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Today’s real story: The Facebook monopoly

Published August 19, 2021

Daniel Liss
Contributor

Daniel Liss is the founder and CEO of Dispo, the digital disposable camera social network.

Facebook is a monopoly. Right?

Mark Zuckerberg appeared on national TV today to make a “special announcement.” The timing could not be more curious: Today is the day Lina Khan’s FTC refiled its case to dismantle Facebook’s monopoly.

To the average person, Facebook’s monopoly seems obvious. “After all,” as James E. Boasberg of the U.S. District Court for the District of Columbia put it in his recent decision, “No one who hears the title of the 2010 film ‘The Social Network’ wonders which company it is about.” But obviousness is not an antitrust standard. Monopoly has a clear legal meaning, and thus far Lina Khan’s FTC has failed to meet it. Today’s refiling is much more substantive than the FTC’s first foray. But it’s still lacking some critical arguments. Here are some ideas from the front lines.

To the average person, Facebook’s monopoly seems obvious. But obviousness is not an antitrust standard.

First, the FTC must define the market correctly: personal social networking, which includes messaging. Second, the FTC must establish that Facebook controls over 60% of the market — the correct metric to establish this is revenue.

Though consumer harm is a well-known test of monopoly determination, our courts do not require the FTC to prove that Facebook harms consumers to win the case. As an alternative pleading, though, the government can present a compelling case that Facebook harms consumers by suppressing wages in the creator economy. If the creator economy is real, then the value of ads on Facebook’s services is generated through the fruits of creators’ labor; no one would watch the ads before videos or in between posts if the user-generated content was not there. Facebook has harmed consumers by suppressing creator wages.

A note: This is the first of a series on the Facebook monopoly. I am inspired by Cloudflare’s recent post explaining the impact of Amazon’s monopoly in their industry. Perhaps it was a competitive tactic, but I genuinely believe it more a patriotic duty: guideposts for legislators and regulators on a complex issue. My generation has watched with a combination of sadness and trepidation as legislators who barely use email question the leading technologists of our time about products that have long pervaded our lives in ways we don’t yet understand. I, personally, and my company both stand to gain little from this — but as a participant in the latest generation of social media upstarts, and as an American concerned for the future of our democracy, I feel a duty to try.

Facebook is shook, asks for removal of FTC Chair Khan from antitrust cases against it

The problem

According to the court, the FTC must meet a two-part test: First, the FTC must define the market in which Facebook has monopoly power, established by the D.C. Circuit in Neumann v. Reinforced Earth Co. (1986). This is the market for personal social networking services, which includes messaging.

Second, the FTC must establish that Facebook controls a dominant share of that market, which courts have defined as 60% or above, established by the 3rd U.S. Circuit Court of Appeals in FTC v. AbbVie (2020). The right metric for this market share analysis is unequivocally revenue — daily active users (DAU) x average revenue per user (ARPU). And Facebook controls over 90%.

The answer to the FTC’s problem is hiding in plain sight: Snapchat’s investor presentations:

Snapchat July 2021 investor presentation: Significant DAU and ARPU Opportunity. Image Credits: Snapchat

This is a chart of Facebook’s monopoly — 91% of the personal social networking market. The gray blob looks awfully like a vast oil deposit, successfully drilled by Facebook’s Standard Oil operations. Snapchat and Twitter are the small wildcatters, nearly irrelevant compared to Facebook’s scale. It should not be lost on any market observers that Facebook once tried to acquire both companies.

The market Includes messaging

The FTC initially claimed that Facebook has a monopoly of the “personal social networking services” market. The complaint excluded “mobile messaging” from Facebook’s market “because [messaging apps] (i) lack a ‘shared social space’ for interaction and (ii) do not employ a social graph to facilitate users’ finding and ‘friending’ other users they may know.”

This is incorrect because messaging is inextricable from Facebook’s power. Facebook demonstrated this with its WhatsApp acquisition, promotion of Messenger and prior attempts to buy Snapchat and Twitter. Any personal social networking service can expand its features — and Facebook’s moat is contingent on its control of messaging.

The more time in an ecosystem the more valuable it becomes. Value in social networks is calculated, depending on whom you ask, algorithmically (Metcalfe’s law) or logarithmically (Zipf’s law). Either way, in social networks, 1+1 is much more than 2.

Social networks become valuable based on the ever-increasing number of nodes, upon which companies can build more features. Zuckerberg coined the “social graph” to describe this relationship. The monopolies of Line, Kakao and WeChat in Japan, Korea and China prove this clearly. They began with messaging and expanded outward to become dominant personal social networking behemoths.

In today’s refiling, the FTC explains that Facebook, Instagram and Snapchat are all personal social networking services built on three key features:

“First, personal social networking services are built on a social graph that maps the connections between users and their friends, family, and other personal connections.”
“Second, personal social networking services include features that many users regularly employ to interact with personal connections and share their personal experiences in a shared social space, including in a one-to-many ‘broadcast’ format.”
“Third, personal social networking services include features that allow users to find and connect with other users, to make it easier for each user to build and expand their set of personal connections.”

Unfortunately, this is only partially right. In social media’s treacherous waters, as the FTC has struggled to articulate, feature sets are routinely copied and cross-promoted. How can we forget Instagram’s copying of Snapchat’s stories? Facebook has ruthlessly copied features from the most successful apps on the market from inception. Its launch of a Clubhouse competitor called Live Audio Rooms is only the most recent example. Twitter and Snapchat are absolutely competitors to Facebook.

Messaging must be included to demonstrate Facebook’s breadth and voracious appetite to copy and destroy. WhatsApp and Messenger have over 2 billion and 1.3 billion users respectively. Given the ease of feature copying, a messaging service of WhatsApp’s scale could become a full-scale social network in a matter of months. This is precisely why Facebook acquired the company. Facebook’s breadth in social media services is remarkable. But the FTC needs to understand that messaging is a part of the market. And this acknowledgement would not hurt their case.

The metric: Revenue shows Facebook’s monopoly

Boasberg believes revenue is not an apt metric to calculate personal networking: “The overall revenues earned by PSN services cannot be the right metric for measuring market share here, as those revenues are all earned in a separate market — viz., the market for advertising.” He is confusing business model with market. Not all advertising is cut from the same cloth. In today’s refiling, the FTC correctly identifies “social advertising” as distinct from the “display advertising.”

But it goes off the deep end trying to avoid naming revenue as the distinguishing market share metric. Instead the FTC cites “time spent, daily active users (DAU), and monthly active users (MAU).” In a world where Facebook Blue and Instagram compete only with Snapchat, these metrics might bring Facebook Blue and Instagram combined over the 60% monopoly hurdle. But the FTC does not make a sufficiently convincing market definition argument to justify the choice of these metrics. Facebook should be compared to other personal social networking services such as Discord and Twitter — and their correct inclusion in the market would undermine the FTC’s choice of time spent or DAU/MAU.

Ultimately, cash is king. Revenue is what counts and what the FTC should emphasize. As Snapchat shows above, revenue in the personal social media industry is calculated by ARPU x DAU. The personal social media market is a different market from the entertainment social media market (where Facebook competes with YouTube, TikTok and Pinterest, among others). And this too is a separate market from the display search advertising market (Google). Not all advertising-based consumer technology is built the same. Again, advertising is a business model, not a market.

In the media world, for example, Netflix’s subscription revenue clearly competes in the same market as CBS’ advertising model. News Corp.’s acquisition of Facebook’s early competitor MySpace spoke volumes on the internet’s potential to disrupt and destroy traditional media advertising markets. Snapchat has chosen to pursue advertising, but incipient competitors like Discord are successfully growing using subscriptions. But their market share remains a pittance compared to Facebook.

An alternative pleading: Facebook’s market power suppresses wages in the creator economy

The FTC has correctly argued for the smallest possible market for their monopoly definition. Personal social networking, of which Facebook controls at least 80%, should not (in their strongest argument) include entertainment. This is the narrowest argument to make with the highest chance of success.

But they could choose to make a broader argument in the alternative, one that takes a bigger swing. As Lina Khan famously noted about Amazon in her 2017 note that began the New Brandeis movement, the traditional economic consumer harm test does not adequately address the harms posed by Big Tech. The harms are too abstract. As White House advisor Tim Wu argues in “The Curse of Bigness,” and Judge Boasberg acknowledges in his opinion, antitrust law does not hinge solely upon price effects. Facebook can be broken up without proving the negative impact of price effects.

However, Facebook has hurt consumers. Consumers are the workers whose labor constitutes Facebook’s value, and they’ve been underpaid. If you define personal networking to include entertainment, then YouTube is an instructive example. On both YouTube and Facebook properties, influencers can capture value by charging brands directly. That’s not what we’re talking about here; what matters is the percent of advertising revenue that is paid out to creators.

YouTube’s traditional percentage is 55%. YouTube announced it has paid $30 billion to creators and rights holders over the last three years. Let’s conservatively say that half of the money goes to rights holders; that means creators on average have earned $15 billion, which would mean $5 billion annually, a meaningful slice of YouTube’s $46 billion in revenue over that time. So in other words, YouTube paid creators a third of its revenue (this admittedly ignores YouTube’s non-advertising revenue).

Facebook, by comparison, announced just weeks ago a paltry $1 billion program over a year and change. Sure, creators may make some money from interstitial ads, but Facebook does not announce the percentage of revenue they hand to creators because it would be insulting. Over the equivalent three-year period of YouTube’s declaration, Facebook has generated $210 billion in revenue. one-third of this revenue paid to creators would represent $70 billion, or $23 billion a year.

Why hasn’t Facebook paid creators before? Because it hasn’t needed to do so. Facebook’s social graph is so large that creators must post there anyway — the scale afforded by success on Facebook Blue and Instagram allows creators to monetize through directly selling to brands. Facebooks ads have value because of creators’ labor; if the users did not generate content, the social graph would not exist. Creators deserve more than the scraps they generate on their own. Facebook suppresses creators’ wages because it can. This is what monopolies do.

Facebook’s Standard Oil ethos

Facebook has long been the Standard Oil of social media, using its core monopoly to begin its march upstream and down. Zuckerberg announced in July and renewed his focus today on the metaverse, a market Roblox has pioneered. After achieving a monopoly in personal social media and competing ably in entertainment social media and virtual reality, Facebook’s drilling continues. Yes, Facebook may be free, but its monopoly harms Americans by stifling creator wages. The antitrust laws dictate that consumer harm is not a necessary condition for proving a monopoly under the Sherman Act; monopolies in and of themselves are illegal. By refiling the correct market definition and marketshare, the FTC stands more than a chance. It should win.

A prior version of this article originally appeared on Substack.

Meet the anti-antitrust startup club

Companies betting on data must value people as much as AI

Published August 19, 2021

Asaf Cohen
Contributor

Asaf Cohen is co-founder and CEO at Metrolink.ai, a data operations platform.

The Pareto principle, also known as the 80-20 rule, asserts that 80% of consequences come from 20% of causes, rendering the remainder way less impactful.

Those working with data may have heard a different rendition of the 80-20 rule: A data scientist spends 80% of their time at work cleaning up messy data as opposed to doing actual analysis or generating insights. Imagine a 30-minute drive expanded to two-and-a-half hours by traffic jams, and you’ll get the picture.

As tempting as it may be to think of a future where there is a machine learning model for every business process, we do not need to tread that far right now.

While most data scientists spend more than 20% of their time at work on actual analysis, they still have to waste countless hours turning a trove of messy data into a tidy dataset ready for analysis. This process can include removing duplicate data, making sure all entries are formatted correctly and doing other preparatory work.

On average, this workflow stage takes up about 45% of the total time, a recent Anaconda survey found. An earlier poll by CrowdFlower put the estimate at 60%, and many other surveys cite figures in this range.

None of this is to say data preparation is not important. “Garbage in, garbage out” is a well-known rule in computer science circles, and it applies to data science, too. In the best-case scenario, the script will just return an error, warning that it cannot calculate the average spending per client, because the entry for customer #1527 is formatted as text, not as a numeral. In the worst case, the company will act on insights that have little to do with reality.

The real question to ask here is whether re-formatting the data for customer #1527 is really the best way to use the time of a well-paid expert. The average data scientist is paid between $95,000 and $120,000 per year, according to various estimates. Having the employee on such pay focus on mind-numbing, non-expert tasks is a waste both of their time and the company’s money. Besides, real-world data has a lifespan, and if a dataset for a time-sensitive project takes too long to collect and process, it can be outdated before any analysis is done.

What’s more, companies’ quests for data often include wasting the time of non-data-focused personnel, with employees asked to help fetch or produce data instead of working on their regular responsibilities. More than half of the data being collected by companies is often not used at all, suggesting that the time of everyone involved in the collection has been wasted to produce nothing but operational delay and the associated losses.

The data that has been collected, on the other hand, is often only used by a designated data science team that is too overworked to go through everything that is available.

All for data, and data for all

The issues outlined here all play into the fact that save for the data pioneers like Google and Facebook, companies are still wrapping their heads around how to re-imagine themselves for the data-driven era. Data is pulled into huge databases and data scientists are left with a lot of cleaning to do, while others, whose time was wasted on helping fetch the data, do not benefit from it too often.

The truth is, we are still early when it comes to data transformation. The success of tech giants that put data at the core of their business models set off a spark that is only starting to take off. And even though the results are mixed for now, this is a sign that companies have yet to master thinking with data.

Data holds much value, and businesses are very much aware of it, as showcased by the appetite for AI experts in non-tech companies. Companies just have to do it right, and one of the key tasks in this respect is to start focusing on people as much as we do on AIs.

Data can enhance the operations of virtually any component within the organizational structure of any business. As tempting as it may be to think of a future where there is a machine learning model for every business process, we do not need to tread that far right now. The goal for any company looking to tap data today comes down to getting it from point A to point B. Point A is the part in the workflow where data is being collected, and point B is the person who needs this data for decision-making.

Importantly, point B does not have to be a data scientist. It could be a manager trying to figure out the optimal workflow design, an engineer looking for flaws in a manufacturing process or a UI designer doing A/B testing on a specific feature. All of these people must have the data they need at hand all the time, ready to be processed for insights.

People can thrive with data just as well as models, especially if the company invests in them and makes sure to equip them with basic analysis skills. In this approach, accessibility must be the name of the game.

Skeptics may claim that big data is nothing but an overused corporate buzzword, but advanced analytics capacities can enhance the bottom line for any company as long as it comes with a clear plan and appropriate expectations. The first step is to focus on making data accessible and easy to use and not on hauling in as much data as possible.

In other words, an all-around data culture is just as important for an enterprise as the data infrastructure.

How to ensure data quality in the era of Big Data

UiPath CEO Daniel Dines is coming to TC Sessions: SaaS to talk RPA and automation

Published August 19, 2021

UiPath came seemingly out of nowhere in the last several years, going public last year in a successful IPO during which it raised more than $527 million. It raised $2 billion in private money prior to that with its final private valuation coming in at an amazing $35 billion. UiPath CEO Daniel Dines will be joining us on a panel to discuss automation at TC Sessions: SaaS on October 27th.

The company has been able to capture all this investor attention doing something called robotic process automation (RPA), which provides a way to automate a series of highly mundane tasks. It has become quite popular, especially to help bring a level of automation to legacy systems that might not be able to handle more modern approaches to automation involving artificial intelligence and machine learning. In 2019 Gartner found that RPA was the fastest growing category in enterprise software.

In point of fact, UiPath didn’t actually come out of nowhere. It was founded in 2005 as a consulting company and transitioned to software over the years. The company took its first VC funding, a modest $1.5 million seed round, in 2015, according to Crunchbase data.

A cooling trend in public markets makes UiPath’s down-round IPO a win for the company

As RPA found its market, the startup began to take off, raising gobs of money, including a $568 million round in April 2019 and $750 million in its final private raise in February 2021.

Dines will be appearing on a panel discussing the role of automation in the enterprise. Certainly, the pandemic drove home the need for increased automation as masses of office workers moved to work from home, a trend that is likely to continue even after the pandemic slows.

As the RPA market leader, he is uniquely positioned to discuss how this software and other similar types will evolve in the coming years and how it could combine with related trends like no-code and process mapping. Dines will be joined on the panel by investor Laela Sturdy from CapitalG and ServiceNow’s Dave Wright, where they will discuss the state of the automation market, why it’s so hot and where the next opportunities could be.

In addition to our discussion with Dines, the conference will also include Databricks’ Ali Ghodsi, Salesforce’s Kathy Baxter and Puppet’s Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope you’ll join us. It’s going to be a stimulating day.

Buy your pass now to save up to $100. We can’t wait to see you in October!

Is your company interested in sponsoring or exhibiting at TC Sessions: SaaS 2021? Contact our sponsorship sales team by filling out this form.

Tiger Global backs Nacelle with $50M for its e-commerce infrastructure

Published August 19, 2021

Consumer shift to buying online during the global pandemic — and keeping that habit — continues to boost revenue for makers of developer tools that help e-commerce sites provide better shopping experiences.

LA-based Nacelle is one of the e-commerce infrastructure companies continuing to attract investor attention, and at a speedy clip, too. It closed on a $50 million Series B round from Tiger Global. This is just six months after its $18 million Series A round, led by Inovia, and follows a $4.8 million seed round in 2020.

The company is working in “headless” commerce, which means it is disconnecting the front end of a website, a.k.a. the storefront, from the back end, where all of the data lives, to create a better shopping experience, CEO Brian Anderson told TechCrunch. By doing this, the back end of the store, essentially where all the magic happens, can be updated and maintained without changing the front end.

“Online shopping is not new, but how the customer relates to it keeps changing,” he said. “The technology for online shopping is not up to snuff — when you click on something, everything has to reload compared to an app like Instagram.”

Nacelle raises $4.8M for its headless e-commerce platform

More people shopping on their mobile devices creates friction due to downloading an app for each brand. That is “sucking the fun out of shopping online,” because no one wants that many apps on their phone, Anderson added.

Steven Kramer, board member and former EVP of Hybris, said via email that over the past two decades, the e-commerce industry went through several waves of innovation. Now, maturing consumer behaviors and expectations are accelerating the current phase.

“Retailers and brands are struggling with adopting the latest technologies to meet today’s requirements of agility, speed and user experience,” Kramer added. “Nacelle gives organizations a future-proof way to accelerate their innovation, leverage existing investments and do so with material ROI.”

Data already shows that COVID-era trends accelerated e-commerce by roughly five years, and Gartner predicts that 50% of new commerce capabilities will be incorporated as API-centric SaaS services by 2023.

Those kinds of trends are bringing in competitors that are also attracting investor attention — for example, Shopistry, Swell, Fabric, Commerce Layer and Vue Storefront are just a few of the companies that raised funding this year alone.

Anderson notes that the market continues to be hot and one that can’t be ignored, especially as the share of online retail sales grows. He explained that some of his competitors force customers to migrate off of their current tech stack and onto their respective platforms so that their users can get a good customer experience. In contrast, Nacelle enables customers to keep their tech stack and put components together as they see fit.

“That is painful in any vertical, but especially for e-commerce,” he said. “That is your direct line to revenue.”

Meanwhile, Nacelle itself grew 690% in the past year in terms of revenue, and customers are signing multiyear contracts, Anderson said.

Anderson, who is an engineer by trade, wants to sink his teeth into new products as adoption of headless commerce grows. These include providing a dynamic layer of functionality on top of the tech stack for storefronts that are traditionally static, and even introducing some livestream capabilities later this year.

As such, Nacelle will invest the new round into its go-to-market strategy and expand its customer success, partner relations and product development. He said Nacelle is already “the de facto standard” for Shopify Plus merchants going headless.

“We want to put everything in a tailor-made API for e-commerce that lets front-end developers do their thing with ease,” Anderson added. “We also offer starter kits for merchants as a starting point to get up-and-running.”

4 views on the future of retail and the shopping experience

Insight Partners leads $30M round into Metabase, developing enterprise business intelligence tools

Published August 19, 2021

Open-source business intelligence company Metabase announced Thursday a $30 million Series B round led by Insight Partners.

Existing investors Expa and NEA joined in on the round, which gives the San Francisco-based company a total of $42.5 million in funding since it was founded in 2015. Metabase previously raised $8 million in Series A funding back in 2019, led by NEA.

Metabase was developed within venture studio Expa and spun out as an easy way for people to interact with data sets, co-founder and CEO Sameer Al-Sakran told TechCrunch.

“When someone wants access to data, they may not know what to measure or how to use it, all they know is they have the data,” Al-Sakran said. “We provide a self-service access layer where they can ask a question, Metabase scans the data and they can use the results to build models, create a dashboard and even slice the data in ways they choose without having an analyst build out the database.”

He notes that not much has changed in the business intelligence realm since Tableau came out more than 15 years ago, and that computers can do more for the end user, particularly to understand what the user is going to do. Increasingly, open source is the way software and information wants to be consumed, especially for the person that just wants to pull the data themselves, he added.

George Mathew, managing director of Insight Partners, believes we are seeing the third generation of business intelligence tools emerging following centralized enterprise architectures like SAP, then self-service tools like Tableau and Looker and now companies like Metabase that can get users to discovery and insights quickly.

“The third generation is here and they are leading the charge to insights and value,” Mathew added. “In addition, the world has moved to the cloud, and BI tools need to move there, too. This generation of open source is a better and greater example of all three of those.”

To date, Metabase has been downloaded 98 million times and used by more than 30,000 companies across 200 countries. The company pursued another round of funding after building out a commercial offering, Metabase Enterprise, that is doing well, Al-Sakran said.

The new funding round enables the company to build out a sales team and continue with product development on both Metabase Enterprise and Metabase Cloud. Due to Metabase often being someone’s first business intelligence tool, he is also doubling down on resources to help educate customers on how to ask questions and learn from their data.

“Open source has changed from floppy disks to projects on the cloud, and we think end users have the right to see what they are running,” Al-Sakran said. “We are continuing to create new features and improve performance and overall experience in efforts to create the BI system of the future.

Hacking my way into analytics: A creative’s journey to design with data

Medical supply marketplace startup bttn. sews up additional $5M seed

Published August 19, 2021

Coming off a $1.5 million seed round in June, bttn. announced Thursday that it secured another $5 million extension, led by FUSE, to the round to give it a $26.5 million post-money valuation.

The Seattle-based company was founded in March 2021 by JT Garwood and Jack Miller after seeing the challenges medical organizations had during the global pandemic to not only find supplies, but also get fair prices for them.

“We went into this building on the pain points customers had dealing with a system that is so archaic and outdated — most were still faxing in order forms and keeping closets full of supplies, but not knowing what was there,” Garwood, CEO, told TechCrunch.

Bttn. is going after the U.S. wholesale medical supply market, which is predicted to be valued at $243.3 billion by the end of 2021, according to IBISWorld. The company created a business-to-business e-commerce platform with a variety of high-quality medical supplies, saving customers an average of between 20% and 40%, while providing a better ordering and shipping experience, Garwood said.

It now boasts more than 300 customers, including individual practices and surgical centers, and multiple government contracts. It is also currently the preferred supplier for over 17 healthcare associations across the country, Garwood said. In addition to expanding into dental supplies, bttn. is also attracting customers like senior living facilities and home and hospice care.

Garwood intends to use the funds to expand bttn.’s technology, sales and operations teams, and increase its partnerships. The company is also adding new features like a portal to track shipments more easily, better order automation and improve the ability to control when supplies will get to them.

Bttn. is also analyzing more of the data coming in from its marketplace to recognize where the trends are coming from, including hospitalization rates, to share with customers. For example, if hospitals are overcrowded, supply shortages will follow, Garwood said.

“The medical supply industry was built on inequity, and we have a sense of duty to build a product that enables a better future for our customers,” he added. “We can proactively let customers know that spikes are expected, provide them with correct information and give that power back to the consumers and healthcare providers in ways they never had before.”

Whereas bttn.’s first seed round was “about pouring gas on the fire,” partnering with FUSE this time around was an easy decision for Garwood, who said the firm is bringing new assets to the table.

Brendan Wales, general partner at FUSE, said via email that his firm backs promising entrepreneurs building businesses in the Pacific Northwest and discovered bttn. before they announced any funding.

He said there is massive consumerization of healthcare, most evident on the patient side for years, but now becoming so on the provider side. Medical office employees are looking for the same type of customer experience they get from online businesses they frequently shop at, and bttn. “has a relentless drive to provide the same type of experiences and interactions to health providers.”

“We fell in love with the idea of providing a transparent and delightful customer experience to health providers, something that has been sorely lacking,” Wales added. “That, tied in with a young and ambitious team, made it so that our entire partnership worked tirelessly to partner with them.”

How tech can build more resilient supply chains

Would the math work if Databricks were valued at $38B?

Published August 18, 2021

Databricks, the open-source data lake and data management powerhouse has been on quite a financial run lately. Today Bloomberg reported the company could be raising a new round worth at least $1.5 billion at an otherworldly $38 billion valuation. That price tag is up $10 billion from its last fundraise in February when it snagged $1 billion at a $28 billion valuation.

Databricks declined to comment on the Bloomberg post and its possible new valuation.

The company has been growing like gangbusters, giving credence to the investor thesis that the more your startup makes, the more it is likely to make. Consider that Databricks closed 2020 with $425 million in annual recurring revenue, which in itself was up 75% from the previous year.

As revenue goes up so does valuation, and Databricks is a great example of that rule in action. In October 2019, the company raised $400 million at a seemingly modest $6.2 billion valuation (if a valuation like that can be called modest). By February 2021, that had ballooned to $28 billion, and today it could be up to $38 billion if that rumor turns out to be true.

Databricks raises $1B at $28B valuation as it reaches $425M ARR

One of the reasons that Databricks is doing so well is it operates on a consumption model. The more data you move through the Databricks product family, the more money it makes, and with data exploding, it’s doing quite well, thank you very much.

It’s worth noting that Databricks’s primary competitor, Snowflake went public last year and has a market cap of almost $83 billion. In that context, the new figure doesn’t feel quite so outrageous, But what does it mean in terms of revenue to warrant a valuation like that. Let’s find out.

Valuation math

Let’s rewind the clock and observe the company’s recent valuation marks and various revenue results at different points in time:

Q3 2019: $200 million run rate, $6.2 billion valuation.
Q3 2020: $350 million run rate, no known valuation change.
EoY 2020: $425 million run rate, $28 billion valuation (Q1 valuation).
Q3 2021: Unclear run rate, possible $38 billion valuation.

The company’s 2019 venture round gave Databricks a 31x run rate multiple. By the first quarter of 2021, that had swelled to a roughly 66x multiple if we compare its final 2020 revenue pace to its then-fresh valuation. Certainly software multiples were higher at the start of 2021 than they were in late 2019, but Databricks’s $28 billion valuation was still more than impressive; investors were betting on the company like it was going to be a key breakout winner, and a technology company that would go public eventually in a big way.

To see the company possibly raise more funds would therefore not be surprising. Presumably the company has had a good few quarters since its last round, given its history of revenue accretion. And there’s only more money available today for growing software companies than before.

But what to make of the $38 billion figure? If Databricks merely held onto its early 2021 run rate multiple, the company would need to have reached a roughly $575 million run rate, give or take. That would work out to around 36% growth in the last two-and-a-bit quarters. That works out to less than $75 million in new run rate per quarter since the end of 2020.

Is that possible? Yeah. The company added $75 million in run rate between Q3 2020 and the end of the year. So you can back-of-the-envelope the company’s growth to make a $38 billion valuation somewhat reasonable at a flat multiple. (There’s some fuzz in all of our numbers, as we are discussing rough timelines from the company; we’ll be able to go back and do more precise math once we get the Databricks S-1 filing in due time.)

Databricks co-founder and CEO Ali Ghodsi is coming to TC Sessions: SaaS

All this raises the question of whether Databricks should be able to command such a high multiple. There’s some precedent. Recently, public software company Monday.com has a run rate multiple north of 50x, for example. It earned that mark on the back of a strong first quarter as a public company.

Databricks securing a higher multiple while private is not crazy, though we wonder if the data-focused company is managing a similar growth rate. Monday.com grew 94% on a year-over-year basis in its most recent quarter.

All this is to say that you can make the math shake out for Databricks to raise at a $38 billion valuation, but built into that price is quite a lot of anticipated growth. Top quartile public software companies today trade for around 23x their forward revenues, and around 27x their present-day revenues, per Bessemer. To defend its possible new valuation when public, then, leaves quite a lot of work ahead of Databricks.

The company’s CEO, Ali Ghodsi, will join us at TC Sessions: SaaS on October 27th, and we should know by then if this rumor is, indeed true. Either way, you can be sure we are going to ask him about it.

Why one Databricks investor thinks the company may be undervalued

How to establish a health tech startup advisory board

Published August 18, 2021

Patrick Frank
Contributor

Patrick Frank is the co-founder and COO of PatientPartner, a platform that connects pre-surgical patients with fully recovered patients who went through the same surgery. Frank has worked in consumer technology across industries including retail banking, law, real estate and healthcare.

When you enter the health tech industry as a new startup, an advisory board is a crucial foundational step. A board can guide you through industry-specific nuances, help you make important decisions and prove your legitimacy to investors looking for a strong industry background.

An advisory board will be able to give you strategic insights about both your company and the wider healthcare and technology industries.

In my experience of raising capital, the unpredictable financial situation at the beginning of the pandemic meant we nearly lost our $2 million round, but came through with a committed $250,000, which we used to bring in about $500,000 in revenue.

Something that helped this process was building our advisory board and starting small — we didn’t go for all of healthcare but instead focused on two healthcare verticals. This allowed us to prove our concept, build case studies and win contracts with specific teams in our customers’ companies.

It pays off to stay focused and prove your worth so that your advisory board members can champion you in niche markets, with the potential to expand in the future. For this reason, it’s important to identify the main intention behind your board, and exactly who should be on it.

Who to recruit

Three to five people is an ideal starting point for an advisory board, depending on the size and stage of your company. In health tech, you need more than just the healthcare perspective — you also need the insight of those who have already grown technology companies, perhaps outside of the industry. Our company’s board is an even split of two healthcare and two technology advisers, and, ideally, you want to find a fifth who is well versed in both industries.

It pays off to stay focused and prove your worth so that your advisory board members can champion you in niche markets, with the potential to expand in the future.

An M.D., a Ph.D. from a respected institution or a thought leader in your relevant field of healthcare is the most important asset to an advisory board. These are the highly decorated physicians who have strong connections and act as a reference for their peers.

They provide instant credibility for your company, help you get into the minds of both patients and healthcare providers, and can outline how various health systems work.

Dear Sophie: Tips on EB-1A and EB-2 NIW?

Published August 18, 2021

Sophie Alcorn
Contributor

Sophie Alcorn is the founder of Alcorn Immigration Law in Silicon Valley and 2019 Global Law Experts Awards’ “Law Firm of the Year in California for Entrepreneur Immigration Services.” She connects people with the businesses and opportunities that expand their lives.

Mealworm farming company Beta Hatch raises $10M

Published August 18, 2021

Last time I was in Hong Kong, a startup gave me a jar of mealworms as a snack. They were crunchy and a bit odd looking (as one might expect from a jar full of baked larvae). They really didn’t offer much in the way of flavor, though, so maybe supply your own seasoning.

For all sorts of sustainability reasons, there’s been a good deal of interest in these sorts of alternative protein sources — for humans and otherwise. Beta Hatch’s farming efforts are squarely focused on the latter, citing livestock and pets as primary targets for a farming process it says is “virtually zero-waste.”

Today the St. Louis-based firm announced $10 million in funding in a round led by Lewis & Clark AgriFood, with participation from Cavallo Ventures and Innova Memphis, which are both signed on as existing investors. The money comes as Beta Hatch is eyeing the expansion of its flagship farm in Cashmere, Washington.

“We are proud to be a part of building the future of farming as a member of the Washington agricultural community,” founder and CEO Virginia Emery said in a release. “We are excited for our presence in rural America to grow, as we employ and partner with the people in those communities to feed a growing global population.”

The company says the new facility will be the largest of its kind in North America, helping to push Beta Hatch to 10x its current output over the next year. The location is currently powered by renewably sourced energy.

Mealworms have proven intriguing as food sources for food sources, as evidenced by Ÿnsect’s $125 million raise way back in 2019.

Tech investors see bugs as a big business as Ÿnsect raises $125 million