What's the best way to predict your startup's exit value using market data? (2024)

Typically, startups are unprofitable or make small profits whereas most at least make some revenues. So, valuing startups based on revenue multiple is more common. And instead of taking the revenue for the trailing 12 months or forecasted revenue for next 12 months, it is common to use the Annualized Revenue Run rate (ARR) where the last month's revenue is just multiplied by 12.Selecting the revenue multiple is more art than science. One typically looks for comparable startups in the same sector/segment and geography and preferably at a similar stage of evolution. The quality and track record of the founders and management team can also be an important factor.

As mentioned in the note following the point #1, it is vital to ascertain the key metric first. In startups wherein manpower is key, then it should be used as a multiple. The most widely used multiple is sales as the ecosystem of startups in general doesn't construe profits for many years.Installed capacity (in case the startup is driven by heavy engineering), total assets (if it is pro physical assets), and intangible (if it is IP based) are other multiples that can be used.Once the multiple is fixed, it is based upon the average value of recent transactions that have taken place in the market. In case the startup is heavily driven by IoT, the Moon and Schwartz model can be used, though with a pinch of salt.

This method involves comparing your startup's key metrics (such as revenue, EBITDA, or users) to similar companies that have been acquired or gone public. It provides a straightforward way to estimate exit value based on market comparables. However, it may be limited by the availability and quality of comparable data, differences in growth rates and margins, and market conditions.

Notwithstanding the superiority of DCF as a valuation approach, it is not suitable to value a typical startup. The principal reason is that a startup doesn't have profits for a considerable amount of time. This makes the projection of cash flows very difficult. Therefore, some authorities suggest bringing in real options analysis (ROA), which is an extension of NPV (read DCF). Start-ups involving R&D, technology, and innovation are usually valued using ROA.

DCF may be more commonly used for startups in niche or new segments where we may not find comparable startups based on which we can select a valuation multiple. The challenge here is that DCF needs cash flow projections for at least the next 5 years but there would be a lot of uncertainty regarding even the next year's cash flow for a startup, not to mention next 5 years.Since startups are high risk investments, we would normally want to use a high discount rate and that can be subjective.

DCF involves estimating the future cash flows your startup will generate and discounting them back to present value using an appropriate discount rate. This method requires making assumptions about future performance and can be complex, but it allows for a more customized valuation based on the unique characteristics of your startup.

The Venture Capital Method can be used as a last resort when neither the multiples-based valuation or DCF is possible. It takes away the complexity of finding comparable companies or projecting cash flows.However, it is somewhat arbitrary as it just depends on the return expectations of the VC for the capital they have invested without regard to whether the startup really deserves the valuation. Of course, valuation in previous rounds can bring some sanity to the process.

It's important to define the Purpose of valuation before deciding which method applies. Typically funding in venture capital involves multiple classes of stock which has differential rights and by using recent funding and saying its worth $ million is not appropriate. Evaluating various rights and understanding the complexity of pay-off (in events such as Dissolution/IPO/M&A) to various classes of stock needs involvement of specialized skills. Investors can put in return expectations from 5.0x to 100.0x while in reality only 5% - 10% (% changes by different studies optimistically only 20% companies survive to give higher returns) gives higher return. Also post money is not good valuation method to rely on due to various reasons.

This method involves estimating the potential return on investment for venture capitalists based on the expected exit value of your startup. It typically involves projecting future revenues or profits and applying a desired rate of return to determine the present value of the investment.

Given the limited track record and variability in the revenue, growth and margins for startups, as well as the fact that valuation multiples change based on macro economic conditions and sentiment, using a Regression model which finds the best fit based on historical data may be open to debate.

Machine learning models can analyze large datasets to identify patterns and make predictions about your startup's exit value. These models can incorporate various factors beyond traditional valuation methods, but they require access to extensive and high-quality data and expertise in machine learning techniques.

Using multiple methods for valuation can help in a sense that it can compel us to put some more thought into key aspects and assumptions regarding the startup.

Hybrid approaches combine elements of multiple valuation methods to provide a more comprehensive and accurate estimate of your startup's exit value. For example, you could use market multiples as a baseline and adjust the valuation based on factors specific to your startup using DCF or venture capital methods.

I wrote an excellent article on how early stage companies are valued on my page called “How Venture Capitalists Value Early-Stage Companies” that captures a lot of nuance as it relates to this collaborative article’s big question.At the end of the day, the exit value of a company is theoretical until the initial investor finds a buyer who is willing to pay more for it than what the original investor paid. If I’m going to be realistic about my exit value, I’m going to be very mindful of the fact that most VC investments exit via M&A and I’m going to want to know what factors are affecting the liquidity and multiples within my niche. Understand what the probabilities of those factors are as it relates to your investment.

An example of a solid way to use the market data, if relevant, is to compare the team's track record to successful teams that already have won in their exit.