When it comes to determining pre-revenue startup valuations, there are a lot of factors to consider. From the strength of the management team and the competitive environment to sales and marketing risk and stage of the business, quite a few qualitative variables can affect the pre-revenue valuation of a startup. And even after all this information has been sifted through and synthesized, the final estimate is still that – an estimate.
Getting the Full Picture
There’s no singular method to most accurately determine the pre-revenue value of a startup, which is why it’s prudent for investors and entrepreneurs to have a solid understanding of each methodology to be able to get the full picture. Here are a few of the most commonly used methods:
Created by prolific angel investor Dave Berkus, the Berkus Method measures both qualitative and quantitative factors to deliver a valuation based on five critical components that can each be assigned up to a $500,000 valuation for reducing risk:
At a perfect score, a startup’s valuation tops out at $2.5 million.
The Berkus Method offers a highly simplified way to come up with a pre-revenue, pre-seed valuation estimation. While this method can be useful for applying a valuation to very early stage companies, it does have disadvantages, including the fact it is fairly limited in scope and that it doesn’t take the market or competitive advantage into account – both of which are very important in most cases.
The Scorecard Method, or the Bill Payne valuation method, compares the pre-revenue startup to funded startups, adjusting the average valuation depending on factors like stage, market, and region. It takes a similar approach as the Berkus Method, with the addition of more factors.
To begin with this method, you will need to determine the average pre-money valuation for pre-revenue startups in-market. Crunchbase and AngelList are excellent resources for researching startup valuation data to find a pre-revenue valuation benchmark.
Once the average has been determined, the pre-revenue startup is compared to your perception of similar venture deals in-market, considering the following:
- Strength of the Management team – 0-30%
- Size of the Opportunity – 0-25%
- Product/technology – 0-15%
- Competitive Environment – 0-10%
- Marketing/Sales Channels/Partnerships – 0-10%
- Need for Additional Investment – 0-5%
- Other – 0-5%
Of course, the ranking of each factor is subjective. Something to note about this model is the weight placed upon a high-quality team, which is reflective of Payne’s argument that “a great team will fix early product flaws, but the reverse is not true.”
Finally, the percentage weights can be calculated. In his worksheet, Payne illustrates his example using the following table:
In this example, Payne assumes a startup with an excellent team (125% of the norm), a big market opportunity (150% of the norm), and a market-average product (100% of the norm). Evaluating the market competition, the startup falls below standard (75% of the norm) but receives great early customer feedback (100% of the norm). Improvements could be made to the startup’s marketing, sales channels, and partnerships (80% of the norm).
Using this information, the sum factor (1.075) is multiplied by the average pre-money valuation – $1.5 million in this case – to deliver a pre-money valuation of $1.6 million.
The Scorecard Method offers a more comprehensive measurement, but like the Berkus Method, is highly subjective.
Risk Factor Summation Method
The Risk Factor Summation Method combines elements from the Berkus Method and the Scorecard Method to deliver a more granular estimation that focuses on risk. This method assesses the following risk factors:
- Stage of the business
- Legislation/political risk
- Manufacturing risk
- Sales and marketing risk
- Funding/capital risk
- Competition risk
- Technology risk
- Litigation risk
- International risk
- Reputation risk
- Potential lucrative exit
Each area of risk above is scored as follows:
- -2 – very negative (-$500,000)
- -1 – negative for scaling the startup and carrying out a successful exit (-$250,000)
- 0 – neutral ($0)
- +1 – positive (+$250,000)
- +2 – very positive for scaling the startup and carrying out a successful exit (+$500,000)
The average pre-money valuation of pre-revenue startups in-market increases by $250,000 for every +1, or $500,000 for every +2. The pre-money valuation decreases by $250,000 for every -1 and $500,000 for every -2. The average valuations in-market can be determined using the Scorecard Method.
The Risk Factor Summation Method can be especially useful in helping to examine the various types of risks that must be managed in order to achieve a successful exit, and pairs nicely with the Scorecard Method for a well-rounded assessment.
Venture Capital (VC) Method
The Venture Capital Method uses industry metrics to work backward from post-money to pre-money valuation. This method requires two primary equations:
- Post-money valuation = Terminal value / Expected ROI
- Pre-money valuation = Post-money valuation – Investment
Terminal value is the expected value of an asset on a specified date in the future, typically between four to seven years. Because of the time value of money, the terminal value must be adjusted to reflect current value. This can be done by taking the average sales of mature companies within the same industry at the end of the projection period, multiplied by 2.
For example, a startup is raising $400,000 and expects to be generating $10,000,000 when the company is sold in five years:
Terminal Value = $10,000,000 * 2 = $20,000,000
On average, less than 50% of startups succeed. With that in mind, investors typically aim for an ROI of 10x-30x of their investment. To be conservative, assume the expected ROI is 10x for the pre-revenue startup. Understanding the startup is raising $400,000, we work backwards to determine the pre-money valuation:
- Post-money valuation = $20,000,000 / 10x = $2,000,000
- Pre-money valuation = $2,000,000 – $400,000 = $1,600,000
A second approach that can be applied to the VC Method uses Price/Earnings ratios (P/E ratio) as the multiple for valuation. If the expected post-tax earnings are 15% on exit in five years, this leaves you with $1,500,000 ($10,000,000 * 15%). This value is then multiplied by the average industry P/E ratio. For this example, assume the P/E ratio is 15x with an expected ROI of 10x:
- Terminal Value = $1,500,000 * 15x = $22,500,000
- Post-money valuation = $22,500,000 / 10 = $2,250,000
- Pre-money valuation = $2,250,000 – $400,000 = $1,850,000
Most often, investors will use both approaches, averaging the results to determine the pre-revenue valuation of the startup. In this case, it would be $1,725,000.
For entrepreneurs and investors, it’s important to understand that there is no single valuation method that is foolproof; however, using a combination of these methods can help provide a ball-park range valuation estimate for an early stage, pre-revenue startup.