There’s a notion in the venture market that LPs typically dislike GPs writing discovery checks. Though I’ve written about VCs writing more discovery checks (here and here) in the past two years, discovery checks have often been a function of investor FOMO (fear of missing out) and not playing their core game. The returns of any established fund are largely realized on big checks with ownership targets.
Of course, rolling funds, micro-VCs, and angels optimize for a different game. They’re spreading their net thinner, but also leveraging their relationships to get into oversubscribed rounds or putting really small bets into hopefuls. Proportionally speaking, if they make bad bets, they lose the same percentage of money, but on an absolute dollar amount, they lose far less. And, well, it’s much easier to return a $1M fund than a $100M fund. It’s also far less committal for LPs to invest in a small fund than a big fund intended to make their incredible returns. The small fund is the bet. The large fund for an LP is the money-making machine.
I was talking with a Venture Partner of a name-brand accelerator yesterday, and he offered a second perspective.
The reason discovery checks by larger funds don’t make any money is because it’s irregular and inconsistent. There often is no fund strategy behind it. That said, if you make discovery checks your core business, that means a fundamentally different strategy. Is that strategy consistent, predictable, and scalable? For accelerators, they’ve made writing discovery checks part of their fund strategy. Their game, at the end of the day, is “buying options.”
It’s a call option. Accelerators invest $100K for 5-10% to buy the rights for the next round. The money is being made in the follow-on, not on the initial bet. And if there’s a fund strategy to deploy 100 checks of a $100K, there’s a systematic approach to writing discovery checks. This is why many accelerators include a provision for pro rata of $0.5-1M in a future round. And they’re unwilling to budge on that, even if a founder comes back and wants to seed that allocation to downstream investors.
Why would an entrepreneur take the $100K that comes with the $500K-$1M option down the road? Accelerators and a lot of angel funds out there are willing to write you, the founder, the check faster and with less debate than other investors on the market.
There’s also a reason many accelerators focus on software rather than other potential areas of investment. A $100K check will get you much further for an asset-lite software company than a deep tech or hardware company. The same amount of cash can bring a software company to market, while a hardware company stays in R&D.
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Over the past decade, stretching its roots to the dot-com boom, there have been more dialogue and literature around entrepreneurship. In a sense, founding a business is easier than it’s ever been. But like all things in life, there’s a bit more nuance to it. So, what’s the state of startups right now?
Lower Barriers to Entry
A number of factors have promoted such a trend:
There are an increasing number of resources online and offline. Online courses and ed-tech platforms. Fellowships and acceleration/incubation programs. Investor office hours and founder talks. YouTube videos, online newsletters, and podcasts.
The low-code/no-code movement is also helping bridge that knowledge gap for the average person. Moreover, making it easier for non-experts to be experts.
The gig economy have created a fascinating space for solopreneurship to be more accessible to more geographies.
Demand (by consumers and investors) fuels supply of startups, through knowledge and resource sharing. Likewise, the supply of startups, especially in nascent markets, fuels demand in new verticals. So, the ecosystem becomes self-perpetuating on a positive feedback loop. As Jim Barksdale, former Netscape CEO, once said:
“There are only two ways I know of to make money – bundling and unbundling.”
Bundling
Unbundling
Market Maturity
Market Nascency
Horizontalization
Verticalization
Breadth
Depth
Execution Risk Bias
Market/Tech Risk Bias
Right now, we’re at a stage of startup market nascency, unbundling the knowledge gap between the great and the average founder. This might seem counter-intuitive. After all, there’s so much discourse on the subject. There’s a good chance that you know someone who is or have thought about starting a business. But, I don’t believe we’re even close to a global maximum in entrepreneurship. Why?
Valuations are still on the rise. Six years back, $250K was enough runway for our business to last until product-market fit. Now, a typical seed round ranges from $500K-$2M. A decade ago, $500M was enough to IPO with; now it only warrants a late-stage funding round. By capitalistic economic theory, when a market reaches saturation, aka perfect competition, profit margins regress to zero. Not only are there still profits to be made, but more people are jumping into the investing side of the business.
Yes, increasing valuations are also a function of FOMO (fear of missing out), discovery checks (<0.5% of VC fund size), super duper low interest rates (causing massive sums of capital to surge in chase yields), and non-traditional venture investors entering as players in the game (PE, hedge funds, other accredited investors, (equity) crowdfunding platforms). It would be one thing if they came and left as a result of a (near) zero sum game. But they’re here to stay. Here’s a mini case study. Even after the 2018 drop in Bitcoin, venture investors are still bullish on its potential. In fact, there are now more and more specialized funds to invest in cryptocurrency and blockchain technology. Last year, a16z, one of the largest and trendsetting VC players, switched from a VC to an RIA (registered investment advisor), to broaden its scope into crypto/blockchain.
Great founders are scarce
“The only uncrowded market is great. There’s always a fucking market for great.”
– Tim Ferriss, podcaster, author, but also notably, an investor and advisor for companies, like Facebook, Uber, Automattic and more
Even if founders now have the tools to do so, it doesn’t mean they’ll hit their ambitious milestones. For VCs, it only gets harder to discern the signal from the noise. Fundamentally, there’s a significant knowledge delta – a permutation of misinformation and resource misallocation – in the market between founders and investors, and between average founders and great founders.
The Culinary Analogy
Here’s an analogy. 30 years prior, food media was still nascent. Food Network had yet to be founded in 1993. The average cook resorted to grandma’s recipe (and maybe also Cory’s from across the street). There was quite a bit of variability into the quality of most home-cooked dishes. And most professional chefs were characteristically male. Fast forward to now, food media has become more prevalent in society. I can jump on to Food Network or YouTube any time to learn recipes and cooking tips. Recipes are easily searchable online. Pro chefs, like Gordon Ramsay, Thomas Keller, and Alice Waters, teach full courses on Masterclass, covering every range of the culinary arts.
Has it made the average cook more knowledgeable? Yes. I have friends who are talking about how long a meat should sous vide for before searing or the ratio of egg whites to egg yolks in pasta. Not gonna lie; I love it! I’ll probably end up posting a post soon on what I learned from culinary mentors, friends, and myself soon.
Is there still a disparity between the average cook and a world-class chef? Hell ya! Realistically I won’t ever amount to Wolfgang Puck or Grant Achatz, but I do know that I shouldn’t deep fry with extra virgin olive oil (EVOO) ’cause of its low smoke point.
Great businesses are scarcer
The same is true for entrepreneurship. There are definitely more startups out there, but there hasn’t been a significant shift in the number of great startups. And the increase in business tools has arguably increased the difficulty to find business/product defensibility. It’s leveled the playing field and, simultaneously, raised the bar. So yes, it’s easier to start a business; it’s much harder to retain and scale a business.
It’s no longer enough to have an open/closed beta with just an MVP. What startups need now is an MLP (minimum lovable product). Let’s take the consumer app market as an example.
The Consumer App Conundrum
Acquiring consumers has gotten comparatively easier. Paid growth, virality, and SEO tactics are scalable with capital. More and more of the population have been conditioned to notice and try new products and trends, partly as a function of the influencer economy. But retaining them is a different story.
So, consumers have become:
More expensive to acquire than ever before. Not only are customer acquisition costs (CAC) increasing, with smaller lifetime values (LTV), but your biggest competitors are often not directly in your sector. Netflix and YouTube has created a culture of binge-watching that previously never existed. And since every person has a finite 24 hours in a day, your startup growth is directly cutting into another business’s market share on a consumer’s time.
And, harder to retain. It’s great that there’s a wide range of consumer apps out there right now. The App Store and Play Store are more populated than they’ve ever been. But churn has also higher now than I’ve seen before. Although adoption curves have been climbing, reactivation and engagement curves often fall short of expectations, while inactive curves in most startups climb sooner than anticipated. Many early stage ventures I see have decent total account numbers (10-30K, depending on the stage), but a mere 10-15% DAU/MAU (assuming this is a core metric). In fact, many consumers don’t even use the app they downloaded on Day 2.
Luckily, this whole startup battlefield works in favor of consumers. More competition, better features, better prices. 🙂
So… what happens now?
It comes down to two main questions for early-stage founders:
Do you have a predictable/sensible plan to your next milestone? To scalability?
Are you optimizing for adoption, as well as retention and engagement?
With so many tools for acquisition hacks, growth is relatively easy to capture. Retention and engagement aren’t. And in engagement, outside of purely measuring for frequency (i.e. DAU/MAU), are you also measuring on time spent with each product interaction?
How are you going to capture network effects? What’s sticky?
Viral loops occur when there’s already a baseline of engagement. So how do you meaningfully optimize for engagement?
From a bottom-up approach (rather than top-down by taking percentages of the larger market), how are you going to convert your customers?
How do you measure product-market fit?
What meaningful metric are you measuring/optimizing?
Why is it important?
What do you know (that makes money) that everyone else is either overlooking or severely underestimating?
What are you optimizing for that others’ (especially your biggest competitors) cannot?
Every business optimizes for certain metrics. That have a set budget used to optimize for those metrics. And because of that, they are unable to prioritize optimizing others. So, can you measure it better in a way that’ll hold off competition until you reach network effects/virality?
Building a scalable business is definitely harder. And to become the 10 startups a year that really matter is even more so. By the numbers, less likely than lightning striking you. In my opinion, that just makes trying to find your secret sauce all the more exciting!
If you think you got it or are close to getting it, I’d love to chat!
Founders take on many different types of risk when creating a business. Subsequently, investors constantly put founders and their businesses under scrutiny using risk as a benchmark. In broad terms, in my experience, they largely fall under two categories: execution risk and market risk.
Where I first introduced the dichotomy of market and execution risk in the frame of idea-market fit.
Some Background
Contrary to popular belief, VCs are some of the most risk-averse people that I know. As an investor, the two goals are to:
Take calculated bets, via an investment thesis and diligence;
And de-risk each investment as much as possible.
From private equity to growth equity to venture capital, more and more investors are writing ‘discovery checks.’ Typically, funds write checks that are 2-4% of their fund size. For example, $100M fund usually write $2-4M initial checks. Yet, more and more investors are writing increasingly smaller check sizes (0.1-0.5% fund size). In the $100M fund example, that’s $100-500K checks. This result is a function of FOMO (fear of missing out), as well as a proving grounds for founders before the fund’s partners put in their core dollar. Admittedly, this upstream effect does lead to:
Less diligence before checks are written (closing within 48-72 hours on the extreme end, and inevitably, more buyer’s remorse);
Less bandwidth allotted per portfolio startup (even less for startups given discovery checks);
The risks for a startup investor are fairly obvious, and so are the rewards. Effectively, an early-stage investor is betting millions of dollars on a stranger’s claim. But not all risks are the same.
In the eyes of a VC, an execution risk is categorically less risky than a market risk. Furthermore, even within the category of execution, a product risk is usually less risky than a team risk.
Execution Risk
Why are more and more early-stage investors defaulting to enterprise over consumer startups?
Two reasons.
Enterprise startups often run on a SaaS (software-as-service) subscription business model. There will always be recurring revenue, assuming the product makes sense. For an investor, that’s foreseeable ROI.
It’s an execution risk, not a market risk. Often times, an enterprise tech startup is the culmination of existing frustrations prevalent in the respective industry already. And therefore, have reasonably stable distribution channels and go-to-market strategies.
Using discovery checks, and playing pre-core business, VCs can evaluate team risk. Between the discovery check and their usual ‘core checks’, VCs can also test their initial hypotheses on their founders.
As a startup grows, especially after realizing product-market fit, market risk becomes more of a product risk. Best illustrated by market share, product risk is when a product fails to meet the expectations of their (target) customers. It can be evaluated via a permutation of key metrics, like unit economics, NPS, retention and churn rate. There is an element of technological risk early on in the startup lifecycle for deep tech ventures, but admittedly, it’s not a vertical I have my finger on the pulse for and can share insight into.
Given that VCs are either ex-operators or have seen a breadth of startup life-cycles, VCs can best use their experience to mitigate a startup’s execution risk.
Market Risk
Market risk requires a prediction of human/market behavior. And unfortunately, the vast majority of investors can predict about the constant evolution of human behavior as well as a founder can. What does that mean? Founders and VCs are walking hand-in-hand to gain market experience. It, quite excitingly, is an innovator’s Rubrik’s cube to solve.
Market risk is frequently attributed to consumer tech products. In an increasing proliferation of consumer startups, consumers have become more expensive to acquire and harder to retain. Distribution channels change frequently and are determined by political, economic, technological, and social trends.
In Closing
Every VC specializes in tackling a certain kind of risk. But founders must quickly adapt, prioritize, and tackle all the above risks at some point in the founding journey. As Reid Hoffman, co-founder of LinkedIn, famously said:
“An entrepreneur is someone who will jump off a cliff and assemble an airplane on the way down.”
