Startup Valuation Calculator
Valuing an early-stage startup is the opposite of valuing a bond. There is no stable cash flow to discount and no perfect comparable transaction, so the venture industry never relies on a single number. Instead it triangulates: run several methods, each looking at the company from a different angle — team quality, risk, exit scenarios, discounted cash flow, market multiples — and reconcile them. The widget above runs seven methods side by side, lets you toggle each one in or out, and averages the ones you trust into a consensus valuation.
If you are founding or angel-investing in Vietnam, you will negotiate in Vietnamese dong, and the headline numbers get large fast — a seed round is often tens of billions of VND, an exit hundreds of billions. The worked example below stays entirely in VND for exactly that reason. It also surfaces two uncomfortable truths. First, the methods routinely disagree by an order of magnitude: for the hypothetical seed-stage SaaS company below, the seven methods range from 43.750.000.000 (Berkus) to 600.000.000.000 (revenue multiple), a dispersion of 89%. That spread is not a bug — it is an honest picture of early-stage uncertainty. Second, forward-looking methods (VC, multiples) print much larger numbers than qualitative ones (Berkus, Scorecard) because they multiply projected revenue by an exit multiple. Cherry-pick the flattering methods and you will talk yourself into a valuation the next investor will not honour.
Once you have a range, the tool computes the due-diligence metrics real investors actually read: runway in months, burn multiple, the Rule of 40, the LTV/CAC ratio, CAC payback, the investor's post-round ownership, and projected MOIC. A standing caveat: every multiple, growth rate and probability in these examples is an illustrative assumption for a fictional company. None of it is a quote, a real company's figures, or investment advice.
The seven methods, and how the tool combines them
The tool takes the arithmetic mean of whichever methods you enable and uses it as the pre-money valuation that feeds the investor metrics.
1. Berkus — qualitative, pre-revenue
Assigns a value to five success factors (sound idea, prototype, team, strategic relationships, rollout plan) and sums them. Best when there is no revenue yet. In the example: 43.750.000.000.
2. Scorecard (Bill Payne) — comparables
Takes the average pre-money valuation of comparable funded startups and scales it by a blended factor from seven weighted criteria (team 30%, opportunity 25%, product 15%, competition/marketing 10% each, funding/other 5% each). Example: factor ≈ 1.06 → 62.500.000.000 × 1.06 ≈ 66.093.750.000.
3. Risk Factor Summation — risk-adjusted
Starts from a base value and adds or subtracts across twelve risk categories, each ±1 step worth a fixed amount. Example: base 50.000.000.000 + net risk score 3 × 6.250.000.000 per step = 68.750.000.000.
4. Venture Capital (VC) — backward from the exit
Exit value = exit-year revenue × exit multiple; divide by your target ROI for post-money; subtract the round for pre-money. Example (assumed): exit revenue 1.250.000.000.000 × 5 = 6.250.000.000.000; ÷ 10 target ROI = 625.000.000.000 post-money; − 50.000.000.000 round = 575.000.000.000 pre-money.
5. Discounted Cash Flow (DCF) — intrinsic
Discounts projected free cash flows plus a Gordon-growth terminal value to present. Example: year-1 FCF 25.000.000.000, growing 35%/yr for 5 years, discounted at 35%, perpetual growth 3% → 152.199.074.074.
6. First Chicago — scenario-weighted
A probability-weighted average of success / base / failure scenarios. Example: 20%×750.000.000.000 + 50%×200.000.000.000 + 30%×12.500.000.000 = 253.750.000.000.
7. Market / Revenue Multiple
Multiplies a metric (typically ARR or EBITDA) by a comparable transaction multiple. Example: ARR 100.000.000.000 × 6 = 600.000.000.000.
Consensus and dispersion
The mean of all seven is 251.363.260.582, range 43.750.000.000–600.000.000.000, dispersion 89% (coefficient of variation = standard deviation ÷ mean). High dispersion is a signal the methods disagree and you should drop the ones that do not fit the stage. Excluding the two forward-looking outliers (VC and Multiple), the remaining five average 116.908.564.815 at 67% dispersion — far closer to a realistic seed negotiation.
What the model leaves out
Every method is only as good as its inputs (multiples, growth rates, probabilities). The tool is a thinking framework, not a price. Treat the output as a negotiating range and always run independent due diligence.
Worked example: valuing a seed-stage VN SaaS startup (assumed, in VND)
Illustrative assumptions for a fictional company: ARR 100.000.000.000, growing 120%/year, 75% gross margin, net burn 6.250.000.000/month, 100.000.000.000 cash on hand, raising 50.000.000.000 this round.
| Method | Valuation (pre-money) |
|---|---|
| Berkus | 43.750.000.000 |
| Scorecard | 66.093.750.000 |
| Risk Factor | 68.750.000.000 |
| DCF | 152.199.074.074 |
| First Chicago | 253.750.000.000 |
| VC Method | 575.000.000.000 |
| Market Multiple | 600.000.000.000 |
| Mean of all 7 | 251.363.260.582 |
| Mean (excl. VC & Multiple) | 116.908.564.815 |
The range runs from 43.750.000.000 to 600.000.000.000 — a dispersion of 89%, far too wide to commit to one number. This is the textbook early-stage pattern: the two forward-looking methods (VC, multiple) drag the mean upward. Drop them and the remaining five converge near 116.908.564.815 (dispersion 67%), a more defensible pre-money to take into the room.
Term sheet at the 251.363.260.582 consensus pre-money
| Line | Value |
|---|---|
| Pre-money (mean of 7 methods) | 251.363.260.582 |
| Investment raised | 50.000.000.000 |
| Post-money | 301.363.260.582 |
| Investor ownership | 16.6% |
| Implied ARR multiple | 2.5x |
Due-diligence metrics (operating health)
| Metric | Value | Read |
|---|---|---|
| Runway | 16 months | ok (≥18 months is strong) |
| Burn multiple | 1.2x | burns 1.2 to add 1 of new ARR (≤1 is best-in-class) |
| Rule of 40 | 95% | growth + net margin (≥40% is healthy) |
| LTV/CAC | 5.0x | healthy (≥3 is healthy) |
| CAC payback | 6.4 months | time to recover acquisition cost (≤12 is good) |
| Projected MOIC | 5.0x | at an assumed 1.500.000.000.000 exit |
Read together: 16 months of runway and a 1.2x burn multiple show capital-efficient growth; the Rule of 40 clears the bar at 95% on the back of fast growth; LTV/CAC of 5.0x is healthy. But the projected MOIC is only 5.0x under the assumed 1.500.000.000.000 exit — below the 10x most venture funds target. That is exactly the trade-off the consensus table forces into the open before anyone signs.
Frequently asked questions
How do you value an early-stage startup?
Not with a single number — you triangulate across methods. This tool runs seven (Berkus, Scorecard, Risk Factor, VC, DCF, First Chicago, market multiple) and averages whichever you select. For the hypothetical seed SaaS company in the example, the seven span 43.750.000.000 to 600.000.000.000 VND with a 251.363.260.582 VND mean. A wide range is normal this early; the goal is a defensible negotiating range, not a precise figure.
What is the difference between pre-money and post-money valuation?
Pre-money is what the company is worth before taking the round; post-money = pre-money + the amount invested. The investor's stake = investment ÷ post-money. Example: a 251.363.260.582 VND consensus pre-money plus a 50.000.000.000 VND round gives a 301.363.260.582 VND post-money and 16.6% ownership. Always confirm whether a quoted number is pre- or post-money before negotiating percentages.
When should I use the Berkus and Scorecard methods?
Both suit pre-revenue or barely-revenue startups, where DCF is unreliable. Berkus assigns value to five qualitative factors (idea, prototype, team, relationships, rollout) — 43.750.000.000 VND in the example. Scorecard scales the average pre-money of comparable funded startups by a seven-criteria factor — an ≈1.06 factor giving 66.093.750.000 VND here. Once you have recurring revenue (ARR), revenue multiples and the VC method become more informative.
How does the VC method calculate a valuation?
The VC method works backward from the exit: exit value = exit-year revenue × exit multiple, divided by your target ROI for post-money, minus the round for pre-money. Example (assumed): 1.250.000.000.000 exit revenue × 5 = 6.250.000.000.000; ÷ 10 (a 10x target) = 625.000.000.000 post-money; − 50.000.000.000 round = 575.000.000.000 pre-money. Because it multiplies future revenue by a multiple, it often prints the largest number — be conservative with the exit assumptions.
Why do the methods disagree so much?
Because their assumptions differ. Qualitative methods (Berkus, Scorecard) are effectively capped in the tens of billions of VND; forward-looking methods (VC, multiple) multiply expected revenue and can reach hundreds of billions. In the example, dispersion hits 89%. The fix: drop the methods that do not fit the stage and average the rest — excluding VC and the multiple, the remaining five average 116.908.564.815 VND (dispersion 67%).
What are runway, burn multiple and the Rule of 40?
Operating-health metrics. Runway = cash ÷ monthly net burn (months of survival); example 100.000.000.000 ÷ 6.250.000.000 = 16 months. Burn multiple = annual net burn ÷ net new ARR; example 1.2x (≤1 is best-in-class). Rule of 40: growth % + net margin % should be ≥40; example 120 + (−25) = 95%. All three show how efficiently the company turns cash into growth, independent of valuation.
Are the valuation figures in the examples real?
No. Every multiple, growth rate, probability and cash flow in the examples is an illustrative assumption for a fictional company, chosen so the arithmetic is easy to verify. Real valuations depend on your company's actual figures and market conditions at the time of the raise. Enter your own numbers — the formulas behave identically for any input. This is not investment advice.