A classic from Mark Suster on patience and pattern recognition for investors:
The first time I meet you, you are a single data point. A dot. I have no reference point from which to judge whether you were higher on the y-axis 3 months ago or lower. Because I have no observation points from the past, I have no sense for where you will be in the future. Thus, it is very hard to make a commitment to fund you.
For this reason I tell entrepreneurs the following: Meet your potential investors early. Tell them you’re not raising money yet but that you will be in the next 6 months or so. Tell them you really like them so you want them to have an early view (which is what all investor’s want). When you’re with them lower the bar by telling them, “we haven’t shipped product yet, we have lots of decisions still to make, but we’d like to show you our prototype” or obviously if you’re more advanced show what you have and what your roadmap looks like.
Because early-stage investing is such a long relationship game, this view seems obvious. But people still make snap decisions to jump into deals (both investors AND startups) based on who’s hot or who’s trendy, which they have little empirical evidence on performance, grit, commitment to do what they say, and other important data points.
The construction market for startups (one that I’m fairly involved in, but only as a segment of our market) has been a historically tough nut to crack for technology companies.
This is a great breakdown from Brian Potter on the past couple decades of construction startups and funding amounts, with a useful segmentation by category into slices like builders, materials, energy use, construction software, digital twins, and more.
It wasn’t surprising to see builders taking such a huge proportion of the funding — after all, trying to scale a soup-to-nuts homebuilding company is enormously capital-intensive. Management software scoops in an ~8% share, with Procore at the top. This bit hits on one of the challenges I’ve observed anecdotally working with construction companies: a slog to scale within big orgs due to various reasons:
Most VC returns come from a small number of huge successes that end up being worth 10s or 100s of billions (for instance, 65% of the value of YCombinator startups comes from just 5 companies), but construction has yet to see any $10 billion+ startups. Part of this is possibly due to a sort of natural throttling (caused by, among other things, rational risk aversion) that limits how fast even a software company with strong network effects can grow in construction. For instance, at its IPO, Procore estimated that it had captured just 2% of its potential market despite being around for over 15 years and having a category-defining product.
Some of the frictions are common in other markets, but particularly acutein construction — risk aversion, resistance to tech, and fragmented cost centers until you get to enterprise-scale (departments compete for their own revenue/budget, and the company wants to book software expenses as op-ex to a project). Plus the multiparticipant nature of every construction project (a sea of subs and contractors) makes it difficult to go upstream with a single stakeholder buyer.
Arnold Kling has an interesting point this week in reference to decentralized finance. He argues that for DeFi to work, we need folks that understand the moving parts on two complex fronts: crypto and the financial system. Many folks on each side don’t deeply understand the other:
Marvin Ammori understands more than I ever will about decentralized finance (DeFi). Indeed, there are thousands of young techies who understand DeFi better than I do.
But I bet that in order for DeFi to work, you need an understanding of financial institutions in addition to an understanding of blockchain and the layers that have been added to it. I don’t think that young techies understand financial institutions as well as I do. And I think I have a better chance of explaining my knowledge of financial institutions to young techies than they have of explaining DeFi technology to me.
He includes a great reading list at the end, as well.
The web3 side of DeFi needs crypto/finance-bilingual product people that can bring some much-needed usability on-ramps into the system. What DeFi offers in theoretical accessibility to an open financial system is opposed by its practical inaccessibility. The process of getting familiar with wallets, Ethereum addresses, and passphrases is pretty impenetrable, even to the tech-savvy. This is an area where decentralization makes this a hard problem to improve. The best user experiences are on the centralized exchanges like Coinbase and Binance, but those don’t give you the access to the open market liquidity providers or DEXes like Curve or Uniswap.
Alex Danco builds on his excellent post on world-building, this time layering in why antifragility is important when rallying a community:
Here’s the thing, though: your world doesn’t exist in a vacuum; it’s subject to the volatility and unpredictability of the outside world. If you’re trying to create or accomplish anything complex and valuable, you know this lesson all too well: once you set off on a mission to get something done, there is no way you can predict what kind of plot twists or stressors you’ll encounter along the way. Your world is going to face shocks and surprises you can’t foresee.
When you find yourself looking at what others are doing too enviously, it’s good to remember that things aren’t what they seem from the outside. Great piece from Morgan Housel last week:
But it’s always hard to know where anyone sits on that spectrum when they’ve carefully crafted an image of who they are. “The grass is always greener on the side that’s fertilized with bullshit,” the saying goes.
Byrne Hobart wrote this piece in the inaugural edition of a16z’s new publication, Future. On bubbles and their downstream effects:
Bubbles can be directly beneficial, or at least lead to positive spillover effects: The telecom bubble in the ’90s created cheap fiber, and when the world was ready for YouTube, that fiber made it more viable. Even the housing bubble had some upside: It created more housing inventory, and since the new houses were quite standardized, that made it great training data for “iBuying” algorithms — the rare case where the bubble is low-tech but the consequences are higher-tech. But, even so, there’s always the question of price: how can you tell when it’s worth the hype?
There’s something special that happens when you allow your kids to treat hobbies like serious endeavors instead of playtime or games. Paul Graham’s latest:
Instead of telling kids that their treehouses could be on the path to the work they do as adults, we tell them the path goes through school. And unfortunately schoolwork tends be very different from working on projects of one’s own. It’s usually neither a project, nor one’s own. So as school gets more serious, working on projects of one’s own is something that survives, if at all, as a thin thread off to the side.
It’s a bit sad to think of all the high school kids turning their backs on building treehouses and sitting in class dutifully learning about Darwin or Newton to pass some exam, when the work that made Darwin and Newton famous was actually closer in spirit to building treehouses than studying for exams.
My interests in history and tech trace straight back to my time in high school building computers to play Civilization II. Personal projects have long term benefit if nurtured.
On the heels of finishing Schelling’s collection of essays on game theory, I read this piece from Vitalik Buterin on legitimacy, a force that underpins any successful coordination game, of which the world of cryptocurrencies and DAOs are prime examples.
In almost any environment with coordination games that exists for long enough, there inevitably emerge some mechanisms that can choose which decision to take. These mechanisms are powered by an established culture that everyone pays attention to these mechanisms and (usually) does what they say. Each person reasons that because everyone else follows these mechanisms, if they do something different they will only create conflict and suffer, or at least be left in a lonely forked ecosystem all by themselves. If a mechanism successfully has the ability to make these choices, then that mechanism has legitimacy.
This was the first episode I’ve listened to of Patrick O’Shaughnessy’s new podcast “Business Breakdowns”. He and Alex Rampell dive deep on the history of Visa and its unique business model. Alex saw Visa’s business first-hand after his company TrialPay was acquired in 2015.
So much good background here on how it started as a local credit card program in Fresno and evolved into the network backbone between banks.
They also mentioned a book on the history of the credit card (and other financial innovations of the same era) called A Piece of the Action, which sounds super interesting.
This week Stripe launched two new major products in their ever-expanding mission to build the economic and financial backbone for the internet.
Ben Thompson was one of two (along with the Wall Street Journal) to have embargoed early access to their launch of Stripe Treasury, their latest major product category. This interview with Stripe co-founder John Collison dives into the background on the product launches, Stripe’s strategy, and where these fit into the wider Stripe mission.
They’re extending their Capital product, which originally launched in 2019 to give Stripe customers access to capital for running their businesses, to their customers’ customers — as Thompson described: “building a platform of platforms.”
But Treasury is the big deal. It provides what they call “banking-as-a-service”; developers can now embed full financial services into their products, using Stripe’s passthrough platform APIs to generate bank accounts and perform other financial transaction types. The key component here is not only that they’re making it instantaneous to set up financial infrastructure through their banking partner network, but also extending that toolkit to the customers of customers, to allow building financial products on top of the Stripe platform.
John mentions in the interview that they’ve been describing this intent for years, calling the company a “payments and treasury network.” I guess we shouldn’t be surprised that they meant what they said, even though it sounded absurdly ambitious at the time. Don’t underestimate Stripe.
Arnold Kling has been a great follow lately. On the Fed’s stimulus plan for COVID economic shutdown:
I have said all along that the checks being written to households and small businesses were just a fig leaf to cover a massive bailout of large corporations and the financial industry.
If we saw mobs breaking into stores, pulling items from the shelves, and walking out, we would recognize this as looting. But if we define looting as taking property without giving anything of value in return, then it is now widespread.
Tenants are looting landlords by not paying rent and not getting evicted.
Borrowers are looting banks by not paying mortgages or credit card debt.
Shareholders of airlines are looting the rest of us by getting bailout money.
The financial industry is looting us by getting bailout money from the Fed.
The topic of funding has been kicking around with the coronavirus. Fastgrants launched a few weeks ago and has already awarded grants to 97 different research proposals.
Roots of Progress breaks down various funding methods that have powered scientific research.
A great piece from the Atlantic’s George Packer, a transcript of his acceptance speech for the Hitchens Prize.
At a moment when democracy is under siege around the world, these scenes from our literary life sound pretty trivial. But if writers are afraid of the sound of their own voice, then honest, clear, original work is not going to flourish, and without it, the politicians and tech moguls and TV demagogues have less to worry about. It doesn’t matter if you hold impeccable views, or which side of the political divide you’re on: Fear breeds self-censorship, and self-censorship is more insidious than the state-imposed kind, because it’s a surer way of killing the impulse to think, which requires an unfettered mind. A writer can still write while hiding from the thought police. But a writer who carries the thought police around in his head, who always feels compelled to ask: Can I say this? Do I have a right? Is my terminology correct? Will my allies get angry? Will it help my enemies? Could it get me ratioed on Twitter?—that writer’s words will soon become lifeless. A writer who’s afraid to tell people what they don’t want to hear has chosen the wrong trade.
It might seem obvious that savings is your ability to reject what you could spend. But the majority of financial goals are about earning more – better investment returns and a higher-paying career. There’s nothing wrong with that. Earning more is wonderful, just like exercise. We just shouldn’t lose sight of the fact that earning more will do little for building wealth if every extra dollar is offset by a dollar of new spending.
The world is filled with the financial equivalent of athletes who finish every workout with four Big Macs. Wealth, at every income level, has less to do with your gains and more to do with your ability to leave gains alone without cashing them in.
An interesting response argument to Kevin Kwok’s post from a while back called the Arc of Collaboration. The meat of the argument is that corralling notifications from the dozens of input streams we all have is challenging, and that a “command line”-style interface like Superhuman’s could function as a filter point to visualize the input stream, but also engage with items in real time. A compelling case with mockups of how it could work (if service providers wanted to plug into this sort of “notification nexus”).
Earlier this year at SaaStr Annual, we spent 3 days with 20,000 people in the SaaS market, hearing about best practices from the best in the business, from all over the world.
If I had to take away a single overarching theme this year (not by any means “new” this time around, but louder and present in more of the sessions), it’s the value of customer success and retention of core, high-value customers. It’s always been one of SaaStr founder Jason Lemkin’s core focus areas in his literature about how to “get to $10M, $50M, $100M” in revenue, and interwoven in many sessions were topics and questions relevant to things in this area — onboarding, “aha moments,” retention, growth, community development, and continued incremental product value increases through enhancement and new features.
Mark Roberge (former CRO of Hubspot) had an interesting talk that covered this topic. In it he focused on the power of retention and how to think about it tactically at different stages in the revenue growth cycle.
If you look at growth (adding new revenue) and retention (keeping and/or growing existing revenue) as two axes on a chart of overall growth, a couple of broad options present themselves to get the curve arrow up and to the right:
If you have awesome retention, you have to figure out adding new business. If you’re adding new customers like crazy but have trouble with customer churn, you have to figure out how to keep them. Roberge summed up his position after years of working with companies:
It’s easier to accelerate growth with world class retention than fix retention while maintaining rapid growth.
The literature across industries is also in agreement on this. There’s an adage in business that it’s “cheaper to keep a customer than to acquire a new one.” But to me there’s more to this notion than the avoidance of the acquisition cost for a new customer, though that’s certainly beneficial. Rather it’s the maximization of the magic SaaS metric: LTV (lifetime value). If a subscription customer never leaves, their revenue keeps growing ad infinitum. This is the sort of efficiency ever SaaS company is striving for — to maximize fixed investments over the long term. It’s why investors are valuing SaaS businesses at 10x revenue these days. But you can’t get there without unlocking the right product-market fit to switch on this kind of retention and growth.
So Roberge recommends keying in on this factor. One of the key first steps in establishing a strong position with any customer is to have a clear definition of when they cross a product fit threshold — when they reach the “aha” moment and see the value for themselves. He calls this the “customer success leading indicator”, and explains that all companies should develop a metric or set of metrics that indicates when customers cross this mark. Some examples from around the SaaS universe of how companies are measuring this:
Slack — 2000 team messages sent
Dropbox — 1 file added to 1 folder on 1 device
Hubspot — Using 5 of 20 features within 60 days
Each of these companies has correlated these figures with strong customer fits. When these targets are hit, there’s a high likelihood that a customer will convert, stick around, and even expand. It’s important that the selected indicator be clear and consistent between customers and meet some core criteria:
Observable in weeks or months, not quarters or years — need to see rapid feedback on performance.
Measurement can be automated — again, need to see this performance on a rolling basis.
Ideally correlated to the product core value proposition — don’t pick things that are “measurable” but don’t line up with our expectations of “proper use.” For example, in Fulcrum, whether the customer creates an offline map layer wouldn’t correlate strongly with the core value proposition (in isolation).
Repeat purchase, referral, setup, usage, ROI are all common (revenue usually a mistake — it’s a lagging rather than a leading indicator)
Okay to combine multiple metrics — derived “aggregate” numbers would work, as long as they aren’t overcomplicated.
The next step is to understand what portion of new customers reach this target (ideally all customers reach it) and when, then measure by cohort group. Putting together cohort analyses allows you to chart the data over time, and make iterative changes to early onboarding, product features, training, and overall customer success strategy to turn the cohorts from “red” to “green”.
We do cohort tracking already, but it’d be hugely beneficial to analyze and articulate this through a filter of a key customer success metric is and track it as closely as MRR. I think a hybrid reporting mechanism that tracks MRR, customer success metric achievement, and NPS by cohort would show strong correlation between each. The customer success metric can serve as an early signal of customer “activation” and, therefore, future growth potential.
I also sat in on a session with Tom Tunguz, VC from RedPoint Ventures, who presented on a survey they had conducted with almost 600 different business SaaS companies across a diverse base of categories. The data demonstrated a number of interesting points, particularly on the topic of retention. Two of the categories touched on were logo retention and net dollar retention (NDR). More than a third of the companies surveyed retain 90+% of their logos year over year. My favorite piece of data showed that larger customers churn less — the higher products go up market, the better the retention gets. This might sound counterintuitive on the surface, but as Tunguz pointed out in his talk, it makes sense when you think about the buying process in large vs. small organizations. Larger customers are more likely to have more rigid, careful buying processes (as anyone doing enterprise sales is well aware) than small ones, which are more likely to buy things “on the fly” and also invest less time and energy in their vendors’ products. The investment poured in by an enterprise customer makes them averse to switching products once on board1:
On the subject of NDR, Tunguz reports that the tendency toward expansion scales with company size, as well. In the body of customers surveyed, those that focus on the mid-market and enterprise tiers report higher average NDR than SMB. This aligns with the logic above on logo retention, but there’s also the added factor that enterprises have more room to go higher than those on the SMB end of the continuum. The higher overall headcount in an enterprise leaves a higher ceiling for a vendor to capture:
Overall, there are two big takeaways to worth bringing home and incorporating:
Create (and subsequently monitor) a universal “customer success indicator” that gives a barometer for measuring the “time to value” for new customers, and segment accordingly by size, industry, and other variables.
Focus on large Enterprise organizations — particularly their use cases, friction points to expansion, and customer success attention.
We’ve made good headway a lot of these findings with our Enterprise product tier for Fulcrum, along with the sales and marketing processes to get it out there. What’s encouraging about these presentations is that we already see numbers leaning in this direction, aligning with the “best practices” each of these guys presented — strong logo retention and north of 100% NDR. We’ve got some other tactics in the pipeline, as well as product capabilities, that we’re hoping bring even greater efficiency, along with the requisite additional value to our customers.
Assuming there’s tight product-market fit, and you aren’t selling them shelfware! ↩
Some interesting data on the current state of public SaaS company performance:
SaaS multiples look steady: of the 82 SaaS companies we follow, the average public SaaS business is trading at 10.03x revenue while the median is 7.72x. Interestingly, the gap between the average and median has never been larger for the time period shown, meaning more attractive SaaS companies are being rewarded with big premiums.
While valuations aren’t everything when it comes to company health (the calculus for valuation can change quickly), recurring revenue is still an amazing thing if you build a company with attractive unit economics. Predictability is highly valued!
