Demo to Close Calculator
The formula
What the demo-to-close rate tells you
The expensive-stage conversion: of everything that reached a live demonstration, how much signed — a direct read on whether demos are discovery-driven or feature tours.
Calculation: Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost. Enter your inputs and every substitution is shown below the result.
Reading the result
Low demo-to-close with high demo volume is not a closing problem, it is a qualification problem that the demo politely concealed.
Rules of thumb: 25–40% demo-to-close for mid-market; below 20% with high volume means leaky top-of-funnel
Limitations and best practice
SE-supported demos cost more than the number implies — track blended hours including the support team, and weight the rate against deal size, not counts.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Should you limit demos to raise the rate?
Do second demos close better than first?
Source & methodology
Sales-enablement benchmarking.
How Demo to Close works — and what your result really means
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Demo to Close is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get Demo-to-close rate in real time, and see every substitution printed below.
The useful way to hold Demo to Close is as a ratio with a story attached: Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost says how the parts combine, and the 31.4% figure above is simply that sentence written in numbers. Everything that follows unpacks one clause of the sentence at a time.
There is a habit that separates people who get useful answers from Sales & Revenue numbers: they decide what question the figure answers before they compute it. Demo to Close answers “Demo-to-close rate?” — and nothing else, which is precisely why the result is trustworthy.
Nothing below is stock text pasted around a number: the worked example computes demo-to-close rate = 31.4% from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Demos delivered first, at ≈11.1 % of the headline for a ten-percent error either way in that input. Work down the page and by the end you could re-derive the result in a spreadsheet from memory.
The Demo to Close formula, explained
Here is the complete model this tool runs — Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
Demos delivered (example value 86) is a quantity rather than a category — precision here is cheap and worth having. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Deals closed won (example value 27) is a measured number in the unit named by the label; the formula does not convert for you. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Average deal size ($) (example value 42,000) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Measure twice and use the unit the label asks for — length terms often scale the result geometrically.
Hours per demo (prep + delivery) (example value 4) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Be precise about the boundary (exact date, start of month); time inputs decide the exponent in most formulas.
A fully worked Demo to Close example
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Demos delivered, Deals closed won, Average deal size ($), Hours per demo (prep + delivery). The computed demo-to-close rate comes out at 31.4%, which the interpretation band labels “Each win costs 12.7 demo hours”.
- Rate = 27 ÷ 86 = 31.4%
- At 4h of seller+SE time per demo, one win burns 12.7 hours of the scarcest GTM resource
Demos needed per win — 3.19. If your inputs change, this is usually the first companion figure to move.
Demo time per win — 12.7 hours. Compare it against the main result of 31.4% before drawing conclusions.
Revenue per demo delivered — $13,186. Compare it against the main result of 31.4% before drawing conclusions.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Demo to Close corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Demo to Close was recomputed at 5 points along the dominant input, with every other field left untouched.
| Demos delivered setting | Demo-to-close rate |
|---|---|
| 80 % of the example value | 39.2% |
| 90 % of the example value | 34.9% |
| example inputs | 31.4% |
| 110 % of the example value | 28.5% |
| 120 % of the example value | 26.2% |
The corridor runs from 26.2% to 39.2% across that band — which is the range worth planning inside rather than the single 31.4% point estimate. Reproduce it in the form above by editing Demos delivered alone; the substitution steps will follow your figures exactly.
What actually moves your Demo to Close
This list was computed for this specific engine just now: each numeric input was nudged ±10 % while every other field held its example value, and the demo-to-close rate was recalculated from scratch. It is the fastest honest answer to “what matters most in Demo to Close?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Demos delivered: ten percent up gives 28.5%, ten percent down gives 34.9% — ≈11.1 % of the demo-to-close rate either way
- Deals closed won +10 % → Demo to Close = 34.5% · −10 % → 28.3% (the demo-to-close rate shifts ≈10.0 %)
Demos delivered is the dominant lever here: ten percent either way moves the result by about 11.1 %, from 28.5% to 34.9%. That is where a careless figure does the most damage, so check it against a source, and treat Deals closed won as the second priority (≈10.0 % per ten percent). Everything below that can stay approximate, which is a licence to stop chasing data that would not change the decision.
Is your Demo to Close good — reading the result bands
Nobody acts on a bare figure — they act on a figure with a comparison attached. The verdict attached to the default calculation — “Each win costs 12.7 demo hours” — is one band on a ladder your own figure may sit somewhere else on. How much of that band is luck? On Demos delivered alone ten percent either way covers 28.5% to 34.9%. The practical reading rules: read the band as a starting hypothesis, then test it: change the two dominant inputs by ten percent and see whether the verdict survives. Verdicts that survive stress are the ones worth acting on.
Related measures answer related questions, and the distinctions matter: Demo to Close is the quantity, Demo-to-close rate is this tool’s reading of it, and the decision that follows belongs to neither of them separately.
Common mistakes with Demo to Close (and the fix)
SE-supported demos cost more than the number implies — track blended hours including the support team, and weight the rate against deal size, not counts. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reporting the headline and quietly discarding Demos needed per win. The companions are where the shape of the trade-off survives the rounding.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows Demos delivered dominating — a careful figure there beats false precision everywhere else.
Another is comparing across contexts: a Demo to Close computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
Six things to confirm before acting on Demo to Close
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Put Demos delivered under a magnifier; the sensitivity table above is the reason why.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Confirm the answer against one independent method or published benchmark for Demo to Close.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — collect, then type. Everything this tool asks for is listed above (demos delivered, deals closed won, average deal size ($), hours per demo (prep + delivery)). Pull each figure from something you can point at — paperwork, a dashboard, a label — before touching a field. Guesswork at the input stage cannot be repaired at the interpretation stage. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Step 2 — enter the conservative case first. Resist the flattering scenario. Type the inputs you would defend in front of a sceptical reader, read the Demo-to-close rate (31.4% for the example values), and note the verdict band. When two sources disagree, it is almost never the arithmetic that differs.
Step 3 — measure what deserves measuring. The ranked levers above tell you where a careful figure pays off. Everything else can stay approximate, which is a licence to stop hunting for data you do not need. If the answer changes your behaviour, it deserves a second run with different assumptions.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. Most surprises in numbers are surprises about inputs, not about formulas.
Step 5 — save the story with the figure. A number without its inputs and its date is unusable within a quarter. Record 31.4%, the assumptions behind it, and today’s date; your future self will be auditing a stranger’s arithmetic. Most surprises in numbers are surprises about inputs, not about formulas.
From calculation to decision: where Demo to Close earns its keep
In Sales & Revenue the figure computed here is usually the first one somebody asks to see. Having it — with the formula behind it — changes your position in the conversation from participant to reference. Estimates improve most when the worst case is written down in ink.
The audience for this page is people who need one trustworthy number before their next decision. In professional Sales & Revenue practice the pattern is always the same — screen with Demo to Close, then invest slow analysis only in whatever survives the screen. Write the assumptions in the same file as the result, and future arguments take minutes instead of meetings.
Treat Demo to Close like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. Half of a good calculation is knowing which input you would hate to be wrong about.
Demo to Close — frequently asked questions
What affects Demo to Close the most?
Demo to Close is driven above all by Demos delivered. Perturbing only that field by ten percent either way produced 28.5% against the 31.4% baseline — a ≈11.1 % response, while Deals closed won manages ≈10.0 %.
Which matters more: deals closed won or demos delivered?
By the numbers, Demos delivered: a ten-percent change in it moves the result ≈11.1 %, versus ≈10.0 % for Deals closed won. Spend your measuring effort in that order — precision on the weaker lever buys almost nothing.
What is a typical Demo to Close?
With the example inputs on this page the result is 31.4%, labelled “Each win costs 12.7 demo hours”. “Typical” varies with situation, which is why every result here ships with its verdict band and its sensitivity list: they turn one figure into a range you can locate yourself inside.
How do I calculate Demo to Close by hand?
Use the stated model — Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost — and substitute in the order the tool prints (it starts from Rate = 27 ÷ 86 = 31.4%). On the example inputs the hand route lands on 31.4%, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Demo to Close if demos delivered changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 28.5% to 34.9% across the ten-percent probe, i.e. ≈11.1 % sensitivity on the demo-to-close rate.
Is the Demo to Close result of 31.4% good or bad?
The tool answers “what”, not “whether”: 31.4% carries the verdict “Each win costs 12.7 demo hours” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
Can Demo to Close be negative or empty?
Yes, and that is informative rather than broken: a negative Demo to Close usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
What affects Demo to Close the most?
Sensitivity depends on where you start, but the inputs Demos delivered and Deals closed won typically move Demo to Close further than the rest because they enter the formula multiplicatively. If you can only measure two things well, measure those and hold the others at conservative defaults.
Should you limit demos to raise the rate?
Yes if capacity-bound — the "no-demo" trial-led motions in product-led companies trade demo cost for a different qualification path; measure revenue per rep-hour, not just the rate.
Do second demos close better than first?
Consistently — a second meeting signals multi-threading; single-demo closes skew smaller and churn more across most published cohort data.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
Key terms on this page
- Demos needed per win
- 3.19 for the Demo to Close worked case; it sits next to the main result because it carries context the headline leaves out.
- Demo time per win
- 12.7 hours for the Demo to Close worked case; it sits next to the main result because it carries context the headline leaves out.
- Revenue per demo delivered
- $13,186 on the example inputs — a companion figure printed beside the headline of Demo to Close so that no result is read in isolation.
- Demo-to-close rate
- The primary output of this tool: 31.4% for the default inputs, computed exactly from Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost.
- Worked example
- Every substitution in order, from the example inputs to 31.4% — the audit trail for the headline figure.
- Verdict band
- The interpretation attached to a result (“Each win costs 12.7 demo hours” on these inputs), which turns a bare number into a position on a scale.
- Sensitivity (±10 %)
- How far the Demo to Close moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
There is no black box on this page — the engine evaluates Demo-to-close = wins ÷ demos; cost per demo = hours × loaded hourly cost. Source of record: Sales-enablement benchmarking. Any other implementation of this model should return the same figure for the same inputs. If one does not, the difference is in its assumptions — which this page prints and that one probably does not.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The design constraint was set by usefulness rather than by comfort: an estimate you can interrogate beats an answer you have to trust.
After the number: what to do with it
Save the number together with its inputs and today’s date; a Demo to Close figure without context is unusable the moment an input changes.
This page was written for people who need one trustworthy number before their next decision, and the promise is that nothing above required trust. Bookmark the tool, re-run it whenever an input moves by more than a few percent, and keep the date with the number.