C2V April Notes From The Trenches
Welcome Friends! We have a lot of great content this month, including a new (fintech) portfolio company to introduce and a bunch of exciting portfolio news and media appearances to share. But first, we take a harder look at one of those pervasive venture axioms that everyone seems to just take on faith, in an effort to determine just how wise this particular piece of conventional wisdom is, calling once again on the indispensable help of our erstwhile friend and ally… math.
We expect every industry to have at least a few of these widely (and blindly) accepted pieces of conventional wisdom, but few, if any, have anywhere near as many as the venture/startup world. We’re not entirely sure where these things come from: why there are so many, how they end up being defended with such religious zeal (and similar reticence among defenders to get too far into the details/logic behind them), but they’re everywhere.
To be fair, most are generally on solid logical footing (if often oversimplified), but sometimes the emperor’s just standing there stark naked while everyone wanders past, oblivious, and someone has to point this out, right?
It’s not that we seek to be contrarian just for the sake of being contrarian, but as you’ve surely gathered by now:
We’re not big on blindly following advice (especially of the “because that’s how it’s done” variety) without doing our own homework;
We’re particularly skeptical of any advice that’s meant to be applied broadly, but delivered within the space of a single tweet; and
When it comes to maximizing fund returns in particular, we do find math to be a more useful tool than “important people” tweets.
That said, if a particular piece of generic market wisdom holds up to scrutiny, great, consider us converted, but if it doesn’t… well, that’s why you ask these questions in the first place.
So, while we all continue to enjoy the irony of the name “Stability AI”…
The Fallacy of “Maintaining Ownership”
Among this smaller group of venture axioms on shakier logical ground, this one may have been on our radar the longest, going back to a 2019 conversation with an institutional investor who scoffed at our follow-on investment strategy telling us — with the kind of unequivocal conviction that only this type of person can muster (you other VCs know the type we’re talking about) — “You’ll never generate returns if you can’t maintain ownership all the way to exit.”
This wasn’t the first time we’d heard this, of course, just the first time we’d been scolded for not blindly falling in line with it. The concept was really coming into vogue at that time,1 used as the primary justification for the launch of hundreds of “opportunity” (i.e., “follow-on”) funds, as well as a new (and much bigger) wave of gigantic, super late-stage funds. Having done enough research to see (at least what we believe to be) the flaws in the logic, we had previously just ignored all of this, but given the source this time, we did stop to reconsider it, and here’s what we found.
The Math
(Author’s Note: In order to thread the transparency/brevity needle, we’re putting most of the underlying assumptions used below in footnotes. These are much easier to navigate in the app or browser version (vs. email), so if you find yourself jumping back and forth a lot, we’d highly recommend you click “Read In-App” in the byline above and enjoy this content there).
For all examples, we’re using the following assumptions (unless otherwise noted):
A $75mm early-stage fund with fairly common construction parameters, including a 50/50 split between funds allocated for first checks and follow-ons (see footnote for additional details)2
Industry average round sizes and valuations from late 2021, as reported by the Carta Data Minute.
Rounds considered here start with Seed, end with Series E,3 and include one bridge round between Seed and A (something so common in recent years, it probably deserves its own name by now).
Average and median exit sizes referenced are trailing 5-year averages, per the Pitchbook-NVCA Venture Monitor.45
The 10 companies that did not receive follow-on money each returned 0 - 1x and unless otherwise specified, the other 10 exited at the industry average valuation.
All exiting companies raise through Series E (this is way too generous to the “maintain ownership” camp, but we’re keeping it this way for simplicity)6
Scenario 1 (Control Group)
This is the vanilla version where follow-on money is allocated pro-rata in each funding round until each company’s share of the follow-on pool is expended.
This should look more or less as expected. The dilution is fairly high but remember, we’re assuming every exiting company raises all the way through Series E, so in that context, it’s actually not that bad.
At 2.9x, the net return to LPs is a bit above the industry average, and the 21.4% annual return is more than double the long-term average for public equity markets (early-stage venture, baby!).
Scenario 2 (Ownership Maintenance in Action)
Here we assume that the fund continues investing pro rata in each round (up to a maximum of 10% of the fund) in 3 of its companies (its “winners” in the common parlance… assuming these are actually the winners; more on that below). Why only 3? Because there isn’t enough follow-on cash left to do more (a definite hole in the strategy, but more on that below).7
Starting with the ownership improvement for the 3 companies in which the fund did extra follow-on rounds (5.8% vs 5.0%): the 10% dilution improvement may sound impactful in isolation, but that extra ownership stake only adds 0.1x DPI (+1.5% annually) for every $1B of exit value for each of these companies.
How is this possible when you’re committing almost twice as much capital to these companies? That extra capital is being invested at a 4x higher valuation than all of the prior capital combined (a weighted average of $360mm vs $90mm for all of the preceding capital). Furthermore, that $360mm number is only 20% below the longer-term average exit value. It begs the question, when you’re putting this much of your capital to work at these kinds of numbers, are you really even running an early-stage fund anymore?
But the real headline here is that if the 3 super-follow-on companies don’t outperform (by quite a bit), this strategy actually produces a worse return than the standard, vanilla version. This is because the continuous follow-on strategy uses up so much capital that it reduces the ownership share at exit for the 7 other companies in this cohort by a similar amount (4.0% vs. 5.0%).
But what if you nail it and the three companies in which you prioritized ownership maintenance each exit for $2.5 billion?
Well, at a net 6.2x return, you’re maybe not quite at “industry legend” status, but you’ll never buy a drink in the company of one of your LPs again and if you immediately launched a new $500mm Mars colonization tech fund it would probably oversubscribe in a couple of months.
But what if the vanilla strategy fund also has three $2.5B exits?
Well, it is a lower return, but at these levels, 0.6% per year is basically a rounding error, and here’s the more important thing — the fund that went all-in on 3 companies had to nail all 3 perfectly, the fund using the vanilla strategy only had to go 3 for 10. Would you pay 0.6% per year for that big an increase in margin for error? You should because, let’s say, these 3 super-follow-on companies only end up exiting for $200mm each…
See what we mean (and it can certainly get a lot worse than 3 x $200mm)?
Scenario 3 (Getting in While the Getting’s Good)
So, what if we lean into this newfound wisdom (both what we learned above and the true magic of early-stage investing itself)? Let’s say a fund decides that 1) carefully selected bridge rounds represent a great opportunity to materially increase ownership8 , and 2) they want to be done allocating follow-on money by Series A, before the potentially huge valuation jump that high-performers often see at Series B (we might even know an intrepid venture manager who has chosen to go this exact route)...
For simplicity’s sake, we’re assuming that the fund would allocate a third of its follow-on reserve to bridge rounds and invest the balance at Series A:
Obviously, what jumps out here is the overall returns — not only a huge jump over the prior examples (4.1x vs 2.7x/2.9x), but now a top quartile performer, even without any big outlier exits (and if this fund hits the big $2.5B x 3 scenarios, DPI jumps to 8x).
But what’s really notable here is the ownership at exit. Despite sitting out a full four subsequent funding rounds, this fund still ended up with by far the lowest net dilution (relative to its initial stake) and largest share at exit (6.8% vs even the 5.8% for the subset of super-follow-on companies in Scenario 2).
As with the prior example, this comes down to valuation. While the fund in Scenario 2 invested at a weighted average of $180mm in its three super-sized positions (and Scenario 1 paid $80mm for each follow-on company), this fund invested in all 10 of its follow-on companies at a weighted average of only $38mm.
This is the real takeaway here: focusing only on ownership is akin to treating a symptom without understanding what’s causing it in the first place. Buying into good companies at attractive/defensible valuations is what actually drives returns. The rest is just window dressing.
Venture myth busted… er, dispelled (let’s not get ourselves sued here).
New Investment
We’re pleased to announce our latest investment in our pre-seed, Tributary Fund, Gratify, a new entrant into the booming buy now pay later (“BNPL”) market.
We can understand readers wondering at this point if we are chasing a market that’s already peaked, given both the pervasiveness of BNPL offers at checkout for large e-commerce retailers and years of seemingly daily headlines announcing a massive funding round for market heavyweights, Affirm and Klarna (of note, this is barely an exaggeration: between the two, they raised $5.4 billion over 30 fundings rounds and from 2019 - 2021, one of the two closed a funding round every 2 months, on average). In fact, BNPL has barely scratched the surface, accounting for only 6% of US purchases in 2022, and some estimates have the market growing by more than 6x over the next decade.
Of course, we are not simply jumping into just any old boat, trying to catch a rising tide (how’s that for butchering an aphorism?). Gratify’s platform has several important advancements, including a proprietary credit underwriting model with new, innovative methods of weeding out higher default-risk consumers (e.g., detecting potential consumer credit issues that fall outside of credit bureau reporting), as well as a proprietary ID verification and fraud detection model that has proven so effective, the company’s merchant and payment processor customers are starting to ask if they can license it as a standalone product.
But the biggest features of Gratify’s platform that we believe will be a critical growth driver are its non-captive payments and consumer data structure. The current BNPL market leaders’ economic models are actually not driven by lending, they’re driven by payment processing fees and consumer data monetization (if you’ve ever wondered how they can offer so many zero-interest options at checkout, this is your answer). While this is unquestionably an effective way to generate revenues, it puts BNPL providers in direct competition with both existing payment processors and their own customers (the merchants themselves).
As a result, incumbents’ business acquisition cost models are very high (hence the $5.5 billion and counting of cash burn), having to market directly to individual e-commerce merchants (and that’s while targeting only the largest merchants), and leave themselves vulnerable to switching if (when?) merchants tire of losing control of large swaths of their customer data. On the other hand, Gratify’s processor-friendly offering allows them to partner with these companies, giving them instant access to tens of thousands of merchants per processor, and providing important protection for the processors that they will be reticent to ever relinquish at the same time.
C2V Watercooler
PrimeTimeVC is headlining TechDay 2024
Highlighting 4 Venture Capitalists going head to head debating startup growth strategies, investment thesis, and recent tech news.... while founders will vote them off the stage and crown one winning VC!
Your admission to PrimeTimeVC also gives you full-day access to TechDay from 10 a.m.! Just show your PrimeTimeVC pass at registration to get full access to their 10th anniversary live event!
Featuring Defending Champion Zehra Naqvi, Investor at Headline Ventures, along with former PrimeTime Champions Chris Cunningham GP at C2 Ventures, and Mac Conwell, Founder & Managing Partner of Rare Breed Ventures!
Register for the event here.
Chris shared some thoughts and founder advice on being selective when choosing investors. While a big-name investor can be tempting, it is better to focus on finding partners (maybe boutique firms) with a strategic fit.
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Along with its corollary about how “the best venture managers” indiscriminately pile onto their “winners” in every funding round (without letting the details of any particular round get in the way, of course)
We’re assuming: A) no reinvestment of exit proceeds, so 78% of total commitments are investable capital (the rest goes to management fees and expenses), B) 50% allocation to first checks; 50% to follow-ons, C) 20 companies with identically sized initial investments, D) initial investments all made at Seed stage, E) 10 companies in which the fund participates in follow-on rounds and 10 in which it is one and done.
Although our case gets only gets stronger the further into the alphabet you go.
If anyone tries to argue to you that valuations they were handing out in 2021 were based on 2021 exit stats, well, we don’t really know what to say. Just end the call and look for a VC with better judgement.
We adjusted average exit values to account for the outsized impact of a handful of outliers each year, as you can’t really base your fund strategy on the assumption that you’ll be one of the 0.1% of VCs who (for example) were in Uber in 2018, which, by itself, accounted for 28% of the total exit value (as reported in the Venture Monitor) for that year.
We have believed that the majority of Series D and E rounds (at least for SaaS companies) are much more signs of unsustainable and unscalable business models than they are signs of actual progress, but this is a topic for another newsletter… that we already wrote…
Similarly, we capped this strategy at 10% of the fund per company because 3 of these (out of 20) is already a little light/highly concentrated.
It’s important to note here that not all post-Seed bridge rounds are created equal. In some cases, you may have a company executing on a pivot and in some ways, almost raising a Seed round do-over. In others, you may see a company firing on all cylinders and simply looking to extend runway in order to maximize Series A valuation and get that round closed as quickly as possible. The latter are the ones we’re talking about here.