April 15, 2021
News

Announcing our Series B: The DNA Markers of Category Kings and Queens

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Typically, when startups issue blog posts about their funding rounds, they follow a standard template which talks about their perspective of the financing; one which often omits the perspective of their investors and the basis for their investment.

I’d like to try and summarize the investment thesis for TetraScience, since it has profound implications for all of our stakeholders – customers, partners, employees, investors, and humanity as a whole.

The following is a composite analysis which includes my own decision criteria as an investor, as my fund - Impetus Ventures - invested in the Series A just a few months ago.

A Venture Primer: Category Kings and Queens and Tech Economics

Category Kings and Queens dominate in the winner-take-all world of tech economics in which they capture virtually all of a market's mindshare, market share, margin, and market capitalization. Simply put, to the category victor belong the category spoils. Or, in the inimitable words of Ricky Bobby, “If you ain't first, you're last. You know, you know what I'm talking about?”

These market leaders don’t dominate based upon a single distinguishing attribute (e.g., best product), but rather by strategically defining and perfectly aligning their category, product, organization, and ecosystem in furtherance of their category strategy. When executed properly, and in complete harmony, these integrated components generate powerful self-reinforcing value loops and enable the category leader to raise the most capital, attract the greatest and largest talent pools, build the best products, aggregate the most partners, and deliver more value – faster – to its ecosystem, than any potential competitor.

These Kings and Queens are very clever in developing platforms, and sometimes networks, which serve as rocket fuel, driving non-linear growth, resulting in increasing returns to scale and insurmountable competitive moats.

Lastly, and most importantly, by harnessing and harmonizing these components, these Kings and Queens quickly evolve from being technology vendors to leaders of industry movements. The reference example in this regard is Salesforce. While it’s certainly a leading vendor within the CRM market, the real legacy and impact of Salesforce was its pivotal role in inspiring a generational movement to SaaS and the cloud. That category leadership also unsurprisingly led to their dominance within CRM. Ultimately, Category Kings and Queens create abundance for all ecosystem participants, including themselves, whereas subscale tech vendors live or die in a world of zero-sum transactional outcomes.

DNA markers of Category Kings and Queens

Pattern recognition is a primary tool of venture capitalists as it enables them to efficiently sift through thousands of investment opportunities per year. There are consistent “DNA markers” of Category Kings and Queens which VCs screen for and once they recognize them, they pursue those startups with uncommon energy. No group understands the power of Category Kings and Queens better than VCs, as they rely on power law distribution economics to generate their returns. Simply put, they only make real money for their limited partners and themselves if they’re able to back the Category Kings and Queens of tomorrow which generate nearly all of their returns.

Clarity and Simplicity  

Unlike me-too vendors, Category Kings and Queens have to contend with many moving parts in building out the category and engendering a movement around them. Orchestrating a category, product roadmap, organization, and ecosystem concurrently is no small logistical feat and requires complete obsession with clarity – strategic clarity, financial clarity, operational clarity, and cultural clarity – to ensure every single stakeholder is speaking the same language and singing from the same hymn sheet.

Investors who ask a startup for their “elevator pitch” are neither impatient nor unreasonable. They’re simply testing startups to determine if they have perfect clarity into who they are, what they do, why it matters, and why it’s different. If they cannot succinctly and consistently convey this, everything downstream – the company’s culture, operations, customer interactions, etc. – is likely a dumpster fire.

Even when startups are discovering greenfields and breaking new product ground, investors want to understand comparable companies and business models to help them analyze the potential shape of the business and inform their valuation assessment. They like to see plausible comps and simple taglines.

At TetraScience, we are maniacally obsessed with clarity on all dimensions. There is no e-staff session, all-hands meeting, or company activity which we undertake in which we don’t tie everything back to our North Star mission, values, and metrics.

Explaining why we exist, who we are, and why it matters is easy:

  • The world’s R&D labs, in vital industries such as life sciences, chemicals, agricultural, materials, and energy, are upstream to the transformational innovations required to solve humanity’s greatest challenges.
  • TetraScience is the R&D Data Cloud Company.
  • Our mission is to be the most trusted and valuable partner to the world’s scientific community, fueling innovation, facilitating collaboration, accelerating discovery, and enhancing and extending human life.
  • We will accomplish this by delivering the first and only cloud-native and open platform and network which allows us to migrate the world’s experimental data to the Tetra R&D Data Cloud to enable new classes of data applications and position the data for advanced analytics and AI-based discovery.

For investors, knowing that patterns and comps help inform their thesis and valuation, we explain that TetraScience is to Snowflake, as Veeva is to Salesforce - the highly focused vertical domain expert and full stack provider against the backdrop of a horizontal but distracted Gorilla. Like Veeva, TetraScience is expected to emerge as the de facto standard in Life Sciences and then rapidly move into adjacent verticals which possess many of the same lab markers.

Big Markets, Shifts, and Trends, and Information Asymmetry

Not surprisingly, VCs seek out startups which are addressing enormous markets and capitalizing on transformational technology shifts (e.g., cloud, big data, AI) and secular replatforming trends. Venture capitalists face two major challenges in this regard – with $300 billion going into startups annually, once a new technology trend emerges which can galvanize a market replatforming, there’s likely to be scores of startups competing for the same mindshare and market share and hundreds of VCs competing to fund the same companies. An important reminder here – notwithstanding the size of the market, ultimately it will coalesce around a single Category King or Queen. Given the overabundance of venture capital and the scarcity of Kings and Queens, I borrow repeatedly from The Hunger Games when I root on my VC friends - “May the odds be ever in your favor.”

For VCs and founders alike, this means that they need to identify and take advantage of some market information asymmetry. They have to identify the non-obvious market opportunity which today looks less like an opportunity and more like a niche or a startup quagmire of some type. A market that scares away most of their competitors but, with the right platform, team, and go-to-market model, could yield commercial success and lead to ever-larger market expansion opportunities.

Representatively, today, TetraScience resides at the nexus of two of the most important venture capital investment themes – the movement of the world’s data to the cloud, and the application of cloud computing and artificial intelligence to life sciences and other complex experimental data challenges. This would logically lead one to conclude that TetraScience must have scores of competitors and is facing all of the byproducts thereof – long sales cycles, feature/functionality-based RFPs in which most startups are column fodder, commoditized pricing, and more.

Yet, as impossible as it may seem, TetraScience is the world’s only pure-play R&D Data Cloud company, operating unimpeded and without a direct competitor, and is building wide and deep competitive moats which will make it exceedingly difficult for new entrants to compete. In fact, we have yet to see a plausible competitor in 23 months due to our first-mover advantage, best-in-class cloud capabilities, open platform and network, and deep domain data expertise. Our competition isn’t really competition at all and is composed of internal IT and/or systems integrators/body shops, or end-point vendors who dabble in integration but are focused elsewhere.

How is this possible? Well, prior to COVID-19 this market had been overlooked, underfunded, and underdeveloped by venture-backed startups due to a misguided and/or misinformed view that experimental R&D labs represent a niche market and that these advanced labs, which have historically been technology laggards, wouldn’t move their data to the cloud. As such, founders and VCs alike have instead focused on pure-play software-enabled biotech companies and end-point lab applications.

In reality, these labs represent a large, growing, and underserved market. Global R&D labs spend more than $300 billion ($177B in Life Sciences alone) annually on research and development and we estimate that $15 billion of that Life Sciences spend is focused on contending with their data challenges via manifestly suboptimal approaches. When large pharmas do replatform – as they have in commercial activities and clinical trials – it’s yielded Category Kings and Queens such as Veeva and Medidata, with a combined value of >$50B.

Endless and Boundless Expansion Opportunities

Category Kings and Queens optimize for creating abundance in all they do and avoid unnecessary zero sum outcomes. The bigger that they can make the economic and value pie for the entire ecosystem, the more everyone benefits. In turn, the ecosystem reinforces their commitment to the King or Queen as the de facto standard. Companies and markets rely upon these standard bearers every day as they maintain clarity and consistency for all.

At TetraScience, our product, market, and business model vectors yield boundless expansion opps for us and all of our category stakeholders. Our product strategy, market focus, and business model – i.e., open data platform, Life Sciences, and partner network – combine to serve as a strong and leverageable foundation from which to seamlessly expand into logical adjacencies, resulting in accelerating revenue, competitive moats, increasing returns to scale, continuous innovation for our customers, and endless monetization opportunities for our partners.

We define this as the SEVENS strategy – i.e., stack evolution (SE), vertical expansion (VE), and network scale (NS):

  • Our open and cloud native data platform is designed to assemble the largest and most organized experimental data sets in the world. We believe this gives us unparalleled advantages in enabling advanced native and 3rd party data-enabled apps, as well as native and 3rd party AI/ML capabilities, which we envision as the core building blocks for future R&D discovery. Platforms are the “gifts that keep on giving” insofar as they enable heretofore unavailable capabilities, ushering in a new generation of applications that solve more problems, deliver more choice, and generate more economic activity than standalone application vendors or primitive data integration providers.
  • Our beachhead in Life Sciences, the largest and most demanding R&D lab segment, coupled with our platform and network model, allows us to move into other large R&D lab verticals with common markers including chemicals, agricultural, materials, energy, and more, with far greater leverage and velocity than potential new entrants. 
  • Our partner network represents the largest ecosystem of R&D innovators. We are enabling these partners to leverage our productized integrations as well as build configurable data apps on our platform and enter into commercial go-to-market agreements with us. These activities accelerate bookings and engender a sense of category and company inevitability across the ecosystem with a constant stream of innovation, press releases, joint marketing, references, and 3rd party validation. This also yields considerable platform cross-sell opportunities as we execute a land-and-expand GTM model following the sale of these Tetra-enabled apps.

Metrics, Metrics, Metrics

A world of capital and startup overabundance which greatly distorts the signal-to-noise ratio, a news cycle operating with ever greater velocity, and a toxic combination of social media and founder vanity which fuels endless and shameless self-promotion, converge to form a perfect storm of hype.

But in the final analysis, you can’t hype your way to best-in-class metrics and Category Kings and Queens know this. They’re the embodiment of execution and their metrics reflect this. The best VCs also know this and, as Andrew Carnegie would have said were he working on Sand Hill Road, “As I grow older, I pay less attention to what people say. I just watch what they do.”

Thanks to two decades of cloud company data and the amazing work of firms like Bessemer Venture Partners and Meritech who catalog the data and share metrics, everyone now knows what meh, good, great, epic, and legendary looks like for today’s cloud companies.

Since May 2019, when Spin and I reimagined Tetra 2.0 and launched the Tetra R&D Data Cloud, our metrics have been somewhere between epic and legendary with 2020 ARR growing 10x over 2019, and 2021 ARR expected to increase 3x over 2020. Our capital efficiency has been stellar, with a score of >1.3 in 2020 and an expected 1.5 score in 2021. To that point, we raised an $11M Series A in 2020 and had $9M left on the balance sheet when we closed our $80M Series B on March 26, 2021. Our customer acquisition costs are certainly in the realm of legendary as we’ve barely invested in marketing (although that’s about to change) and our customer retention and expansion metrics are epic. 

In connection with our $80 million Series B, I never built a “pitch deck” and instead simply gave Insight and Alkeon unfettered access to our 2020 plan, results, and metrics, and our board-approved 107-slide Plan of Record. I wanted them to “see what we do” and not “hear what we say.”

We led with our metrics and not hype, and we were rewarded by an extraordinarily efficient, professional, and rewarding fundraising process.

Summary

At TetraScience, our vision is noble, our mission is vital, and we’re passionately committed to being responsible stewards of a global movement to improve and extend human life through AI-based discovery, enabled by the Tetra R&D Data Cloud.

In preparation for this awesome and humbling responsibility, we have been extremely deliberate in designing, organizing, and aligning our category, product, organization, and ecosystem and we have taken nothing for granted in this regard.

We are guided by our mission and enabled by our values and we are assembling the very best and brightest talent from the scientific, cloud, and data science domains.

We have very purposefully built a one-of-a-kind open platform and integrated network which will deliver increasing returns to scale and generate powerful network effects fueling self-reinforcing value-creation and innovation loops resulting in deep and wide competitive moats.

We have catalyzed massive latent market demand and enjoy first-mover advantage and benefit from remarkably strong tailwinds generated by a secular replatforming to the cloud by the world’s most important labs.

In summary, TetraScience possesses all of the DNA markers of a Category King or Queen and today’s $80 million Series B announcement serves as both validation of this and an enabler of it. Evidence once again that category leaders generate self-reinforcing value creation loops and self-fulfilling prophecies.

We are grateful, blessed, and humbled by the commitment of Insight and Alkeon. Now, back to execution.

Patrick


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Patrick Grady
Chairman & CEO Patrick is responsible for TetraScience’s strategy and operational execution and oversees all functional areas of the company. Patrick is considered the co-founder of Tetra 2.0, jointly envisioning and implementing the Tetra R&D Data Cloud with original founder, Siping “Spin” Wang.

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