Verissimo Monthly - April 2025
Demystifying Startup Valuations
Thoughts on Investing and Starting Up
Anyone who has followed my writing for the last few years knows that I love DCFs as a great way to conceptually map startup characteristics to value drivers through four key variables: short term growth, long term growth, discount rate and free cash flow margin.
Even when I was in investment banking working with companies with $50M+ revenue, it was often hard to accurately perform a DCF analysis to point to a real valuation. In fact, during training at Morgan Stanley, a certain VP said “DCFs are just fun with excel - you can make it say whatever you want.” For investment bankers this is fine because more often than not, you are starting with the answer to the valuation question and then trying to apply rigor to justify that valuation.
The investing world is fundamentally different because buying an asset means that you’re stuck with it and will either need to sell it or illustrate value accretion to shareholders (or risk losing your job). Selling an asset as a broker is a much simpler game: get the highest price you can while still getting a deal done.
With the limitations of DCF analyses for high-growth, unprofitable tech companies, many look to comps multiples for valuation. I have written before about the limitations of the revenue multiple and the fact that it is an “output metric” based solely on comparison of value, but we are going to run with it for now with all of those considerations in the background. In most cases, it’s the best we’ve got.
There is a well-known phenomenon in investing that revenue is worth more if it’s growing faster - this makes sense on many levels, and it manifests in premium revenue multiples. As a result, there is a strong positive correlation between revenue growth and revenue multiple, with profitability playing a role as well (especially over the last couple of years).
This correlation works best with companies that are around the same revenue scale and growth. If revenue scale is far below or growth is far above the median, then the analysis breaks down. If, for example, a company is at $65M revenue scale and is growing 100% annually, then this correlation has limited value and we need to figure out another way to compare it to the public market comps.
I’ll introduce another valuation method (which we used at Morgan Stanley) called the Discounted Equity Valuation Method. (caveat: it’s super hand-wavy and can make a DCF for a highly unprofitable company look rigorous…). But as always, there is a broader point, and while the method may not yield definitive results, it provides a valuable framework for valuing companies without great public comps.
(You’ll see how this gets back to seed stage startups soon, so sit tight.)
We’ll start with example projections of a hypergrowth mid-to-late stage software company:
This company is currently at ~10% of the revenue scale of the 25th percentile and ~10x the median revenue growth of the publicly traded comparables shown above, which makes it very hard to use them as comps. But if we look a few years out, the revenue scale and growth get much closer to where comps are actually trading today. How do we compare 2027 numbers for this company to 2025 numbers for public comps?
Enter: The DEV (Discounted Equity Value) Method
The basic idea:
Take 1, 2 or 3 year forward multiple on the public trading comps
Apply it to a 3, 4 or 5 year forward revenue number on the target company (i.e., a 2-year shift)
Discount the valuation back to present value for the number of years that you shift using a discount rate
This is a very basic version of a DEV analysis. For comparison, this yields current company valuations of $1.7-2.6Bn whereas a simple comps multiple would yield $845M. It is effectively rewarding the company for its aggressive growth prospects. (Note this only works if the projected growth rates are higher than the discount rate.)
Naturally you can play with just about every variable here:
Comps multiples can change meaningfully based on comps selection and the current market
Shifts can be 1, 2, 3 or more years
Discount rate can vary greatly (and is probably the hardest variable to nail down without a reliable way to calculate WACC)
If you were trying to do a rigorous valuation analysis here, I would recommend a bunch of sensitivity analyses. The large range of outcomes that this analysis produces is also a good reason why you likely will see bankers using it much more than investors.
So who cares?
As per my normal theme, I am trying to find fundamentally sound reasons for many of the market dynamics and trends in the early-stage venture market. A strongly held belief is that investing is investing no matter the asset class or company stage: the job is to buy an asset for less than it is worth and then sell when the price corrects (or overcorrects). It doesn’t matter if it’s an ice cream shop, gold bars or a nascent AI company.
A long time scale makes this more complicated. If you are a day-trader and find a mispriced asset, you could be in and out within hours. For an early-stage startup investor, the corrections take much longer and the time-value of money is a much larger factor.
In many ways, early-stage VCs are betting on long-term enterprise value accretion in its purest sense. Sustainable revenue growth is always the key to success. High risk, high reward, low liquidity, long hold periods.
Underwriting at the early stage
Ultimately startups are trying to go from 0 to $1Bn+. But why does it need to go to $1Bn+? Naturally many startups never get there - having middling success or failing completely.
It comes down to underwriting the early-stage investment using the key variables:
Future Valuation
Discount Rate
Time
30% IRR for a VC fund is excellent, but would LPs in an early-stage venture fund get excited about a 1.3x? The simple answer is no. Early-stage venture targets high multiples of capital over long periods of time.
So what is the right mix of these variables to deliver exciting fund-level returns?
I recently met a founder who asked about changing the equation… and aiming lower - he was wondering if a multi-billion dollar outcome was really needed if the chances of success are higher. The theoretical answer is that if the time to exit is shorter and the discount rate is lower, then a smaller target future valuation should be acceptable. But are great VCs getting excited about those sorts of opportunities? The answer is generally no.
Why is the theory different from practice?
Outliers drive exciting fund returns - the real reason to invest in an early-stage venture fund is that one of the $1Bn target outcomes may end up being a $10Bn outcome and fund-level returns go from a solid 4x to an outstanding 20x.
Aiming low is deemed a bad signal on founders - their abilities, grit and vision.
Saying that discount rate is lower for one reason or another is a difficult claim to make.
Most investors want it all: de-risked founders & markets, incredibly high upside, medium time to exit - this becomes the optimization equation.
What is the key takeaway?
This has been a very long-winded explanation behind why “great markets” and “great founders” demand higher valuations even at the earliest stages - it is because they are deemed higher upside and lower discount rate.
What is the opportunity?
Arbitrage! Of course, that is the point of investing - buy underpriced assets and sell them when price corrects. When it comes to both founders and markets, we need to look for people and opportunities where the conventional market approach will undervalue them - only later on will the market recognize how great they and their markets really are, correcting valuation.
There is another popular approach: swing for the fences. Pay whatever you need to and make sure you’re absolutely getting into the best markets with the best founders and hope that you add an extra 10 turns on the return - anything else will yield mediocre-at-best returns. This approach can work in certain market environments, at certain stages and for certain investors. It is not our preferred method or approach.
Overall, we want to make sure that we optimize our ability to invest into the next cohort of $10Bn companies, but also that our returns will be outsized when that happens. We rely heavily on our network and pattern recognition to make this a reality.
We’re investing in great people from our network who fit our ideal founder profile and are bringing their energy to exciting markets with fundamental underlying shifts afoot. We believe these are the greatest opportunities of maximum returns. Some of these investments might seem weird or counter-intuitive, but at the pre-seed and seed, we believe strongly that that is the job!
Programming, Events, Content and More
🎙 Podcast Feature: Tech on the Rocks
Tune in to Verissimo’s Nitay Joffe, and Kostas Pardalis founder of Typedef, as they chat with tech geniuses on Tech on the Rocks—where hardware, cloud, and all things future-tech meet over a virtual drink!
Episode 17: Incremental Materialization: Reinventing DatabaseViews with Gilad Kleinman of Espio -
https://techontherocks.transistor.fm/17
🚀 Founder & Community Programming
Reminder to check out our It’s All About Everything Series!
Portfolio Highlights
We’re excited to announce our investment in WatchWell for Fund 2.
Founder and CEO Jonathan Weber impressed us early on, and his strong ties to the luxury world — alongside a major U.S. dealer as co-founder — position WatchWell to lead innovation in this space.
WatchWell is building the modern, technology-driven companion for luxury goods. In response to rising theft, WatchWell is developing a discreet, embedded geo-tracking solution for luxury watches, a "LoJack for watches." Beyond theft recovery, the technology unlocks new possibilities for asset tracking, digital engagement, and streamlined insurance claims, offering a smarter, more connected ownership experience.
Airvet recently announced a $11M Series B-2 round led by HighlandX.
Airvet provides 24/7 virtual veterinary care through a platform that connects pet owners to licensed veterinarians via video and chat. Core features include immediate access to urgent care consultations, behavioral support, and preventative wellness advice without the need for in-person visits. Airvet also partners with employers to integrate pet telehealth as a workplace benefit, supporting employee wellbeing and reducing lost productivity.
Botika uses AI to revolutionize product photography in the fashion industry, offering a full-stack platform that enables retailers to plan, create, deploy, and optimize high-quality, scalable visual content in real time. Powered by custom foundation models, Botika provides a cost-effective way for fashion brands to generate on-brand imagery for their websites—forming the creative backbone of modern eCommerce.
Who we are
Verissimo Ventures is a Pre-seed and Seed Venture Fund based in Israel and the US. We invest primarily in enterprise software companies and take a fundamentals-driven approach to early-stage investing. We work closely with founders to help them build the strongest, most fundamentally sound businesses with potential for explosive growth and a meaningful impact on the market.
We were founded in 2020 and are currently investing out of our $26M Fund 2.