The SPAC craze is slowing in the wake of myriad missteps.

Companies as far afield from one another as BuzzFeed (media), Bird (e-scooter fleets), and Dave (consumer fintech), among other recent SPAC-led debuts, have shed value since their blank-check combinations. The result of the SPAC boom looks more like a series of misses with a few hits (SoFi) than a viable exit path for highly valued technology companies that remain private.

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And yet, there’s still life in the SPAC game, and one particular combination could prove to be a bellwether for future unicorn liquidity via blank-check companies.

The company in question, MariaDB, is the force behind the open source project of the same name. MariaDB the software is an “open source relational database,” as the company writes, meaning that it’s available for free. The company also has an enterprise product (subscription-based) that includes support and a hosted version of its service called SkySQL.

MariaDB is a modern open source software company with recurring revenues that is going public via a SPAC. This means that the deal will take a startup that has raised nine figures of private capital to the public markets in an expedited manner. For unicorns that are too expensive to sell themselves, but not yet mature enough for a traditional IPO, MariaDB the company is setting precedent.

This morning, we’re talking MariaDB’s recurring revenues, its forecasts, its deal and what we can glean from the transaction at this distance.

Why? Because if the price that MariaDB has secured for itself through the deal is attractive, it could indicate that while many SPACs have struggled post-combination, there could still be a path for software companies with well-understood business models to lever blank-check companies to public-market debuts.

Given the rising unicorn backlog that the recent explosion in venture capital dealmaking has created, it’s critical to understand what exit paths are open and which are not. So let’s get into this SPAC deal, yeah?

MariaDB’s SPAC transaction

Let’s very briefly chat through the transaction details, and then get into the meat of MariaDB’s business results.

Per the company’s release, it intends to merge with Angel Pond Holdings Corporation. The transaction is a little complicated, involving a “$104 million private placement of Series D Preferred shares of MariaDB” that “closed concurrently with [the] announcement,” along with a “$43 million commitment from existing investors and $27 million from an affiliate of Angel Pond’s sponsor.”

In simpler terms, a lot of money is being pledged to the company and the deal, which the release claims “shows the commitment and conviction of Angel Pond’s sponsor in the transaction.” Normally we’d gloss over corporate boilerplate of that sort, but in this case, it actually matters. A good chunk of capital is going into MariaDB as part of this deal in a manner that appears to limit the take-backs that many SPAC deals have struggled with at close.

In total, the deal could yield as much as “$317 million of net cash proceeds,” though that number will change a little, redemptions depending.

Finally, the transaction values MariaDB with an enterprise value of $672 million and an equity value of $973.6 million, according to an investor presentation. That means that MariaDB will be valued in traditional terms at just about the unicorn mark. That means we’re seeing a unicorn software debut by SPAC. Next: results.

Whose Your Landlord,¹ or WYL, announced a $2.1 million seed round today led by Black Operator Ventures, better known as BlackOps Ventures. TechCrunch readers will already be aware of BlackOps’ fund, which we covered at launch last December. The goal behind the $13 million capital pool was to invest in Black founders. The WYL round indicates that the fund is living up to its plan.

TechCrunch spoke with Ofo Ezeugwu, founder and CEO of WYL, about his company and its new investment. Per Ezeugwu, WYL was founded back in 2015 and raised $1.1 million over a roughly seven-year period. Launched with a focus on collecting renter notes concerning landlord and building quality, the company has evolved to include a SaaS service for what WYL calls “home providers,” or the folks who own buildings and other rental units.

Image Credits: WYL. Ofo Ezeugwu.

In simple terms, WYL collects renter feedback, which is easy to find and digest on its website. For rental owners with a good number of units, they can pay for the collected information, allowing landlords to track how they are performing with their customers, how many of their current tenants intend to stay, and so forth.

The startup charges building owners $2 per unit, per month for its software, a figure that Ezeugwu said can be discounted for larger contract volumes. The startup has plans to expand its feature set, naturally, allowing it to charge more in time. An example the CEO provided during our chat was using natural language processing (NLP) to find trends in written reviews, which could help companies with hundreds of units better parse incoming feedback.

Before it launched its software product, WYL generated revenue through brand partnerships with companies like Allstate and others that sell to folks who rent. Presumably, the company can continue that work to supplement its software incomes, though we anticipate that WYL will become a majority software business in time — if it isn’t already — from a revenue perspective.

The idea of underestimated founders is bandied about in startup land pretty often. And yet if we rifled through the latest few hundred funding rounds, you might wind up wondering if anything has changed at all.

Black Ops co-founder James Norman told TechCrunch about his own fundraising journey for his company, Pilot.ly, when explaining the impetus behind his venture group. In Norman’s view, Black founders are underinvested in, which means that his firm may have access to deal flow that competing venture firms are overlooking and that the founders he wanted to invest in are “the biggest arbitrage opportunity to tech.”

Now flush with its largest investment to date and a software product in-market — after running pilots for the SaaS offering last year, WYL has onboarded 7,000 units, the CEO said — the startup intends to hire and keep building. Let’s see how quickly it can scale its software incomes. If that goes according to plan, it shouldn’t have to wait another seven years for external investor interest to manifest in the form of a seven-figure check.

1. The startup uses the “possessive form of the word ‘who’,” it writes on its website, because it wants its “community [to have] ownership of their living situations by putting housing in their hands.” Sharing that clarification in case some of you were about to send me emails about the grammar I used!

Rising pressure on big business to address the threat of climate change by decarbonizing their ops has, in recent years, led to huge demand for carbon offset schemes — enabling companies to buy carbon credits to ‘offset’ emissions so they can claim to be ‘greening’ their activities, without having to make more substantial changes (like, say, an airline running fewer planes).

Unsurprisingly this has created lots of wonky incentives attached to forestry resources and carbon offsetting projects. Which, in turn, is creating lots of knock-on startup opportunities.

One example of dubious carbon offsetting involves existing woodlands being repurposed for carbon credits in a way that artificially inflates the claimed credit — such as by claiming a forest was going to be cut down when it wasn’t, meaning there is no net increase in carbon sequestered (and a woodland is essentially just repurposed to help corporates greenwash their pollutive ‘business as usual’). So without robust oversight carbon offsetting projects can clearly be a sink for kicking the climate can down the road towards disaster.

Similarly, greenwashing pressures have led to the awful sight of trees being chopped up for biomass and burnt — under a dubious claim of ‘green energy’. Here, too, there’s a need for rigorous accountancy — in the form of a full lifecycle analysis of a biomass project — else the risks can even go beyond meaningless greenwashing to actively harmful environmental outcomes (such as a loss of mature woodlands and another net reduction in how much carbon is sequestered).

Pressure on companies to quickly get on a path to carbon neutrality is, very evidently, generating huge but often poorly directed demand to stand up glossy marketing pledges that claim to be ‘tackling’ climate change.

The overarching question is whether anything of value is being done with this corporate reputation spend when it comes to actually preventing catastrophic climate change?

Turns out this too is a burgeoning startup business opportunity.

Startups applying technologies to target the accountability/credibility gap around carbon offsetting by proposing schemes to verify the credibility of projects and monitor performance include the likes of Pachama and Sylvera, which are both backed by some major investors — with around $25M and $39M raised respectively to date.

There are also startups focused on expanding access to carbon markets so that smaller landowners can get looped into revenue-generating carbon offsets for their woodlands. Such as US-focused Silvia Terra.

The prospect of receiving recurring revenue for conserving forestry may at least held protect woodlands from other forms of development that could see trees felled to make way for different money-generating schemes with less or no carbon sequestering benefits. But — clearly — forestry conservation alone isn’t going to be enough to reduce global carbon emissions.

Hence other climate startups are focused on expanding the volume of forested landmass. Such as Terraformation — which is using a mix of old and new technologies to rapidly reforest wasteland with the goal of increasing the amount of global landmass that’s covered by trees.

Again, though, even tree planting has been criticized as a flawed “magical thinking” non-solution to climate change.

In some cases, poor incentives to simply increase forestry volume have led to native tree species being ripped out and replaced with faster growing alternatives — leading to biodiversity loss and a forestry monoculture that’s less resilient to the challenges of a changing climate. Which is also, ultimately, environmentally counterproductive.

Climate change increases the risk of drought, storms and forest fire — all of which can decimate forests. So mindless tree planting projects that fail to effectively model risks, don’t selectively and sensitivity plant, and fail to follow through with good forestry management to ensure the long term success of a woodland are also best filed under pointless (and even potentially harmful) greenwashing.

The sad truth is that, globally, forests are still being felled at a far faster rate than they’re being replanted — and ultimately that net destruction is fuelled by the unreconstructed demands of industry and the system of growth-focused consumption that powers the modern world.

Without systemic restructuring of how we consume and trade towards a reformed, circular economy that revolves around reuse and longevity it’s hard to see how the rapacious global engine of demand can be dialled back to an environmentally sustainable level — in which trees and all the rest of life on Earth (including humans) can survive and thrive far into the future.

Given such vast challenges — not to mention the incremental timescales involve in anything attached to forestry ecosystems — startups that are trying to make a meaningful difference in this space certainly have their work cut out.

Optimizing for forest survival

YC-backed Pina Earth is a relative newcomer (founded 2021) that’s trying to tackle some of the problematic incentives around carbon offsetting projects by creating smarter skews that encourage landowners to increase woodland biodiversity and future-proof forests against the hotter, harsher climate that’s fast coming at us.

It’s doing this by pitching forest owners on making sustainable improvements to existing woodlands that will enable them to get certification for additional carbon credits — i.e. on top of whatever their woodland may already be bringing in — generating a “recurring income” via selling any extra stored carbon to the scores of companies eager to top up their offsetting.

So while some carbon offsetting atop existing woodlands may be accused of bogus greenwashing, here at least the premise is that carbon credits are being attached to — and contingent on — improvements to forestry that will, or well, should generate extra carbon, assuming all goes to plan.

“With the help of sustainable forestry, your forest can store additional carbon,” runs the pitch to forest owners on Pina Earth’s website. “This is done through measures such as planting climate-resilient tree species and increasing biodiversity.”

The Munch-based startup — which is backed by Y Combinator — was set up by a trio of founders, CEO Dr. Gesa Biermann; CPO Florian Fincke; and CTO Jonas Kerber who met at the Center for Digital Technology and Management (CDTM) and have a collective background in environmental studies, human-computer interaction, robotics and technology management.

Munich startup Pina Earth’s co-founders; L to R: Fincke, Biermann, Kerber (Image credits: Pina Earth)

Their idea is to sell landowners on the financial value of good woodland management — linking sustainable forestry to additional carbon credits which mean there’s a financial reward for making the kinds of relatively costly interventions that are likely to be needed to make woodlands more productive (in carbon sequestering terms) and resilient to climate change over the longer term.

“Essentially we’re building an online platform where we’re connecting forest owners and carbon credit buyers,” explains Biermann. “Our goal is to make it as easy as possible for forest owners to be rewarded for the ecosystem services they provide.”

“In the projects that we do we’re trying to change the species diversity of the forest over time to make it more resilient to climate change,” she adds.

“That’s really our goal — to democratize access to this market, to the voluntary carbon market in this case, where I think for one of the first times you’re able to align ecology and economy in a very productive way,” she also tells TechCrunch. “The way that it works in the forest timeline is you actually give out future-looking carbon credits — this is quite common in the forestry carbon credit scene because they’re just slow ecosystems. So you’re trying to overcome this by paying someone now for the carbon that will be sequestered a bit later on.

“With the monitoring cycle that we have of about three years this is something that we would then align to these vintages of carbon credits being given out in three year cycles to keep incentivizing the forest owners to keep doing the restructuring project over time.”

Albeit she won’t be drawn into predicting exactly how much extra income a landowner might be able to generate through additional carbon credits. (She says the price will “depend” on a variety of per-project factors, such as the existing tree species and how much optimization is possible.)

“That’s kind of the challenge we’re trying to address the whole way through is incentivizing someone to do something now that will pay off in let’s say 30 or 40 years because forests are just very slow ecosystems,” she adds. “As a startup I think that’s quite an interesting challenge because us starting into this journey — the effects of this will take place a lot later, so once we are kind of close to the end of our work life, so I think that’s a very interesting perspective on the timeframe, also as a startup founder.”

To support its long term environmental mission, Pina Earth is building a platform that helps landowners with the admin side of project certification, especially to make it easier for smaller landowners to access carbon markers — while also taking care of the remote sensing and AI modelling to quantify a project’s carbon outputs and — it hopes — increase the speed and quality of carbon credits derived from the forestry.

There are a couple of components to Pina Earth’s product (which is still pre-commercial launch).

Firstly process automation: It’s building out a platform to support landowners through what can be a complex certification process vs manually filling in scores of forms.

Pina Earth project dashboard (Image credit: Pina Earth)

The second, back-end element involves complex data processing and modelling, such as using machine learning to predict how climate change might affect future growth of the forest and impact its ability to sequester carbon.

To power this and conduct ongoing remote monitoring of the projects Pina Earth is pulling in and processing 2D and 3D data on forests, captured via sensors attached to ultralight aircraft (it partners with a third party to do the actual data gathering). 

She says they considered a range of possible methods for remotely capturing data to monitor the carbon offsetting projects — from drones to satellites — but settled on hobby planes as best suited to capture the level of data needed for it to be able to quantify improvements to forests.

“We’re in the middle with this approach of using ultralight aircraft data because the type of project that we’re focusing on — improved forest management — actually requires an improved resolution [vs satellite data] to be able to detect the tree species,” she notes.

“Our goal — with these improved forest management projects — is we try to summate into the future what will happen to this particular forest under climate change. Because especially in Germany — but also throughout Europe — we’ve been seeing a lot of forests dying due to droughts, bark beetles, storms. And we’re trying to incentivize forest owners to change the structure of these forests that are mostly monocultures — usually one type of tree species — to a biodiverse mix.”

Biermann likens the approach to diversifying a financial portfolio — i.e. in order to make it “less prone to risk in the future”.

As well as increasing the mix of of trees in a woodland as a strategy to reduce disease risk, she mentions that having forestry where growth is managed so as not to have all the trees at the same height can help with resilience to storms, for example.

She suggests it may also be the case that landowners need to plant different, even non-local tree species that may be more resistant to the hotter temperatures and drought conditions which are associated with climate change.

Per Biermann, Pina Earth is planning to do monitoring of projects about every three years — “to have a tighter net on what’s going on on the ground in this forest; is it developing in the way we’d like it to?”, as she puts it.

Doing remote monitoring of forests allows for more regular monitoring vs traditional on the ground methods, which — she suggests — helps improve the quality of the carbon credit. She says its method is able to transform the 2D and 3D forestry data it gets as a raw input into “single tree-based carbon storage” validation of projects.

“I think what’s also unique in our approach is that we simulate carbon sequestration of every single tree that we detected into the future under changing regional climate conditions,” she adds. “This allows us to optimize for this forest’s survival probability and sequester more carbon. So I think there’s where we have a unique twist to forest carbon projects because we’re very much focused on making those forests climate resilient.”

While the startup’s initial business model is focused on charging forest owners for its SaaS, Biermann says ultimately they want to be able to offer the tech for free to maximize access — but would then charge a cut on any extra carbon credits generated.

However that could create a potential conflict of interest — since Pina Earth is also involved in assessing the quality and performance of the projects.

Asked how it would resolve that conflict Biermann says it’s working with a German non-profit — which has a technical advisory board that spans environmental organizations, forestry science and the carbon credit market — and she envisages such an independent entity being involved in helping to verify the carbon credits as an additional accountability layer.

“We’re partnering with this local non-profit that’s developing a domestic German forest carbon standard,” she says, adding.  “Since they are also just developing this we’re working very closely to get our data interactions points very aligned so that there won’t be the downside of having larger costs and having a longer process to get certified… In this case working with this non-profit that’s also doing the stakeholder consultation really gives this additional trust and allows us to not have this conflict of interest because there’s another party also looking at the project.”

Discussing generally how it stands up the accuracy of its data, she says it’s using terrestrial forest data (which landowners usually already have) at the start of a project to benchmark the accuracy of its models when it’s using remote sensing.

“This ground-truthing with terrestrial data’s really important to use to be able to show we can get close to these results,” she says, adding: “The other side of it, I think, is more related to having a stakeholder dialogue — to get everybody on board, all kinds of different organizations, because you have to agree on the way a forest carbon credit is actually generated, and for that we’re partnering with [local] organizations.”

Biermann says Pina Earth is also intending to put its method through a public consultation process — and its website notes that its open data approach will include purchased carbon credits being “retired in a public registry” to ensure they can only be used once — “to make sure that we don’t have any blind spots”. 

Given the rising numbers of carbon offsetting validation startups there are likely to be growing opportunities for other types of partnerships that may further help drive accountability.

“I think that’s actually one of the most exciting things of working in this particular segment because at least from our experience everybody is so open to partnering because the bottom line is you’re trying to remove carbon from the atmosphere and you’re trying to create this sustainable impact so if we could achieve this by partnering I think everybody is kind of on board, so there’s usually not a long discussion on this,” adds Biermann. “It’s much more collaborative, I think, than other environments.”

What about if forest projects don’t perform as it projected when it handed out the carbon credit?

On that, Biermann says it’s built in multiple safeguards — starting with making conservative assumptions on the science side.

It is also structuring the credit system with a “risk buffer”, whereby a certain percentage of carbon credits are pooled across all projects, so aren’t given out, “as an internal insurance mechanism”.

“We are also doing this frequent monitoring cycle because we want to be able to incorporate new science as it comes out,” she adds. “Thankfully this is a really active science scene and we are quite close to the scientific community un our startup so also with our measurements and monitoring we want to adjust to and adapt to whenever anything new is found out… to really guarantee this high quality carbon credit, also for the carbon credit buyer side.”

On the wider critique of carbon offsetting — i.e. that it generates greenwashing by creating a means for companies to pay to avoid making systemic changes that will lead to net reductions in their own carbon emissions — Biermann agrees this can be a problem.

“Some carbon credits projects have been questioned on the way they set up their methodology and that’s why we went through all of the forest methodologies that are out there for domestic and international standards for voluntary carbon projects to rethink the criteria and to try to automate the documentation to, again, democratize access to these but also to really think about what does a high credit have to show? What’s important to do in terms of data?” she also says.

To try to avoid Pina Earth ending up inadvertently working for greenwashers, Biermann says it’s partnering with organizations that are doing carbon footprinting for corporates.

“Partnering with them I think is important because then they’re the part who does the footprint calculation, according to official criteria. They first work on reduction methods and only then do they resort to offset projects. So I see ourselves very much in this chain — and the important of other partners who work on footprinting and reduction,” she suggests.

“There are so many startups working on different issues — let’s say of the carbon credit value chain — I can think of a lot of other problem areas where it would be great if other startups started; having a way to really tell the footprint of a company through the scope 1, 2, 3 [emissions]. Being able to make that transparent. Yeah, so a lot of transparency issues along the value chain are being tackled by different startups… And those are the ones we get to partner with, essentially.”

On the go to market front, Pina Earth is focused initially on its home turf and forests of Germany — where it is currently operating two projects across 1,200 hectares as it prepares to launch later this year.

But Biermann says it believes its approach can scale across Europe — and she mentions France, Spain as other countries of “particular” interest, because they have quite similar forest structures to Germany so it reckons it could easily transfer its methods there.

The UK is another potential market it’s eyeing expanding into, she adds.

“An advantage with these countries is they already have domestic forest carbon standards — in the UK that would be the woodland carbon code for example,” she notes. “And we could then apply to get our methodology approved with them to develop these types of improved forest management projects under a domestic standard in a different country.”

Sadly, a study published in 2020 found that Europe’s forest biomass has seen a dramatic rise in the rate of loss since 2015 — likely as a result of increased demand for timber and to burn wood for biomass. So the trend curve is not bending in the right direction.

Albeit that means there’s even greater imperative to nudge regional landowners towards sustainable forestry and caring for — not cutting down — their precious woodlands.

What’s Biermann prediction for the future of forestry? Is every woodland going to be end up under some form of high tech surveillance and carbon quantification — with such tech becoming a key conservation tool, given the still rising pressures on natural ecosystems?

“It comes back to if you don’t really measure it you can’t really incentivize it and you can’t really value it,” she says. “At least in the way that our economy works. So I think it would be really beneficial for forests to be measured more closely and to then brought to the attention of the public and investors.

“I think we can see a shift towards this — I think it goes beyond climate investments being done for the climate’s sake but because it is the next wave of innovation and economic opportunity. So I think in that sense these monitoring systems will become more applicable to also other forest areas.”

Currently Pina Earth is in YC’s Winter batch — so is focused on getting ready for demo day.

The $500k in funding it’s received via the accelerator is its first external investment, with the founders having bootstrapped early research and development of the product.

“We had a couple of grants that helped us bootstrap along the way and this is the first equity funding now that we’ve gotten. We’re looking to use the money to hire key team members… and to launch the product on the market later [this year].”

“Right now we’re really focused on product development and getting that off the ground and running,” she adds. “So trying to take also the advice — by YC — to heart to really collaborate with our customers as much as possible.”

Netlify, the well-funded company that, in many ways, started the Jamstack movement, today announced that it has acquired Quirrel, an open-source service for managing and executing serverless functions.

Founded by Simon Knott, who is also the maintainer of the popular Blitz.js React framework, Quirrel never raised any outside funding before the acquisition, which quietly happened in the middle of last year after one of Netlify’s investors made the introduction, as Netlify CEO Matt Biilmann told me.

Given that it has raised quite a bit of money, making acquisitions to accelerate its growth and build out its product makes a lot of sense for Netlify right now. While a few years ago, Netlify still had to explain the concept of the Jamstack, we’ve now seen the rise of a number of competitors, including the likes of Vercel, which itself announced a $150 million Series D round in November — after announcing a $102 million Series C round in June.

This marks Netlify’s third acquisition in total. First, the company acquired the Y Combinator-backed developer collaboration service FeaturePeek in May. In November, it bought GraphQL specialist OneGraph, another Y Combinator graduate, shortly after announcing its $105 million Series D round.

Image Credits: Netlify

“It’s very clear where we want to be and where we want to go,” Biilmann said. “So, of course, it also starts making it interesting when we see opportunities from smaller startups in the space that are doing really cool and interesting stuff that fits into where we want to go and that feel aligned with the vision we have of what the web could be. For some of those, we will find great opportunities to partner and work together — and for some of those we will find that we will work even better together if we just did it all together.”

While the open source project will live on under the Quirrel name, Netlify has already started integrating into its own platform many of the ideas behind the service. The company first launched its serverless platform in 2018. Since then, it has become a core feature of its service, but scheduling functions and background tasks to run on a regular schedule still remained a bit of a hassle for Netlify developers.

Image Credits: Netlify

“Those kinds of jobs are important to what developers want to accomplish,” Billmann explained. “I think Simon [Knott] had really nailed some of the developer experiences around how do you not turn that into a lot of configurations and old school lists of cron jobs? How can you get this to feel more like writing code — and then it happens?”

Netlify, of course, operates at a completely different scale from Quirrel, so it’s maybe no surprise that the team set to rebuild a lot of the infrastructure with a focus on keeping the developer experience aligned with the original vision of Quirrel. Billmann described it as working from first principles, not just because of the company’s scale but also because Netlify has a philosophy of ensuring that the core abstractions of its service don’t depend on specific frameworks (Blitz.js, in Quirrel’s case).

Netlify’s new scheduling features based on the Quirrel user experience are now available for free through Netlify Labs, the company’s platform for beta testing new features. That means some of the features may still change and the team is still thinking about how (and if) it will charge for the service. For now, though, Netlify wants to see how developers will use the service and then build out the product accordingly.

Regardless of your perspective on blockchain-centered projects, venture capitalists appear to have made up their minds about the sector: Investments into crypto-themed companies — the web3 space, as its supporters call it — set records in 2021, records that could be beaten in 2022 if early data indicates where capital will flow this year.

The Exchange explores startups, markets and money.

Read it every morning on TechCrunch+ or get The Exchange newsletter every Saturday.

Data from a new venture capital fund and recent funding rounds underscore the pace of deal flow the crypto market has ahead of it, indicating that bets placed on blockchain-related startups will continue despite some wobbly indicators from the decentralized market.

That there are believers in crypto in the market is not a surprise. The pace of investing may prove to be. For example, early PitchBook data relating to startups it categorizes in the “Cryptocurrency/Blockchain” sector raised around as much this January as all startups in Africa did last year — despite the fact that the African startup investment market is accelerating, as TechCrunch has noted.

This morning, let’s take a look at a few data points showing how rapidly the current pace of investment into crypto-focused startups is shaping up in 2022 and cast a quick glance at issues in the blockchain market that could, but are not, giving investors pause.

To the moon

The recent fundraise by FTX drew a host of headlines. Any time a private company scales its private-market valuation to the range of dozens of billions, it’s hard to ignore. That FTX raised $400 million for its main business — at a $32 billion valuation — less than a week after the company raised $400 million for its U.S.-based operations at an $8 billion valuation did not garner the shock that it should. That’s a simply tectonic sum of cash, and at prices that indicate that FTX sold a total of around 2% of the shares in both companies, or $800 million worth of investment into $40 billion worth of equity value.

But that’s not the only recent news event that underscores how big the crypto bets may prove in 2022. Alexis Ohanian’s Seven Seven Six venture firm just announced $500 million in two funds, that, per The Wall Street Journal, it will “invest primarily in crypto startups.”

Metafy, a startup that operates a marketplace for video game coaching, announced this morning that it has closed a $25 million Series A. Tiger Global and Seven Seven Six led the funding round.

This publication last covered Metafy in May 2021, when the company raised a $5.5 million extension to its preceding $3.15 million seed round.

Since that funding event, Metafy acquired rival games coaching platform GamersRdy, and the company said coaches using its service grossed over $1 million last year. Metafy doesn’t take a cut of coach income when they use its platform; it charges students a 5% fee.

Coached activities on the platform include well-known video game titles and things as far afield from Starcraft as poker and sports betting.

Metafy is a wager that the gaming market will continue to grow, retain its cultural cachet, and that titles popular in the niche will maintain high skill requirements — fodder for coaching demand. With video games becoming increasingly complex over time, and recent mega-dollar acquisitions of gaming studios announced by platform technology companies, the gamble appears to have supporting evidence.

The round

TechCrunch caught up with Metafy co-founder and CEO Josh Fabian to discuss the round, which he described as an early event for his company.

Per Fabian, his company had around half of the money it had raised previously in the bank when it put together its Series A. Why raise before it was a cash-led requirement? Fabian said that changing market conditions led him to secure capital ahead of what could become an investing “winter.”

TechCrunch has noted a rapid decline in the value of publicly traded technology companies and investigated what impact those devaluations may have on startup investment and valuations.

How the round came together is illustrative of the high-tempo fundraising environment of 2021. Fabian said that his first two fundraising events were “stressful and time-consuming.” Metafy’s Series A was different, he said. After speaking to what the CEO described as “household names” in the venture community, Forerunner Ventures introduced him to Tiger Global, which ran a fast, deep vet of his company. This included diligence into individuals from Fabian’s past, seven coaches on the Metafy platform and more. And it was a quick process to boot.

Fabian, rare in his candor among the startup CEO cohort, said that a quick term sheet from Tiger led to his company letting other investors he had spoken to know that Metafy had a deal that it was going to take. Then, Fabian said, other term sheets came rolling in. Thus, it appears that Tiger’s rapid dealmaking is still leaving traditional venture players in hurry-up mode.

Metafy intends to use its new capital for hiring, of course, and more acquisitions. It also demarcated $1 million toward a fund that it will invest over the next 18 to 24 months into competitive tournaments and other gaming-community events.

When TechCrunch covered Metafy’s second seed round, the company had scaled from $76,000 in monthly platform spend in April 2021 to $190,000 in September of last year, up 52% from the preceding month. We’ll be curious to see how quickly the startup can scale its platform GMV this year and whether it can keep up the double-digit month-on-month rates of expansion that it has historically garnered.

GWI, a UK-based tech company — formerly GlobalWebIndex — that’s built up a SaaS business which disrupts traditional offline market research methods with a global network of data contributors, mobile surveys and a self-serve platform for surfacing rich consumer insights to customers that include tech giants like Google, has closed a $180 million Series B at a valuation of more than $850M.

The growth funding round is led by global investment firm Permira — and is only GWI’s second tranche of VC after a $40M Series A back in 2018.

The 2009-founded startup was bootstrapped for years by founder and CEO, Tom Smith, before finally taking external investment a few years ago with the goal of scaling access to its consumer lifestyle and habits data beyond dedicated research teams — to “non expert” professionals who may be working in all sorts of roles right across a business.

“That huge market opportunity needed us to really scale up both the GTM [go-to-market] teams but also engineering teams, build up bigger data sets — that’s what we started to really push the peddle on in 2018. And that was a great success, in terms of scaling up the business. That’s really why we’ve come back now to do a growth round because that market opportunity has got bigger,” Smith tells TechCrunch.

Following its $40M Series A, GWI says it’s tripled recurring revenue and grown to nearly 400 employees based across offices in London, New York, Prague, and Athens. Last year it also opened an office in Singapore.

“It’s a really large market, it’s very global,” he adds on why the company has gone back for a second dip into VC now. “The more capital we have to expand out GTM, data-sets and build world class user interface solutions the quicker we’ll be able to build that traction in the global market.”

Rising competition from ‘no code’ touting research-as-a-service rivals (such as London-based Attest) is also likely giving GWI cause to step on the growth gas.

Smith’s original itch to transform traditional (offline) market research methods — infamous for being slow and costly — led to GWI building out a platform for large scale, high frequency data collection which can serve up instantaneous audience profiling and consumer insights to a roster of customers that includes giants like Facebook and Google (who are hardly short of a bit of personal data themselves). Other customers GWI names include Spotify, Twitter, EA, Red Bull, WPP, and Omnicom.

It says it has around 700 customers at this stage.

“The kind of customers we work with now are very large technology companies and platforms who essentially have all the first party data you can think of but they don’t have the richness of that data — they need independent, rich, profiling data to build a better understanding of customer subsets, and that’s what we provide.”

“The big area of growth for us is enrichment of first party data,” Smith adds. “This is where we match — probabilistically, through similar types of demographics and variables (or in some cases deterministically between IDs) — and in an anoymized way we’re able to enrich their first party data and provide our profiling data.”

GWI’s market research platform is fed by around 22 million “digitally connected” consumers across (currently) 48 countries, who take detailed surveys (meaning there’s opt in consent to use of their data) via third party panel providers which plug into GWI’s platform to continuously supply that core data.

It then does its own weighting and probabilistic matching to extrapolate out from the millions of (pseudonymized) survey responses it receives — to what it describes as “global insights at scale, representing the views of 2.7BN, digitally-connected consumers”; covering data about consumers’ demographics, preferences, and behavioural attitudes — all with the goal of helping customers (major brands, agencies, and media organisations) gain a deeper understanding of their audiences.

“We’re looking at preference, attitudes, lifestyles, brand choices, types of media consumed, demographics — the broad subsets,” says Smith, sketching the broad-brush insights the platform serves up to help customers profile their audiences.

Any direct identifiers are stripped out of the survey response data prior to GWI getting it, per Smith — replaced with a unique ID so it’s still possible for its customers to ask follow up questions via the platform without the individuals needing to be identified to customers or to GWI. So the pitch is ‘privacy safe’ behavioral profiling data at scale.

“What we’re doing really differently — it hasn’t been done before — is that we’ve applied technology to the process of [market research] data collection. So we’re running an incredibly large scale data collection, highly frequent in terms of collection process, delivery to customers and all of that is made available inside a self-service platform… instantaneously accessible. Which is a very unique proposition.”

“Every company needs to understand their target audiences, whether they’re future customers, current customers, or the market place they operate in. And increasingly, as companies move — thanks to the digital world we live in — the possibility to engage and reach customers from anywhere in the world is a very real possibility,” he adds.

“But the challenges of understanding those audiences become massively complicated. And if you use market research — which is what people have done traditionally it’s going to take you months, cost millions of dollars. And you going to end up with a very substandard set of data, ultimately.

“The problem we’re solving is by collecting this massive pool of global data any company, regardless of size, scale or budget, can utilize our data to build a really rich understanding of their target audiences that would be impossible with market research.”

Smith says GWI’s latest chunk of VC funding will go on further expansion of GWI’s geographical reach and demographic depth. Or, put more simply, it’s going to capture more data-points from more consumers in more countries.

“This will enable us to provide instant answers to any question and to better understand people,” he says, adding: “We will represent more communities, particularly in underserved markets and segments than any data set before.

“We currently cover 48 countries, but this will increase to 50 in the coming months, and we’ll be expanding that further and adding more data sets across a range of audiences and verticals. We already cover over 40,000 attributes and over 4,000 brands.”

Another big focus for the funding is on the UX of the platform — with Smith saying they want to make it “even more accessible”.

“We want anyone, regardless of research experience, to be able to answer questions, develop meaningful insights and drive decisions in their day-to-day workflows. Creating insights should be as easy as searching Google; and sharing them and aligning across an organisation should be effortless and embedded whether the company is five people or five million.

“This means major investment in consumer grade UX, machine learning for insights automation, and natural language processing.”

“Most businesses are well aware of the need for a deep understanding of their audiences, but for many, this is still a one-off piece of research undertaken every year,” he adds.

“Market research as an industry has stubbornly refused to evolve, clinging on to high-cost service based models, offline methods, and a lack of scale. We are demystifying audience insight and democratising the data to make global audience insight a reality for any business of any size, without the need for deep research expertise or extensive training.”

While he confirms that a small percentage (1%) of GWI’s customers do also use tracking cookies (and/or pixels) in conjunction with the audience insights its platform surfaces, he’s not concerned about the imminent demise of third party cookies.

In recent years, Google has signalled an intent to deprecate support for tracking technologies in Chrome — via its evolving Privacy Sandbox suite of proposed alternative ad targeting technologies. Other browsers already block third party cookies by default. So the direction of travel of for core web infrastructure is toward a cookie-less future. Which may end up making alternative sources of consumer insight data more valuable.

“GWI’s survey-led data does not rely on cookies to provide audience insights to our customers,” says Smith, adding: “We’re actually excited about the prospect of a cookieless future. It presents so many opportunities for the industry to rethink how it uses behavioural data.

“At GWI we believe strongly that data insights are so much more valuable when they’re based on (or fused with) zero-party data. We know that there are organisations everywhere scrambling to find alternatives to the cookie, many of which appear to be very cookie-esque in nature. Which is probably just kicking the can down the road.

“For GWI, we are focused on proving that probabilistic matching, using really great zero-party data, can be far more effective.”

What does he mean exactly by “zero party data”? Smith says this refers to information that’s been “totally anonymized and can never be linked back to an individual but can be used to drive additional profiling or probabilistic matching”.

“There’s really no way you can tie it back to an individual because of the nature of the data that our customers want us to collect — which is attitudes, lifestyles, outlooks. It’s all the stuff that you can’t collect through behavioral data [i.e. such as tracking cookies] really. You just can’t tie it back to one individual person,” he argues, discussing the robustness of the anonymity.

In theory, if a customer of GWI were to have enough of its own extremely high dimension first party data — on millions or even billions of global consumers (as, for example, Facebook has) — there might, potentially, be a way for a customer to reverse the pseudonymity if they could link individual survey takers to identifiable user accounts on other service/s based on matching/mapping profiled interests.

However as GWI’s platform provides access to aggregated as well as anonymized data it’s indeed hard to see how that could happen. (At least outside of a custom integration that did not aggregate the data or else substantially reduced the level of aggregation and enabled matching with other data-sets.)

“They don’t use our data in this way,” Smiths says of Facebook own use of GWI’s service. “They would use it completely independently to their first party data. They are analyzing our data-sets to provide independent profiling data of their audiences in different countries — and they just work with GWI data in silo. You look at data on an aggregated basis. You look at segments of Facebook users, how likely that they are to engage with specific brands or exhibit specific behaviors — there’s absolutely no linkage to first party data.”

“That’s what 99% of our customers use-cases are — they’re using our data in silo to build insights around audiences which they then translate and use elsewhere,” he adds.

Smith also confirms that the unique IDs GWI receives from panel providers (which would likely still constitute personal data under EU law) are never passed to customers.

“The general movement from GDPR and towards individual privacy has been really good for us because people increasingly having to work with aggregated and anonymized data — which is what is our absolute strength and really core for our proposition,” he adds.

“I started the business in 2009 which was the last really great recession. Obviously we’re going through interesting times now but it’s a very different dynamic to back then. That was a tough environment to build a business. There was no way I was going to raise early stage investment for the idea I brought to market — and also it was a research-based solution, which was very much seen as probably not the future of audience insights.”

Over a decade on from the spark of an idea Smith had, with use of behavioral data facing a rising tide of privacy concern and regulatory control, his bet on modernizing the business of market research — via big data, aggregation and probabilistic modelling — looks well positioned to cater to changing compliance requirements while still being able to serve businesses with valuable consumer insights.

Provided GWI can iterate and evolve its UX fast enough to keep up with ‘no code’ touting rivals that are fast following ballooning demand for research-as-a-service.

“What we’re seeing a demand for is a shift from deterministic data — so ‘I can target this individual’ — to one where it’s probabilistic,” says Smith on changing customer demand. “So… based on data we can see or the attributes we can see through the first party data within the browser, they’re likely to fit this bucket in terms of attitudes and lifestyles. And that probabilistic matching is far easier to make happen — and to do at real scale [which] is what you need for advertising to be effective. And we’re increasingly getting asked to probabilistically match our data.

“The other interesting thing for us is that as more and more media runs through it’s basically being bought on first party deterministic data — directly from Facebook or all the big vendors of advertising space — [and] they’ll use our data to perform the key parts of that strategic planning process: Who is my audience, what do they look like? They’ll build that rich profiling and then take the insights from the audience and just translate those into a platform that has first party or deterministic data.

“They’re not directly matching it but they’re taking the insights to inform the types of audiences they should reach through Facebook or Google or Snap or Twitter or TikTok. The people that own the data directly. You don’t actually need to deterministically match that data — and that’s something that’s really in demand.”

Smith adds that GWI is in the process of rolling out a new feature that will enable customers to push an audience that’s been identified in its platform into Facebook — based on “matching the common variables” — much like Facebook’s own ‘lookalike audience’ ad targeting tool.

“There’s no direct data link but you’re taking commonalities and those commonalities drive your media buy and the audiences you should reach for in Facebook,” says Smith, adding: “And that’s really where the industry is moving in my opinion.

“You’re modelling out probabilistic likelihood that that audience fits the audience you want — and actually more valuable is the insights you derive about who your audience is, they really determine where you should activate your media plan.”

Commenting on GWI’s Series B in a statement, Alex Melamud, principal at Permira, said: “Understanding the digital consumer will continue to be increasingly important to brands, agencies, and media organisations who focus on engaging and acquiring customers through digital channels. Companies competing in today’s marketplace need instant audience insights and we believe GWI’s modern platform and globally, harmonised data set provides a unique solution to any data storyteller. We look forward to leveraging our global platform to support GWI’s continued growth and expansion across international markets.”

In another supporting statement, Ron Shah, partner at New York-based VC Stripes, who led its Series A, added: “GWI’s exceptional products should be in the hands of every professional who wants to better understand their customers and make smarter, data-driven decisions, and this milestone is a powerful step forward for the company. Since our original investment in 2018, Tom and the GWI team have made great strides in delivering a transformative and superior product and we believe they’re just getting started. We’re thrilled to have Permira join us in this journey to make GWI’s ambitions a reality.”

Don’t bootstrap for too long

With GWI trotting along a path that could lead to a unicorn valuation this once bootstrapped startup has come a long way — in time and money — from earlier years, such as when Smith had to take some 200 meetings to nail down its first customer (Microsoft). Evidently there’s been a fair amount of sweat and pain involved in scaling this particular SaaS business. So what tips does Smith have for other bootstrapping founders?

“There are many more avenues for raising capital now. Alternative finance just didn’t exist back then,” he notes, perhaps a little ruefully. “There are some obvious things — you have to keep the business extremely lean. The product at the beginning was fairly rudimentary but it solved one problem for customers which was how to understand their audience on a global basis. Solve that on a small scale.

“You’ve got to try and keep it very focused, very lean — and just try and solve one small problem. Most of what we did in the very early days was more service based. There wasn’t really any technology. We tried to minimize the costs. I was a non-technical founder so that didn’t help. But try and fulfil it as a service to begin with — before you really invest in engineering technology which is obviously very hard to pull off and very expensive.

“You [also] need to consider what product you’re selling. Ultimately we’re selling market research which is a high value product that people will pay a good high ticket for and were used to paying for at the beginning of a payment cycle up front. Not all products would suit that. So you need to understand the dynamics of what you’re selling and if it would suit that model. It worked for us — but it’ll only get you so far. At some point if you’re really going to scale you’ve got to spend more than you’re bringing through the door, basically.”

“I probably wouldn’t have bootstrapped for quite as long as I did,” Smith adds. “Try to get to a position of funding earlier.”

GWI, a UK-based tech company — formerly GlobalWebIndex — that’s built up a SaaS business which disrupts traditional offline market research methods with a global network of data contributors, mobile surveys and a self-serve platform for surfacing rich consumer insights to customers that include tech giants like Google, has closed a $180 million Series B at a valuation of more than $850M.

The growth funding round is led by global investment firm Permira — and is only GWI’s second tranche of VC after a $40M Series A back in 2018.

The 2009-founded startup was bootstrapped for years by founder and CEO, Tom Smith, before finally taking external investment a few years ago with the goal of scaling access to its consumer lifestyle and habits data beyond dedicated research teams — to “non expert” professionals who may be working in all sorts of roles right across a business.

“That huge market opportunity needed us to really scale up both the GTM [go-to-market] teams but also engineering teams, build up bigger data sets — that’s what we started to really push the peddle on in 2018. And that was a great success, in terms of scaling up the business. That’s really why we’ve come back now to do a growth round because that market opportunity has got bigger,” Smith tells TechCrunch.

Following its $40M Series A, GWI says it’s tripled recurring revenue and grown to nearly 400 employees based across offices in London, New York, Prague, and Athens. Last year it also opened an office in Singapore.

“It’s a really large market, it’s very global,” he adds on why the company has gone back for a second dip into VC now. “The more capital we have to expand out GTM, data-sets and build world class user interface solutions the quicker we’ll be able to build that traction in the global market.”

Rising competition from ‘no code’ touting research-as-a-service rivals (such as London-based Attest) is also likely giving GWI cause to step on the growth gas.

Smith’s original itch to transform traditional (offline) market research methods — infamous for being slow and costly — led to GWI building out a platform for large scale, high frequency data collection which can serve up instantaneous audience profiling and consumer insights to a roster of customers that includes giants like Facebook and Google (who are hardly short of a bit of personal data themselves). Other customers GWI names include Spotify, Twitter, EA, Red Bull, WPP, and Omnicom.

It says it has around 700 customers at this stage.

“The kind of customers we work with now are very large technology companies and platforms who essentially have all the first party data you can think of but they don’t have the richness of that data — they need independent, rich, profiling data to build a better understanding of customer subsets, and that’s what we provide.”

“The big area of growth for us is enrichment of first party data,” Smith adds. “This is where we match — probabilistically, through similar types of demographics and variables (or in some cases deterministically between IDs) — and in an anoymized way we’re able to enrich their first party data and provide our profiling data.”

GWI’s market research platform is fed by around 22 million “digitally connected” consumers across (currently) 48 countries, who take detailed surveys (meaning there’s opt in consent to use of their data) via third party panel providers which plug into GWI’s platform to continuously supply that core data.

It then does its own weighting and probabilistic matching to extrapolate out from the millions of (pseudonymized) survey responses it receives — to what it describes as “global insights at scale, representing the views of 2.7BN, digitally-connected consumers”; covering data about consumers’ demographics, preferences, and behavioural attitudes — all with the goal of helping customers (major brands, agencies, and media organisations) gain a deeper understanding of their audiences.

“We’re looking at preference, attitudes, lifestyles, brand choices, types of media consumed, demographics — the broad subsets,” says Smith, sketching the broad-brush insights the platform serves up to help customers profile their audiences.

Any direct identifiers are stripped out of the survey response data prior to GWI getting it, per Smith — replaced with a unique ID so it’s still possible for its customers to ask follow up questions via the platform without the individuals needing to be identified to customers or to GWI. So the pitch is ‘privacy safe’ behavioral profiling data at scale.

“What we’re doing really differently — it hasn’t been done before — is that we’ve applied technology to the process of [market research] data collection. So we’re running an incredibly large scale data collection, highly frequent in terms of collection process, delivery to customers and all of that is made available inside a self-service platform… instantaneously accessible. Which is a very unique proposition.”

“Every company needs to understand their target audiences, whether they’re future customers, current customers, or the market place they operate in. And increasingly, as companies move — thanks to the digital world we live in — the possibility to engage and reach customers from anywhere in the world is a very real possibility,” he adds.

“But the challenges of understanding those audiences become massively complicated. And if you use market research — which is what people have done traditionally it’s going to take you months, cost millions of dollars. And you going to end up with a very substandard set of data, ultimately.

“The problem we’re solving is by collecting this massive pool of global data any company, regardless of size, scale or budget, can utilize our data to build a really rich understanding of their target audiences that would be impossible with market research.”

Smith says GWI’s latest chunk of VC funding will go on further expansion of GWI’s geographical reach and demographic depth. Or, put more simply, it’s going to capture more data-points from more consumers in more countries.

“This will enable us to provide instant answers to any question and to better understand people,” he says, adding: “We will represent more communities, particularly in underserved markets and segments than any data set before.

“We currently cover 48 countries, but this will increase to 50 in the coming months, and we’ll be expanding that further and adding more data sets across a range of audiences and verticals. We already cover over 40,000 attributes and over 4,000 brands.”

Another big focus for the funding is on the UX of the platform — with Smith saying they want to make it “even more accessible”.

“We want anyone, regardless of research experience, to be able to answer questions, develop meaningful insights and drive decisions in their day-to-day workflows. Creating insights should be as easy as searching Google; and sharing them and aligning across an organisation should be effortless and embedded whether the company is five people or five million.

“This means major investment in consumer grade UX, machine learning for insights automation, and natural language processing.”

“Most businesses are well aware of the need for a deep understanding of their audiences, but for many, this is still a one-off piece of research undertaken every year,” he adds.

“Market research as an industry has stubbornly refused to evolve, clinging on to high-cost service based models, offline methods, and a lack of scale. We are demystifying audience insight and democratising the data to make global audience insight a reality for any business of any size, without the need for deep research expertise or extensive training.”

While he confirms that a small percentage (1%) of GWI’s customers do also use tracking cookies (and/or pixels) in conjunction with the audience insights its platform surfaces, he’s not concerned about the imminent demise of third party cookies.

In recent years, Google has signalled an intent to deprecate support for tracking technologies in Chrome — via its evolving Privacy Sandbox suite of proposed alternative ad targeting technologies. Other browsers already block third party cookies by default. So the direction of travel of for core web infrastructure is toward a cookie-less future. Which may end up making alternative sources of consumer insight data more valuable.

“GWI’s survey-led data does not rely on cookies to provide audience insights to our customers,” says Smith, adding: “We’re actually excited about the prospect of a cookieless future. It presents so many opportunities for the industry to rethink how it uses behavioural data.

“At GWI we believe strongly that data insights are so much more valuable when they’re based on (or fused with) zero-party data. We know that there are organisations everywhere scrambling to find alternatives to the cookie, many of which appear to be very cookie-esque in nature. Which is probably just kicking the can down the road.

“For GWI, we are focused on proving that probabilistic matching, using really great zero-party data, can be far more effective.”

What does he mean exactly by “zero party data”? Smith says this refers to information that’s been “totally anonymized and can never be linked back to an individual but can be used to drive additional profiling or probabilistic matching”.

“There’s really no way you can tie it back to an individual because of the nature of the data that our customers want us to collect — which is attitudes, lifestyles, outlooks. It’s all the stuff that you can’t collect through behavioral data [i.e. such as tracking cookies] really. You just can’t tie it back to one individual person,” he argues, discussing the robustness of the anonymity.

In theory, if a customer of GWI were to have enough of its own extremely high dimension first party data — on millions or even billions of global consumers (as, for example, Facebook has) — there might, potentially, be a way for a customer to reverse the pseudonymity if they could link individual survey takers to identifiable user accounts on other service/s based on matching/mapping profiled interests.

However as GWI’s platform provides access to aggregated as well as anonymized data it’s indeed hard to see how that could happen. (At least outside of a custom integration that did not aggregate the data or else substantially reduced the level of aggregation and enabled matching with other data-sets.)

“They don’t use our data in this way,” Smiths says of Facebook own use of GWI’s service. “They would use it completely independently to their first party data. They are analyzing our data-sets to provide independent profiling data of their audiences in different countries — and they just work with GWI data in silo. You look at data on an aggregated basis. You look at segments of Facebook users, how likely that they are to engage with specific brands or exhibit specific behaviors — there’s absolutely no linkage to first party data.”

“That’s what 99% of our customers use-cases are — they’re using our data in silo to build insights around audiences which they then translate and use elsewhere,” he adds.

Smith also confirms that the unique IDs GWI receives from panel providers (which would likely still constitute personal data under EU law) are never passed to customers.

“The general movement from GDPR and towards individual privacy has been really good for us because people increasingly having to work with aggregated and anonymized data — which is what is our absolute strength and really core for our proposition,” he adds.

“I started the business in 2009 which was the last really great recession. Obviously we’re going through interesting times now but it’s a very different dynamic to back then. That was a tough environment to build a business. There was no way I was going to raise early stage investment for the idea I brought to market — and also it was a research-based solution, which was very much seen as probably not the future of audience insights.”

Over a decade on from the spark of an idea Smith had, with use of behavioral data facing a rising tide of privacy concern and regulatory control, his bet on modernizing the business of market research — via big data, aggregation and probabilistic modelling — looks well positioned to cater to changing compliance requirements while still being able to serve businesses with valuable consumer insights.

Provided GWI can iterate and evolve its UX fast enough to keep up with ‘no code’ touting rivals that are fast following ballooning demand for research-as-a-service.

“What we’re seeing a demand for is a shift from deterministic data — so ‘I can target this individual’ — to one where it’s probabilistic,” says Smith on changing customer demand. “So… based on data we can see or the attributes we can see through the first party data within the browser, they’re likely to fit this bucket in terms of attitudes and lifestyles. And that probabilistic matching is far easier to make happen — and to do at real scale [which] is what you need for advertising to be effective. And we’re increasingly getting asked to probabilistically match our data.

“The other interesting thing for us is that as more and more media runs through it’s basically being bought on first party deterministic data — directly from Facebook or all the big vendors of advertising space — [and] they’ll use our data to perform the key parts of that strategic planning process: Who is my audience, what do they look like? They’ll build that rich profiling and then take the insights from the audience and just translate those into a platform that has first party or deterministic data.

“They’re not directly matching it but they’re taking the insights to inform the types of audiences they should reach through Facebook or Google or Snap or Twitter or TikTok. The people that own the data directly. You don’t actually need to deterministically match that data — and that’s something that’s really in demand.”

Smith adds that GWI is in the process of rolling out a new feature that will enable customers to push an audience that’s been identified in its platform into Facebook — based on “matching the common variables” — much like Facebook’s own ‘lookalike audience’ ad targeting tool.

“There’s no direct data link but you’re taking commonalities and those commonalities drive your media buy and the audiences you should reach for in Facebook,” says Smith, adding: “And that’s really where the industry is moving in my opinion.

“You’re modelling out probabilistic likelihood that that audience fits the audience you want — and actually more valuable is the insights you derive about who your audience is, they really determine where you should activate your media plan.”

Commenting on GWI’s Series B in a statement, Alex Melamud, principal at Permira, said: “Understanding the digital consumer will continue to be increasingly important to brands, agencies, and media organisations who focus on engaging and acquiring customers through digital channels. Companies competing in today’s marketplace need instant audience insights and we believe GWI’s modern platform and globally, harmonised data set provides a unique solution to any data storyteller. We look forward to leveraging our global platform to support GWI’s continued growth and expansion across international markets.”

In another supporting statement, Ron Shah, partner at New York-based VC Stripes, who led its Series A, added: “GWI’s exceptional products should be in the hands of every professional who wants to better understand their customers and make smarter, data-driven decisions, and this milestone is a powerful step forward for the company. Since our original investment in 2018, Tom and the GWI team have made great strides in delivering a transformative and superior product and we believe they’re just getting started. We’re thrilled to have Permira join us in this journey to make GWI’s ambitions a reality.”

Don’t bootstrap for too long

With GWI trotting along a path that could lead to a unicorn valuation this once bootstrapped startup has come a long way — in time and money — from earlier years, such as when Smith had to take some 200 meetings to nail down its first customer (Microsoft). Evidently there’s been a fair amount of sweat and pain involved in scaling this particular SaaS business. So what tips does Smith have for other bootstrapping founders?

“There are many more avenues for raising capital now. Alternative finance just didn’t exist back then,” he notes, perhaps a little ruefully. “There are some obvious things — you have to keep the business extremely lean. The product at the beginning was fairly rudimentary but it solved one problem for customers which was how to understand their audience on a global basis. Solve that on a small scale.

“You’ve got to try and keep it very focused, very lean — and just try and solve one small problem. Most of what we did in the very early days was more service based. There wasn’t really any technology. We tried to minimize the costs. I was a non-technical founder so that didn’t help. But try and fulfil it as a service to begin with — before you really invest in engineering technology which is obviously very hard to pull off and very expensive.

“You [also] need to consider what product you’re selling. Ultimately we’re selling market research which is a high value product that people will pay a good high ticket for and were used to paying for at the beginning of a payment cycle up front. Not all products would suit that. So you need to understand the dynamics of what you’re selling and if it would suit that model. It worked for us — but it’ll only get you so far. At some point if you’re really going to scale you’ve got to spend more than you’re bringing through the door, basically.”

“I probably wouldn’t have bootstrapped for quite as long as I did,” Smith adds. “Try to get to a position of funding earlier.”

AirTree partners (from l to r): From left to right: James Cameron, John Henderson, Elicia McDonald, Jackie Vullinghs, Craig Blair and Helen Norton

More money is flowing into Australia and New Zealand’s startup ecosystems. Sydney-based AirTree Ventures, one of the region’s most prolific VC firms, announced it has raised $700 million AUD (about $493 million USD), to be divided between three investment vehicles. These include a $200 million AUD for early-stage companies that AirTree says is Australia’s largest-ever seed fund; a $50 million AUD fund earmarked for Web3 startups; and $450 million AUD for growth-stage companies, including ones headed for an initial public offering.

Founded in 2014, AirTree now manages a total of $1.3 billion AUD and has more than 80 active investments. Out of that number, 23 are valued at more than $100 million and include eight unicorns. The new round was oversubscribed and much of it came from returning investors, including cornerstone LPs, superannuation funds AustralianSuper, Sunsuper, TelstraSuper and Statewide Super, said AirTree co-founder and partner Craig Blair.

Some of AirTree’s best-known investments include Canva and A Cloud Guru. The last funding AirTree raised was a total of $300 million AUD for seed and growth rounds that closed in 2019. About 70% of that went to early-stage startups including Mr. Yum, Linktree and MILKRUN.

“We’ve been in this space for coming up to ten years now and we’ve seen more and more exciting founders tackling huge global markets,” said Blair. “We see 1,000 potential investments a year and invest to 10 to 20 of them and we think one or two of those will go on a billion dollar outcome.” AirTree is sector agnostic, but Blair named SaaS, agriculture, mining and government as particularly exciting ones to find the firm’s next early-stage investments.

AirTree works closely with portfolio companies, often helping them recruit key talent, working on public relations and their pricing strategies. It also has a community forum made up of experts and portfolio founders.

“The exciting thing about the Australian ecosystem at the moment is we are at the point where there’s enough repeat and successful founders who are willing to give their time and resources back to helping the next generation,” said AirTree partner Elicia McDonald. She added “we definitely don’t have a spray and pray mentality, and we’re very focused on our portfolio success, their teams and providing support from the earliest stages.”

The Web3 fund will focus on decentralized finance (DeFi), NFTs and decentralized autonomous organizations (DAO). AirTree has already made five investments in the space, ranging from Immutable, the NFT infrastructure startup, to DeFi projects.

McDonald said AirTree has been looking at the crypto space since it launched seven years ago, but didn’t feel like it was an investable asset class for the firm until recently. “The view there was that crypto was in the installation phase, so the infrastructure was still being built and the real use cases were still to come,” she said. “For us, that tipped over and changed in the middle of 2020, with the rise of decentralized finance and NFTs. We’re well aware that the crypto markets will continue to be a bit of a rollercoaster, but we’re focused on making long-term bets in that space and seeing through the cycles.”

Capital from the growth fund will go primarily toward AirTree’s portfolio companies as they scale up into Series B and further stages, but Blair said the firm occasionally invests in other companies out of the growth fund.

With the launch of their new funds, AirTree’s partners underscored that diversity, equality and inclusion is tenet at the firm, which has as 50/50 split between men and women among their partners and broader team. McDonald said AirTree tracks its funnel at each stage of the investment process for a mix of gender and ethnicity among founders, and then at each stage of the fund.

“We take our responsibility as a leader in this industry very seriously,” she said. “Our approach is to the change we want to see and set the standards for the industry, and there’s always more that can be done.”

Urban mobility startup Dott has raised an extension to its Series B round. Originally announced in the Spring of 2021, the company raised an $85 million Series B round — it was a mix of equity and asset-backed debt financing. And today, the company is adding another $70 million to this round —once again, it’s a mix of equity and debt.

Dott is a European micromobility startup that is better known for its scooter-sharing service. More recently, the company also added an electric bike-sharing service in some cities.

abrdn is leading the Series B extension with Dott’s existing investor Sofina. Other existing investors put more money on the table, such as EQT Ventures and Prosus Ventures.

Dott competes with several micromobility startups in Europe. Its most direct competitors are Tier, Lime and Voi. There are quite similar when it comes to pricing and scooters — most of them work with Okai to design their scooters. But they don’t necessarily operate in the same markets.

Right now, Dott covers 36 cities across nine European countries. The company manages 40,000 scooters and 10,000 bikes. While Dott isn’t sharing revenue numbers, the startup processed 130% more trips in 2021 compared to 2020.

Two other differentiating factors between micromobility operators are logistics and regulation. When it comes to logistics, Dott tries to internalize its processes as much as possible. It doesn’t work with third-party logistics providers and it has its own warehouses and repair teams to take care of its fleet.

When it comes to regulation, the company has won several permits to operate in highly coveted markets, such as Paris and London. However, Paris is currently trying to heavily regulate scooter-sharing services in Paris with a new top speed of… 10 km/h (that’s 6.2 mph). There are currently 700 slow zones in Paris with a top speed of 10 km/h.

There are two key takeaways here. First, building a micromobility company requires a ton of capital. It shouldn’t come as a surprise as buying scooters is expensive, charging batteries is expensive and hiring people to make everything run smoothly is expensive.

Second, the regulatory landscape is still evolving and there are still some uncertainties for scooter startups. Dott is diversifying its product offering with electric bikes — and that seems like a smart move. It’s also going to be interesting to see how it plans to optimize battery charging even more to make its service more cost effective.

Deepnote, a startup that is building a data science platform on top of Jupyter-compatible notebooks, today announced that it has raised a $20 million Series A round co-led by Index Ventures and Accel, both of which also participated in its 2020 seed round. Existing investors Y Combinator and Credo Ventures also participated in this round.

As Deepnote co-founder and CEO Jakub Jurovych told me, the company has pretty much stayed true to its original vision since its launch a couple of years ago.

“When we started out, we were coming from this data science and machine learning background,” Jurovych explained. “We were pretty confident that something needed to change in the data science space because we tried everything out there — like all the tools you could possibly imagine — the collaboration was always broken, no matter what we tried.”

The team, which includes co-founder Jan Matas (CTO) and Filip Stollar (Head of Design), was already quite familiar with Jupyter notebooks and set to work on bringing easier ways to collaborate to this existing tool.

Image Credits: Deepnote

In many ways, Deepnote has become the de-facto standard for shared data science notebooks. Companies like ByteDance, Discord and Gusto now use the company’s platform and since the data science market is growing quickly, yet talent remains hard to find, the team also made a concerted effort to bring its tools to students. Today, 80 out of the top 100 universities in the world use Deepnote in at least some of their classes.

“The pain that students and teachers our feeling is pretty much the same thing that you see at organizations. “You have the same need to collaborate,” Jurovych said. And just like a professor is able to use the tool to distribute an assignment to hundreds of students, enterprise users can now share their notebooks with anybody else inside the company, including C-level executives. Indeed, Jurovych believes that notebooks — as a format — are able to breach the gap between technical and non-technical audiences. So while Deepnote specifically targets data scientists, one of the teams’ goals is to lower the barrier of entry for using notebooks (while staying fully compatible with the Jupyter standard).

“Two years ago, you would have to know how to write Python to get any value out of the notebooks,” Jurovych said. “Today, you just receive a link from someone else who is technical on the team and if you want to tweak the visualization, it’s actually a pretty simple thing to do. If you want to leave a comment, provide some feedback, you don’t have to be the most technical person in the world.”

Deepnote offers a free tier, with a paid Pro plans starting at $12/month/editor that is also available for free for students and teachers.

The remote-first company plans to use the new funding to build out its product and expand its foothold in the data science community. In the process, Jurovych expects to double the teams’ size to about 50 employees in the next 12 months.

Deepnote, a startup that is building a data science platform on top of Jupyter-compatible notebooks, today announced that it has raised a $20 million Series A round co-led by Index Ventures and Accel, both of which also participated in its 2020 seed round. Existing investors Y Combinator and Credo Ventures also participated in this round.

As Deepnote co-founder and CEO Jakub Jurovych told me, the company has pretty much stayed true to its original vision since its launch a couple of years ago.

“When we started out, we were coming from this data science and machine learning background,” Jurovych explained. “We were pretty confident that something needed to change in the data science space because we tried everything out there — like all the tools you could possibly imagine — the collaboration was always broken, no matter what we tried.”

The team, which includes co-founder Jan Matas (CTO) and Filip Stollar (Head of Design), was already quite familiar with Jupyter notebooks and set to work on bringing easier ways to collaborate to this existing tool.

Image Credits: Deepnote

In many ways, Deepnote has become the de-facto standard for shared data science notebooks. Companies like ByteDance, Discord and Gusto now use the company’s platform and since the data science market is growing quickly, yet talent remains hard to find, the team also made a concerted effort to bring its tools to students. Today, 80 out of the top 100 universities in the world use Deepnote in at least some of their classes.

“The pain that students and teachers our feeling is pretty much the same thing that you see at organizations. “You have the same need to collaborate,” Jurovych said. And just like a professor is able to use the tool to distribute an assignment to hundreds of students, enterprise users can now share their notebooks with anybody else inside the company, including C-level executives. Indeed, Jurovych believes that notebooks — as a format — are able to breach the gap between technical and non-technical audiences. So while Deepnote specifically targets data scientists, one of the teams’ goals is to lower the barrier of entry for using notebooks (while staying fully compatible with the Jupyter standard).

“Two years ago, you would have to know how to write Python to get any value out of the notebooks,” Jurovych said. “Today, you just receive a link from someone else who is technical on the team and if you want to tweak the visualization, it’s actually a pretty simple thing to do. If you want to leave a comment, provide some feedback, you don’t have to be the most technical person in the world.”

Deepnote offers a free tier, with a paid Pro plans starting at $12/month/editor that is also available for free for students and teachers.

The remote-first company plans to use the new funding to build out its product and expand its foothold in the data science community. In the process, Jurovych expects to double the teams’ size to about 50 employees in the next 12 months.