Discover more from Tango.vc
The Lonely Middle of the Hard Tech Spectrum
There is a spectrum of hard tech, from predictable companies to those that break models of what is possible. Both have standard fundraising stories. What happens in between?
One end of the spectrum is something like B2B SaaS. You’ll be judged by well-known performance metrics. The example below is from Initialized. They know so much about these types of businesses that they can give thresholds for metrics to earn a Series B.
Another end of the spectrum is very Hard Tech. Think artificial general intelligence (AGI) or launching rockets. Tesla was founded in July 2003 and shipped its first roadster in July 2006 - a full 3 years. SpaceX was founded in March 2002 and had its first successful commercial launch after 3 failures in September 2008 - 6.5 years later. Deepmind was founded in 2010 and acquired in 2014 without a public product beyond their incredible research.
It’s actually relatively easy to pitch these most ambitious hard tech startups. Venture Capital bets on outliers, and the story “if this works, everything changes” fits very well. It doesn’t have to be a large chance of winning. A VC is happier with a grand slam home run than getting on base many times.
The lonely middle on this spectrum is different. Your company has deep technical challenges that might take some time to solve. But it might not be judged like solving AGI. Instead, you might be judged compared to B2B SaaS metrics.
Imagine year 2 of SpaceX or Tesla. New Revenue: $0. Growth 0%. Retention: who knows?
At Tango, we back a lot of companies in the middle here. Traction can solve problems, but short of that without a launched product, you have to find proxies for the value you’re building.
Early interest can take a few forms. Letters of Intent (LOIs) are non-binding contracts that share a customer’s interest in purchasing. Because they’re non-binding and in the distant future, the numbers can get quite large, especially in large markets. I’ve seen “hundreds of millions in LOIs”. If you map the contract value per customer to the whole market, you get a large addressable market.
If you’re close enough to launch, selling first units before they are ready can pull forward traction. This requires the customer interest to be strong enough to put down money, maybe only a fraction of the purchase price, early on. The cash is nice, but the signal is crucial.
Sometimes customers can pay you to develop the product they want to buy. It’s normal for larger companies with enterprise clients to have service revenue as part of a deal – maybe as high as 30%. Consider adding this revenue before you have a product to show that customer interest is there. Take care in how you talk about this revenue to investors because it isn’t ARR. Nothing spooks investors faster than telling half truths about your numbers. Investors also don’t like consulting and service businesses, so you need to make this message especially clear about how this service revenue is helping hit technology and product goals.
One of the clearest ways of demonstrating you know how to break into a market is by showing how you understand the customer. This comes across in many ways. How many have you talked to? Do you have a causal explanation for why they want to solve a problem with your product? Can you quote them on it?
Customer understanding is especially important in industries where tech has lagged. It’s precisely this lag that creates enormous opportunities, but also investors have heard the story too many times. This includes industries like construction, education, energy, and agriculture. It’s not enough to say that “construction productivity growth is actually negative”. You need to explain why your product will change that.
A few Tango.vc portfolio companies come to mind that live in this lonely middle of the hard tech spectrum.
Teleo builds autonomous and teleoperated heavy equipment. Think about moving large amounts of dirt and rocks on construction sites or mining operations. The economic case is crystal clear: operators are aging and expensive and allowing them to spend more time piloting is a win. The customer story needs to spell out much more: how does rollout work? Do you have a support network for the equipment? How are operators trained? Answering this and more helped earn a Series A for Teleo.
Faction makes driverless deliveries. Driverless vehicles are famously difficult, and some would argue on the far end of the hard tech spectrum. But Faction is built different. I’ve never met a robotics founder more obsessed with making a profitable business and launching a real product than Ain McKendrick from Faction. Every design choice feeds this goal, including choosing a light electric vehicle chassis, avoiding human passengers, and leveraging teleoperation. Their answer is to have real revenue from real deliveries as soon as possible.
Edia makes AI software for math education. The product helps generate math questions, can grade them automatically, and give explanations for where students went wrong. There is a deeper layer to Edia, evident from Joe Philleo’s twitter bio: “solving Bloom’s 2-Sigma problem for K-12”. The Bloom 2-Sigma problem is the notable impact 1:1 education has on performance. 2-sigma refers to two standard deviations of improvement, which in the world of education is staggering. But humans are too expensive to do this: in the US the ratio of kids 5-18 to working adults is 33%. Software can solve this problem in the long term with AIs that are as good as real teachers.
This is an enormous ambition, but what do you sell right now? I’ve learned so much from Joe about the education market, specifically in public schools. What will parents pay for? Who makes decisions not for schools but for districts? What is a district’s “IT budget” per student, and how might that thinking evolve? What measure of student success from a product turns into district enterprise contracts? The level of customer understanding here is crucial to build and sell a product well before you have an AI tutor for every student.
Keep your big vision. Investors love outlier hits.
Build revenue signals like LOIs & pre-orders
Consider services revenue, but keep it connected to product roadmap
Build customer connections and your understanding of their industry
Clearly model why a customer will buy, what problem it solves
GTM includes where to buy and where to get support
Move as fast as you can to early traction. Traction solves all problems
I’d love to hear more tactics and strategies that work for other companies on the hard tech spectrum. Add them in the comments or email me: firstname.lastname@example.org