates that will move |
| Time in stage | Leading | A cycle that is getting longer |
| Stage conversion rate | Mixed | Where future deals will stop |
| Sales velocity | Mixed | The pace of the whole pipeline |
| Win rate | Lagging | How the closed deals ended |
| Sales cycle length | Lagging | How long the closed deals took |
| Loss reasons | Lagging | Why the lost deals were lost |

The leading metrics are the ones to check in the pipeline review each week. The lagging ones are read monthly or quarterly, and they feed the leading ones: the win rate sets the coverage you need, and the cycle tells you how far ahead coverage has to look.

## Qualification problem or closing problem? Reading the metrics together

One metric rarely tells you what is wrong. Two questions, asked in order, usually do.

**First question: is it a qualification problem or a closing problem?** Look at the stage conversion rates and the loss reasons. (For a wider view of where B2B sales teams get stuck, see our guide to the [8 B2B sales challenges](https://derrick-app.com/b2b-marketing/b2b-sales-challenges).) If deals die early, between discovery and demo, and the top loss reasons are "poor fit" and "no decision", the deals should not have been opened: the problem is qualification, upstream. If deals reach proposal and negotiation in good numbers and are lost there, to price or to another supplier, the problem is closing. In the worked quarter, a quarter of losses are "no decision" and 35% of opportunities never reach the demo: qualification is the first suspect.

Before concluding, check the field behind it. A "no decision" loss is often a deal whose contact left the company, or whose account was bought, and nobody noticed. That is not a qualification problem; it is a record that aged.

**Second question: is the pipeline too small or too slow?** Look at coverage and velocity side by side. Low coverage with a normal velocity means you do not have enough deals: the fix is more opportunities created, which takes one cycle to show. Normal coverage with a low velocity means deals are there but do not move: look at time in stage, slippage and stalled deals. In the worked quarter, coverage is 1.9x against 4x needed: the pipeline is too small, whatever its speed.

Then check the fields again. Coverage that looks fine because of 9 stalled deals is not fine; remove the stalled ones and recompute before you decide the pipeline is big enough.

## How to run a sales pipeline analysis in 5 moves

A sales pipeline analysis is the monthly or quarterly version of the reading above, done on the whole pipeline. Five moves, in this order.

1. **Clean.** Close out or re-qualify every open deal with no buyer activity for longer than your average cycle, and every deal whose close date is already past. Check that the contact on each deal still works at the account.
2. **Measure.** Compute the twelve sales pipeline metrics on the cleaned pipeline, for the period and for the previous one.
3. **Locate the stage that loses.** Compare stage conversion rates and time in stage with the previous period. The stage that moved most is where to look.
4. **Check the forecast.** Compare last period's weighted pipeline with what was actually won. A large gap means your stage probabilities need to come from your own history.
5. **Decide.** One or two actions, each tied to a metric you will read again next period: more opportunities created in a [customer segment](https://derrick-app.com/b2b-marketing/b2b-customer-segmentation) that converts, a qualification rule, a stage exit criterion. Our guide to the [sales process steps](https://derrick-app.com/b2b-marketing/sales-process-steps) covers how those rules fit the rest of the process.

The deal-by-deal review held each week is a different exercise, covered in our guide to [sales pipeline stages](https://derrick-app.com/b2b-marketing/sales-pipeline-stages). The analysis looks at the pipeline as a system; the review looks at each deal.

**One email every 2 weeks.** Fill Down covers go-to-market and sales data tactics, including how to keep the data behind a pipeline worth measuring. [Subscribe to the Fill Down newsletter →](https://www.linkedin.com/newsletters/fill-down-gtm-sales-news-7480639838598184961/)

## Why benchmarks for sales pipeline metrics disagree

Look up a "good" pipeline coverage and you will find 3x, 3 to 4x, and up to 6x, sometimes on the same page of results. Look up a "good" win rate and the answers range from around 20% to above 50%. These ranges do not agree because they measure different things: win rates counted from different stages, with or without "no decision" deals, in markets with different deal sizes and cycles.

A coverage benchmark is a win rate in disguise. 3x assumes a win rate of about 33%; 4x assumes 25%; 6x assumes about 17%. Applying someone else's multiple means applying someone else's win rate. The only defensible reference is your own history: **coverage needed = 1 ÷ your win rate, measured from the stage where your open deals sit**. A pipeline full of early-stage deals needs more coverage than one full of deals in negotiation, because its win rate is lower.

The same goes for all twelve sales pipeline metrics on this page. Compare each one with your previous period, and between your own segments, sources and teams measured the same way. A market average tells you little about whether your quarter is on track.

## Stale records, wrong metrics: refreshing the accounts and contacts behind open deals

Several of the traps above share one cause: the opportunity stays open while the contact moves on, the account is acquired or renamed, the email starts to bounce. The deal still counts in coverage and velocity, and ends months later as a "no decision".

Derrick does not calculate these metrics and does not replace your CRM. It keeps the account and contact data under your opportunities current. Before the pipeline review, export the companies and contacts of your open deals and import them into the Derrick web app: [Enrich Companies](https://derrick-app.com/features/enrich-companies) refreshes each company from its LinkedIn page (1 credit per company) and [Enrich Leads](https://derrick-app.com/features/enrich-leads) returns each contact's current job title and company from their LinkedIn profile (1 credit per profile), so you can see who has moved. Both run on the free plan (100 credits a month, no card needed) with your LinkedIn account connected through the Derrick Chrome extension. The same actions run from the Google Sheets sidebar, from Claude or any MCP client such as ChatGPT, or from the REST API to refresh your CRM on a schedule (API and MCP from the Plus plan). How cleaner data speeds up a pipeline is covered on our page about [data enrichment and pipeline velocity](https://derrick-app.com/data-enrichment/pipeline-velocity).

## Where to use Derrick: web app, Google Sheets, Claude (MCP) or API

The same B2B data enrichment is available on four surfaces. The free plan gives 100 credits a month, no card required.

- **Web app** (main entry, nothing to install): import or paste your list and enrich it in the browser. https://app.derrick-app.com
- **Google Sheets**: the sidebar add-on enriches your list in place, inside your spreadsheet. Install: https://workspace.google.com/marketplace/app/linkedin_email_phone_finder_ia_%E2%80%94_derrick/3746789989?flow_type=2
- **Claude / AI agents (MCP)**: connect the Derrick MCP server, then enrich from chat. Setup: /mcp
- **REST API**: call the same enrichment endpoints from your own stack (PLUS plan and up). Docs: https://app.derrick-app.com/api-docs

## FAQ

### What are pipeline metrics?
Pipeline metrics are the numbers that describe the opportunities a sales team is working: how many are created, how they convert from stage to stage, how long they take, and whether the open pipeline is large enough to reach the target. They start where lead generation metrics stop, at the creation of a qualified opportunity.

### What is the formula for sales pipeline velocity?
Open qualified opportunities multiplied by average deal size and by win rate, divided by the sales cycle length in days. The result is revenue per day. With 40 opportunities, a 12,000 average deal, a 25% win rate and a 60-day cycle, velocity is 2,000 per day.

### What is a good pipeline coverage ratio?
The one that matches your own win rate: coverage needed equals 1 divided by your win rate, measured from the stage where your open deals sit. With a 25% win rate you need about 4x your target; with 40%, about 2.5x. Generic figures of 3x or more disagree because they assume different win rates.

### What is the most important sales pipeline metric?
Win rate, because most of the others depend on it: it sets the coverage you need, it drives velocity, and it tells you whether the deals you open are worth opening. Read it with the deals that ended without a decision counted as lost.

### How often should you review pipeline metrics?
Leading metrics such as opportunities created, coverage, weighted pipeline, slippage and stalled deals belong in the review held each week. Conversion metrics are read monthly, and the sales cycle and loss reasons quarterly, because they need enough closed deals to mean something.

### What is the difference between a pipeline metric and a sales KPI?
A sales KPI is any number a sales team is judged on, including revenue and activity. A pipeline metric is a KPI computed on the opportunities themselves: their number, value, conversion, age and speed. Every pipeline metric can be a KPI; not every sales KPI describes the pipeline.

### What is the 10-3-1 rule in sales?
It is a rule of thumb, not a law: out of 10 prospects, about 3 become real opportunities and 1 becomes a customer. It is useful as a starting assumption for a new team. Once you have closed a few dozen deals, replace it with your own stage conversion rates and win rate.

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