Tractable
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Extra Crunch roundup: Finding GTM, China’s edtech clampdown and how to define growth
Early-stage startups tend to claim that their go-to-market strategy is fully operational. In reality, GTM is a stark numbers game, and even with a solid plan in place, it can be easily foiled by common problems like turf battles and poor communication.
Finding GTM fit is a milestone for any startup that includes everything from expanding the engineering team to launching your first media buy. But how do you know when you’ve reached that magic moment?
“You have to consider three metrics: gross churn rate, the magic number and gross margin,” says Tae Hea Nahm, co-founder and managing director of Storm Ventures.
High churn means customers aren’t delighted, low gross margins mean poor unit economics, and that so-called magic number?
“You can calculate it by taking new ARR divided by your marketing and sales spending,” Nahm writes. “But keep in mind that the magic number is a lagging indicator, and it may take you a few quarters to see a positive result.”
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Use discount code ECFriday to save 20% off a one- or two-year subscription.
If you are methodical in your approach to building a larger customer base, it is not difficult to foster steady growth.
Marketers who shift with whichever way the wind is blowing — or blindly follow someone else’s idea of best practices — are less likely to be successful.
“The not-so-secret secret here is that the key to great retention is really simple,” said growth expert Susan Su recently at TechCrunch Early Stage: Marketing and Fundraising. “It is building a product that solves a real and especially persistent problem for people.”
In conversation with Managing Editor Eric Eldon, Su delved into several issues, including tips on how founders should discuss growth with investors, and her methods for developing a sample qualitative growth model.
“I firmly believe that every founder should try their hand at growth,” said Su.
Thanks very much for reading Extra Crunch this week!
Walter Thompson
Senior Editor, TechCrunch
@yourprotagonist
How we built an AI unicorn in 6 years
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Few startups go to market with the exact product their founders first envisioned.
Today, Tractable is known for developing tech that allows drivers to upload photos of their vehicles after a collision so its AI can assess the damage. Its first paying customer, however, used Tractable to inspect plastic pipe welds.
And as fate would have it, that customer also fired them just as the founders were raising their first round.
“We struck gold with car insurance,” says co-founder Alex Dalyac, as it was “a huge and inefficient market in desperate need of modernization.”
In an Extra Crunch guest post, he shares several takeaways from the last six years spent scaling a unicorn that have value for founders of all stripes. Step one?
“Search for complementary co-founders who will become your best friends,” advises Dalyac.
The European VC market is so hot it may skip its summer holiday
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Alex Wilhelm and Anna Heim continued their exploration of the scorching global VC market, this time taking a look at Europe.
For perspective, they analyzed data from Dealroom and spoke to four VCs about the continent’s investment climate:
- Diana Koziarska, SMOK Ventures
- Vinoth Jayakumar, Draper Esprit
- Simon Schmincke, Creandum
- Javier Santiso, Mundi Ventures
“There’s little indication that what we’ve seen thus far from Europe in 2021 will slow in Q3 or Q4,” Alex and Anna write.
“Even though Europe has a reputation for lengthy summer vacations, investors don’t expect much — if any — slowdown to come in Europe during this sun-drenched quarter.”
Startups and investors are turning to micromobility subscriptions
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“Amid the chaos of the COVID-19 pandemic and the murky path to profitability for shared electric micromobility, an increasing number of companies have turned to subscriptions,” Rebecca Bellan writes in a roundup about the future of micromobility.
“It’s a business model that some founders and investors argue hits the profit center sweet spot — an approach that appeals to customers who are wary of sharing as well as paying upfront to own a scooter or e-bike, all while minimizing overhead costs and depreciation of assets.”
What Robinhood’s warnings about crypto trading say about Coinbase’s near-term future
Image Credits: Nigel Sussman (opens in a new window)
After noting that Robinhood anticipates a decline in revenue in the third quarter as a result of slowing crypto trading, Alex Wilhelm got to thinking about what that forecast means for Coinbase.
“The now-public unicorn has lived through crypto ups and crypto downs,” he writes. “A decline in consumer interest in the next few months or quarters is not a huge deal, assuming one keeps a long enough perspective and the crypto-infused future that its fans expect comes to pass.”
But will it?
Dear Sophie: Should we look to Canada to retain international talent?
Image Credits: Bryce Durbin/TechCrunch
Dear Sophie,
I handle people ops as a consultant at several different tech startups. Many have employees on OPT or STEM OPT who didn’t get selected in this year’s H-1B lottery.
The companies want to retain these individuals, but they’re running out of options. Some companies will try again in next year’s H-1B lottery, even though they face long odds, particularly if the H-1B lottery becomes a wage-based selection process next year.
Others are looking into O-1A visas, but find that many employees don’t yet have the experience to meet the qualifications. Should we look at Canada?
— Specialist in Silicon Valley
Silicon Valley comms expert Caryn Marooney shares how to nail the narrative
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Caryn Marooney, a Silicon Valley communications professional turned venture capitalist, spoke extensively on storytelling at TechCrunch Early Stage: Marketing and Fundraising.
Throughout her time in Silicon Valley, she helped companies like Salesforce, Amazon, Facebook and more launch products and sharpen their messaging. In 2019, she left Facebook, where she was VP of technology communication, and joined Coatue Management as a general partner.
Marooney uses the acronym RIBS to describe her basic strategy for startup messaging: Relevance, Inevitability, Believability and keeping it Simple.
Canada’s startup market booms alongside hot global VC investment
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For The Exchange, Alex Wilhelm and Anna Heim looked at Canada’s VC market in the first half of 2021, and if you’ve been reading their work, you know what’s coming.
Canada, like the rest of the globe, was absolutely scorching in the first half.
“Canada’s venture capital results now rival those of the entire Latin American region, with exits and mega-deals coming in roughly on par in the second quarter, and a similar number of total venture capital rounds in the period,” they write.
“That caught our attention.”
Greylock’s Mike Duboe explains how to define growth and build your team
With more venture funding flowing into the startup ecosystem than ever before, there’s never been a better time to be a growth expert.
At TechCrunch Early Stage: Marketing and Fundraising earlier this month, Greylock Partners’ Mike Duboe dug into a number of lessons and pieces of wisdom he’s picked up leading growth at a number of high-growth startups, including StitchFix. His advice spanned hiring, structure and analysis, with plenty of recommendations for where growth teams should be focusing their attention and resources.
Last-mile delivery in Latin America is ready to take off
Image Credits: Erlon Silva/TRI Digital (opens in a new window) / Getty Images
Thanks to sprawling fulfillment centers, seamless logistics networks and ubiquitous internet access, consumers in many regions can now order groceries and a new set of cookware during breakfast and reasonably expect everything to arrive in time for dinner.
In Latin America, a lack of technology infrastructure makes delivery operations complex, and these supply chains are often managed with spreadsheets, paper and pen.
Algorithms that manage delivery routes or automatically dispatch drivers “are almost unheard of in the Latin America retail logistics sector,” says Bob Ma, an investor at WIND Ventures.
But thanks to growing consumer demand and expanding investment in last-mile delivery startups, Ma says the region is at a turning point.
Since Latin America’s middle class has grown 50% in the last decade and e-commerce constitutes just 6% of all retail, several unicorns have emerged in recent years, with more waiting in the wings.
China’s expected edtech clampdown may chill a key startup sector
Image Credits: Nigel Sussman (opens in a new window)
China’s edtech industry is estimated to be worth $100 billion, but its leaders are reportedly considering a plan that would require these firms to operate as non-profits.
“When it comes to control, the Chinese government doesn’t mind wiping out a few dozen billion dollars in market cap here and there,” writes Alex Wilhelm in this morning’s edition of The Exchange.
“That’s not a great system.”
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Tractable raises $60M at a $1B valuation to make damage appraisals using AI
As the insurance industry adjusts to life in the 21st century (heh), an AI startup that has built computer vision tools to enable remote damage appraisals is announcing a significant round of growth funding.
Tractable, which works with automotive insurance companies to let users take and submit photos of damaged cars that are then “read” to make appraisals, has raised $60 million, a Series D that values Tractable at $1 billion, the company said.
Tractable says it works with more than 20 of the top 100 auto insurers in the world, and it has seen sales grow 600% in the last 24 months, which CEO Alex Dalyac told me translates as “well into eight figures of annual revenue.” He also told me that “we would have grown even faster if it weren’t for COVID.” People staying at home meant far fewer people on the roads, and fewer accidents.
Its business today is based mostly around car accident recovery — where users can take pictures using ordinary smartphone cameras, uploading pictures via a mobile web site (not typically an app).
But Tractable’s plan is to use some of the funding to expand deeper into areas adjacent to that: natural disaster recovery (specifically for appraising property damage), and used car appraisals. It will also use the investment to continue building out its technology, specifically to help build out better, AI-based techniques of processing and parsing pictures that are taken on smartphones — by their nature small in size.
Insight Partners and Georgian Partners co-led the round and it brings the total raised by the company to $115 million.
Dalyac, a deep learning researcher by training who co-founded the company with Razvan Ranca and Adrien Cohen, said that the “opportunity” (if you could call an accident that) Tractable has identified and built to fix is that it’s generally time-consuming and stressful to deal with an insurance company when you are also coping with a problem with your car.
And while a new generation of “insurtech” startups have emerged in recent years that are bringing more modern processes into the equation, typically the incumbent major insurance companies — the ones that Tractable targets — have lacked the technology to improve that process.
It’s not unlike the tension between fintech-fuelled neobanks and the incumbent banks, which are now scrambling to invest in more technology to catch up with the times.
“Getting into an accident can be anything from a hassle to trauma,” Dalyac said. “It can be devastating, and then the process for recovery is pretty damn slow. You’re dealing with so many touch points with your insurance, so many people that need to come and check things out again. It’s hard to keep track and know when things will truly be back to normal. Our belief is that that whole process can be 10 times faster, thanks to the breakthroughs in image classification.”
That process currently also extends not just to taking pictures for claims, but also to help figure out when a car is beyond repair, in which case which parts can be recycled and reused elsewhere, also using Tractable’s computer vision technology. Dalyac noted that this was a popular enough service in the last year that the company helped recycle as many cars “as Tesla sold in 2019.”
Customers that have integrated with Tractable to date include Geico in the U.S., as well as a large swathe of insurers in Japan, specifically Tokio Marine Nichido, Mitsui Sumitomo, Aioi Nissay Dowa and Sompo. Covéa, the largest auto insurer in France, is also a customer, as is Admiral Seguros, the Spanish entity of U.K.’s Admiral Group, as well as Ageas, a top U.K. insurer.
Japan is the company’s biggest market today Dalyac said — the reason being that it has an aging population, but one that is also very strong on mobile usage: combining those two, “automation is more than a value add; it’s a must have,” Dalyac said. He also added that he thinks the U.S. will overtake Japan as Tractable’s biggest market soon.
The new directions into property and other car applications will also open the door to a wider set of use cases beyond working with insurance providers over time. It will also bring Tractable potentially into new competitive environments. There are other companies that have also identified this opportunity.
For example, Hover, which has built a way to create 3D imagery of homes using ordinary smartphone cameras, is also eyeing ways of selling its tech (originally developed to help make estimates on home repairs) to insurance companies.
For now, however, it sounds like the opportunity is a big enough one that the race is more to meet demand than it is to beat competitors to do so.
“Tractable’s accelerating growth at scale is a testament to the power and differentiation of their applied machine learning system, which continues to improve as more businesses adopt it,” said Lonne Jaffe, MD at Insight Partners and Tractable board member, in a statement. “We’re excited to double down on our partnership with Tractable as they work to help the world recover faster from accidents and disasters that affect hundreds of millions of lives.”
Emily Walsh, partner at Georgian Partners added: “Tractable’s industry-leading computer vision capabilities are continuing to fuel incredible customer ROI and growth for the firm. We’re excited to continue to partner with Tractable as they apply their artificial intelligence capabilities to new, multi-billion dollar market opportunities in the used vehicle and natural disaster recovery industries.”
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Tractable is applying AI to accident and disaster appraisal
“Happy to spend 10 minutes on our vision and the journey we’re on, but then, really, 15 minutes on what we’ve got today, what it is we’ve achieved, what it is our AI does,” says Tractable co-founder and CEO Alexandre Dalyac when I video called him a couple of weeks ago. “You can probably speed up all of that,” I quip back.
The resulting conversation, lasting well over an hour, spanned all of the above and more, including what is required to build a successful AI business and why he and his team think they can help prevent another “AI winter.”
Founded in 2014 by Dalyac, Adrien Cohen and Razvan Ranca after going through company builder Entrepreneur First, London-based Tractable is applying artificial intelligence to accident and disaster recovery. Specifically, through the use of deep learning to automate visual damage appraisal, and therefore help speed up insurance payouts and access to other types of financial aid.
Our AI has already been trained on tens of millions of these cases, so that’s a perfect case of us already having distilled thousands of people’s work experience Alexandre Dalyac
Dalyac launches into what is clearly a well-rehearsed and evidently polished pitch. “We are on a journey to help the world recover faster from accidents and disasters. Our belief is that when accidents and disasters hit, the response could be 10 times faster thanks to AI. So what we mean there is, everything from road accidents, burst piping to large-scale floods and hurricane. Whenever any of these things happen, things get damaged.”
Those things, he says, broadly break down into cars, homes and crops, roughly equating to $1 trillion in damage each year. But, perhaps more importantly, livelihoods get impacted.
“If a car gets damaged, mobility is reduced. If a home gets damaged, shelter is reduced. And if crops get damaged, food is reduced. Across all of those accidents and disasters, we’re talking hundreds of millions of lives affected.”
It is here where a little lateral (and non-artificial) thinking is required. Accident and disaster recovery starts with visual damage appraisal: look at the damage, say how much it’s going to cost, unlock the funds and rebuild. The problem (and Tractable’s opportunity) is that having an appraiser look at a car, house or field can take days to weeks depending on availability — and therefore so can accessing funds to start rebuilding — whereas the claim is that computer vision and AI technology can potentially do the same job in minutes.
“When you assess, that is basically a very powerful but very narrow visual task, which is, look at the damage, how much is it gonna cost? Today, as you can imagine, these kind of assessments are manual. And they take days to weeks. And so you instantly know that with AI that can be 10 times faster,” says Dalyac.
“In some sense this is a perfect class of AI tasks, because it’s very heavy on image classification. And image classification is a task where AI can surpass human performance as of this decade. If you have instant appraisal, that means faster recovery. Hence the mission.”
Dalyac says that part of Tractable’s secret sauce is in the many millions of proprietary labels the company has produced. This has been aided by its patented “interactive machine learning technology,” which allows it to label images faster and cheaper than typical labeling services.
The team’s focus to date has been to train its AI to understand car damage, technology it has already deployed in six countries, seeing the startup work primarily with insurers.
Related to this I’m shown a simple demo of Tractable’s car damage appraisal tool. Dalyac opens a folder of car images on his laptop and uploads them to the software. Within seconds, the AI has seemingly identified the different parts of the car and determined which parts can be repaired and which parts need to be entirely written-off and therefore replaced fully. Each has an AI-generated estimated cost.
It all happens within a matter of minutes, although I have no way of knowing how difficult the pre-determined and fully controlled task is. It’s also unclear how an AI can possibly do the full job of a human assessor based on a limited set of 2D images alone, and without the ability to peek under the hood or undertake further investigations.
“We’re trying to figure out how much damage there is to a vehicle based on photos,” explains Dalyac. “There’s some really tough correlations to pick out, which are: based on the photos of the outside, what’s the internal damage? When you’re a human you are going to have seen and torn down maybe about a thousand to two thousand cars in your whole life of 20 or 30 years of doing that. Our AI has already been trained on tens of millions of these cases, so that’s a perfect case of us already having distilled thousands of people’s work experience. That allows us to get hold of some very challenging correlations that humans just can’t do.”
You need to find real-world use cases that will make a difference, where you can surpass human performance Alexandre Dalyac
With that said, he does concede that a photo doesn’t always contain all of the necessary information, and that it might only have a certain level of accuracy. “You might need to then get a tear-down of the car and get photos of the internal damage. You might even want to get some data from the dashboard. And you can think that as cars get more sensors… the appraisal will be not just visual but also based on IoT data. But that doesn’t detract from the fact that we are convinced that it will be AI that will be doing this entirely.”
What is abundantly clear is Dalyac’s commitment to developing AI technology with real-world use that is commercially viable. If that doesn’t happen, he believes it won’t just be Tractable that will suffer, but the continued belief and investment in AI as a whole. Here, of course, he’s talking about the prospect of another so-called “AI winter,” citing a recent Crunchbase report that says funding for artificial intelligence companies in the U.S. has levelled off and even started to decline at seed stage.
“If you’re trying to make the $15 billion that has been invested into AI not fuck up and lead to something successful that will prevent an AI winter that will lead to continuous improvement, you need a really good return on that asset class. And for that you need those businesses to be successful.
“To make an AI company successful, really successful — not just an acqui-hire, not just an IP exit but a real commercial success that’s going to prevent an AI winter — you need to find real-world use cases that will make a difference, where you can surpass human performance, where you can change the way things work,” he says.
The reference to acqui-hire or IP exit takes on more meaning when you consider that Tractable was in the same cohort at Entrepreneur First as Magic Pony Technology, the AI startup acquired by Twitter for up to $150 million for its image enhancing technology. And most recently, the team behind Bloomsbury AI, another EF company, was acqui-hired by Facebook for $20-30 million.
To ensure that Tractable can continue its mission of applying AI to accident and disaster recovery — and presumably not sell too early — the startup has closed $20 million in Series B investment in a round led by U.S. venture capital firm Insight Venture Partners. Existing investors, including Ignition Partners, Zetta Venture Partners, Acequia Capital and Plug and Play Ventures, also participated. The new capital is to be spent on accelerating growth, expanding its research and development and entering new markets.
(The Series B also included an additional $5 million in secondary funding, seeing some investors at least partially exit. I understand Tractable’s founders sold a relatively small number of shares as they were permitted to take money off the table. Dalyac declined to comment.)
As we wrap up our call, I note that all of Tractable’s main investors, not including EF, are from the U.S. — something Dalyac says was a deliberate decision after he discovered the gulf between European and U.S. valuations.
“That’s a shame, isn’t it?” I say with my European tech ecosystem hat on.
“It isn’t; it’s enormous exports for the U.K.,” says the Tractable CEO who is French-born but raised in the U.K. “We have, as of today, the vast majority of our headcount in London. The entire product team is in London. The entire R&D team is in London. But most of the revenue comes from the United States. We are making AI an export industry of the U.K.”
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