DeepTech founders beware: pragmatists don't buy technology breakthroughs

Your technology works. The evaluations went well, the engineers on the customer's side are impressed, and the early adopters who backed you are telling anyone who will listen. So why is the mainstream market still holding back?

Because pragmatic buyers don't buy technology breakthroughs. They buy complete solutions, and in DeepTech someone else often owns most of the solution. Who makes the rest decides how quickly you reach the mainstream market and how much of the solution value you keep.

Geoffrey Moore called the gap between early adopters and the mainstream market "the chasm", and two of our most-read pieces have explored it. The first looked at the chasm as the funding gap between Seed and Series A. The second asked why early adopters must share your belief. Both were written with software in mind.

DeepTech changes the shape of the problem. Not because the science is harder, but because the thing the buyer needs is usually bigger than the thing you make. That gap is wider for some DeepTech companies than for others, and in our experience how a founder closes it is one of the most consequential choices made between Seed and Series B.

This week we return to Moore's thesis, and to what it tells DeepTech founders that it never needed to tell software ones.


Believers and buyers

Moore's model, first published in 1991, divides the market for a new technology by buyer attitude. Visionaries buy early because they see an advantage their competitors lack, and they will tolerate an unfinished product to get it. Pragmatists, who make up the far larger mainstream, buy only what has been proven by people like themselves. The chasm is the gap between the two, and the classic way across is to win a beachhead: one narrow segment of pragmatists served so completely that they become references for the next.

Moore has since put the distinction more sharply. The target market, he told Forbes, moves "from people who believe what you believe" to "people who need what you have".

That line explains the chasm better than any adoption curve. The belief that carried you through the Seed rounds is not the currency the mainstream deals in. Need is.

And what pragmatists need is rarely a technology on its own.


The whole product

Moore's answer to what pragmatists need is the idea founders most often underestimate: the whole product. A visionary will meet you halfway, assembling the missing pieces themselves. A pragmatist will not. In Moore's words, "you have to meet them 100% on their turf, which means you have to bring what we call the whole product." It is everything the buyer needs for the technology to solve their problem from day one: integration, support, certification, the surrounding system. His book frames the task of crossing as "building out the whole product", recruiting the right partners and allies to do it.

Software made this look easy. A SaaS startup typically builds nearly everything its customer touches and needs far fewer partners than the enterprise technology vendors Moore originally studied. When the product relieves a genuine pain, little stands between the first pragmatist and the second, which helps explain how quickly pain-relieving SaaS can cross.

DeepTech reopens the gap. More than 80% of DeepTech ventures build physical products, according to BCG, and a physical product usually has to work inside somebody else's system. Often, the startup makes one critical part, and the rest of the whole product belongs to someone else.


Continuous for whom?

How wide that gap is depends on where a company sits on a scale that Moore's own definition helps draw. He reserved the chasm for discontinuous innovations: products that require the buyer to change their behaviour, as an electric car does for a driver who has only ever bought petrol.

At one end of the DeepTech scale sits drop-in technology: a better engine, battery cell or material that slots into an existing system. For the end user nothing changes, which can make it look as though Moore's model does not apply. It does, but the chasm moves. For the prime contractor or system supplier who must integrate an unproven startup's component, the decision is every bit as discontinuous: new supply risk, new qualification work, a new dependency.

At the other end sits behaviour-changing technology, where the end user must learn to work differently. Quantum computing is a classic case. In a survey of 291 organisations by QuEra, itself a quantum vendor, only 13% had moved quantum projects into production, and a shortage of skilled people was the leading barrier.

Most companies sit somewhere between the two ends of the scale, and even drop-in technology can demand some re-engineering of the system around it. Where you sit shapes everything that follows.


Build a crude whole product first

For many DeepTech startups the route across the chasm begins with a counter-intuitive move: building more than the core technology. Buyers can rarely judge a component in isolation, so the startup assembles a working, if crude, version of the whole system to show what its technology makes possible.

Tesla offers a well-documented example. Its first car, the Roadster, was built on a body and chassis supplied by Lotus, the British sports car maker, while Tesla supplied the powertrain. The car was never the whole point. Tesla's own filings describe its powertrain as "the foundation of our business", and the Roadster was its showcase.

In our experience the choice of showcase partners matters as much as the showcase itself. Founders who assemble their first system with other pioneers, specialists at a similar stage who gain as much from the collaboration as they give, keep control of the result. Founders who lean too early on large, established primes often find those companies holding the leverage over the final solution - and control over end customer access.

Amadeus Capital puts the purpose of this stage plainly: "a pilot is not traction". It is an audition. A showcase is an audition for the whole product, paid for in time and capital that your investors need to understand they are funding.


Enter the mainstream with pull

Once buyers in the mainstream market have seen the potential, the startup usually has to work with established partners to build a solution that is deployable at scale. This is where drop-in DeepTech companies are most exposed. The primes own the whole product, and a supplier they can replace has little say over price, specification or timing.

The way through is market pull: making the end customer ask for your technology by name. Intel wrote the playbook in 1991. Rather than relying on PC makers to promote its processors, it subsidised their advertising in return for carrying the Intel Inside logo. By the end of 1992 more than 500 PC makers had signed up, and 70% of the adverts that could carry the logo did so. A component had become a reason to buy the system.

Tesla followed a similar sequence. After the Roadster, its annual report records that it had been selected to supply around 1,800 battery packs and chargers to Daimler, had agreed a powertrain development deal with Toyota worth up to $69m, and counted both carmakers as shareholders.

The startup that reaches this point holds something the primes lack: hard-won knowledge of how its technology behaves inside the whole system. Combined with a name the end customer already trusts, that knowledge is leverage and acts as an accelerant in the scale-up strategy.


When the whole product is yours to build

At the behaviour-changing end of the scale the partner problem largely disappears, because there is often no existing system to plug into. The startup has to build most of the whole product itself, including the training and support that let a customer change how they work. It keeps control but pays for it in time and capital.

The sale is different too. Moore's pragmatists buy when they are in pain, typically because they are responsible for a business process that is not working. Drop-in technology that transforms what a system can do relieves that pain in a way the buyer feels immediately. Behaviour-changing technology is more often sold on opportunity: the buyer is not fixing something that is broken today but investing in a capability that could open up an advantage tomorrow, such as a new product or a faster route to discovery. In Moore's terms, that means it is still being sold to visionaries, and those sales take longer.

So, the question for these founders is where opportunity turns into pain. The same QuEra survey found that 62% of organisations are already running into the limits of classical computing. That is what the edge of the chasm looks like: a pragmatist starting to hurt. Until it arrives, someone has to fund the long build, and for most DeepTech companies that bill often falls due at Series B, the round that pays to turn a working technology into something that can be deployed at scale.

As we showed in Europe's Series B problem, Series B is the one stage of European venture funding where capital is shrinking. A behaviour-changing company that has not found its pragmatists in pain by then will be raising in the tightest corner of the market.


Three questions to answer before Series A

Moore's thesis has held for 35 years. What DeepTech changes is who builds the thing the pragmatist in the mainstream market buys, and that question deserves an answer long before Series A.

Three tests are worth putting to your own plan. Where do you sit on the scale: will your customer have to change how they work, or only your integrator? If you need a showcase, who are you building it with, and will they leave you in control of the result? And when you finally sit down with the primes, will the end customer already be asking for you by name?

A founder who can answer all three has more than a go-to-market plan. They also know how much capital the crossing will take and over what timescale: a drop-in company and a behaviour-changing company are raising for very different journeys. That is the plan that will survive investor interrogation, and it is far better drawn up before Series A than discovered at Series B.

Let's talk.