Ten sales pipeline metrics, four questions
One pipeline figure hides four separate answers. Ten metrics give them back.
Summary
- Four questions decide whether a pipeline will deliver: is there enough, are these the right deals, will they close in time, and are the numbers true.
- Ten metrics answer them: three for quantity, three for quality, three for speed and one for honesty.
- Start with the last question. If the data is not honest, every other number inherits the error.
Picture a founder whose pipeline report shows ₹4 crore of open deals against a ₹1 crore quarter. Ten weeks later the quarter closes at ₹70 lakh, and nobody in the room can say which part of the ₹4 crore let her down.
The report was asking one figure to answer four questions. Is there enough? Are these the right deals? Will they close in time? Are the numbers even true? A pipeline that fails any one of them misses the target as surely as an empty one.
This is the first of four pieces on pipeline health, and it is the map. The next three take pipeline coverage, velocity and the choice of sales motion in turn.
The ten pipeline metrics, grouped by the question each answers
| Question | Metric | How it is worked out | What it tells you |
|---|---|---|---|
| Quantity | Total active pipeline | Value of every open deal | What you have to work with today |
| Quantity | Pipeline coverage | Open pipeline ÷ target for the period | Whether the pile is big enough for the target |
| Quantity | Net new pipeline | Value of deals added each week or month | Whether the pipeline is refilling as fast as it empties |
| Quality | Win rate | Deals won ÷ deals decided (won plus lost) | How often a deal that reaches a decision goes your way |
| Quality | Average deal size | Value of deals ÷ number of deals | Whether deals are growing, or you are chasing volume instead |
| Quality | Stage conversion | Share of deals that move on from each stage | Where in the process deals are lost |
| Velocity | Sales cycle length | Average days from first conversation to signed contract | How long revenue takes to arrive |
| Velocity | Stage duration (ageing) | Average days a deal spends in each stage | Which stage is the bottleneck |
| Velocity | Pipeline velocity | Deals × win rate × deal size ÷ cycle days | Revenue the pipeline produces per day |
| Health | Push rate | Share of deals whose close date moved to a later quarter | Whether forecast dates reflect buyers or hope |
Quantity: is there enough?
Think of the pipeline as a water tank. Total pipeline is today's level. Coverage compares that level with what the quarter will draw. Net new pipeline is the tap that refills it.
The tap is the one founders forget. Suppose deals leave your pipeline, won or lost, at ₹80 lakh a month, while new ones arrive at ₹30 lakh. A ₹3 crore pipeline is then empty in six months.
A tank can look full on the day you check it and still be empty by the time you need it.
Quality: are these the right deals?
These three numbers can cover for one another, so read them together. A team whose win rate is slipping often keeps revenue steady by chasing more, smaller deals.
Last year it closed ten deals of ₹10 lakh. This year it closes twenty of ₹5 lakh. Revenue is the same ₹1 crore, but the team ran twice the demos, proposals and follow-ups to earn it.
Stage conversion then shows where deals are lost, the way a plumber finds the joint that drips. It is only as honest as your stage names, and our piece on revenue execution argues for naming them after what the buyer did.
Velocity: will they close in time?
Good deals in the pipeline are like passengers on a train. You know they are aboard. You do not yet know when they arrive.
Cycle length is the usual journey time. Stage duration spots the train that has stopped between stations. If deals normally spend 20 days at the proposal stage and one has sat there for 70, it is not slow. It is probably stuck.
Pipeline velocity folds quantity, quality and time into one figure: rupees of revenue per day. It gets its own piece, with a worked example.
Health: are the numbers even real?
Every number above comes out of the same CRM, so each one inherits its honesty. Push rate is the test of that honesty.
Picture an airport board where the same flights flip to "delayed" every hour. Of 30 deals forecast to close last quarter, 9 had their dates moved into this one: a push rate of 30%. Dates that keep moving were set by hope, not by anything a buyer agreed.
Push rate stands alone in its group, but it guards the other nine. When it is high, your coverage, cycle length and velocity all rest on the same wishful dates.
Where to start
Start with the last question, not the first. Make the data honest before anything else, because every later number inherits its errors. Then check there is enough, then that it is the right kind, and only then work on speed.
Put all four groups on the agenda of your monthly revenue review. Judge each metric by its direction over several months, not by a single reading, which can flatter or frighten for no good reason.
Questions
What are sales pipeline metrics?
Measures of the deals open right now: how much there is, how good it is, how fast it moves and whether the data can be trusted. The ten in the table cover all four.
How do you measure sales pipeline health?
Put one number against each question: coverage for quantity, win rate for quality, velocity for speed and push rate for honesty. If all four hold up month after month, the pipeline is healthy.
What is the difference between sales pipeline metrics and sales funnel metrics?
Funnel metrics follow leads through your process over a period, counting how many become customers at each step. Pipeline metrics look at the deals open today and ask whether they will produce the revenue you need, and when.
Which sales pipeline KPIs matter most?
Win rate and sales cycle length. Coverage, velocity and most forecasts are built from them, so if either is wrong, much of the rest is wrong with it.
What is pipeline push rate?
The share of forecast deals whose expected close date has moved into a later quarter. Track it by salesperson and by stage, because a high rate in one place often points to a single habit you can fix.
Figures as at October 2026.
How useful was this article?
One tap. It tells us what to write more of.
The next one
Get what we publish next, by email.
Working notes on raising, borrowing, protecting, growing and structuring capital in India. One email a week at most, and you can leave any time.
We use your address only to send this. See our privacy policy.
We store your address to send you these emails and nothing else. See our privacy policy.
Related reading
The services behind this article
What we do about it, for founders and finance teams. Each has its own page.
Revenue Operating System
For companies whose revenue is chaotic: planning, demand generation, execution and measurement, installed as one system you can forecast from.
FP&A Operations
The monthly financial planning cadence run as a service: close, review, variance, forecast and the board pack, by a team that sits inside yours.
Go-to-Market Planning
How the product reaches the buyer: channel, motion, pricing, and the numbers that say whether it worked.
