Managing investment in a deep-tech startup isn’t the same as that in a SaaS startup. Deep tech is a very attractive space for investors right now. Traditional SaaS VCs entering this space need to assess their investments with a slightly different lens than they would a typical SaaS startup. Specialist deep-tech funds already know this and can show the way.
Non-recurring revenue
The very first difference is the key success metric. In SaaS the main success metric is Annual Recurring Revenue (ARR). As soon as a SaaS company showed ARR growth, you knew it was on the right track. But in deep tech, revenue has different characteristics – it is irregular and primarily non-recurring in the early stages. The reason is that not only is the product evolving, but also the technology is at an early stage. The early adopters of this breakthrough technology are other researchers, who want to use this new tech to further their own research. They rely on grants that are irregular and such a dynamic makes recurring revenue measurement less relevant.
Traction
The second difference is related to the metric above. Traction. In SaaS, you know the startup has traction when you see new logos on the monthly report and existing customers renewing with an uplift. This is not quite the case in an early-stage deep-tech startup. Here, the traction indicators are lighthouse institutes betting on the technology, pilots with known peers and grants. While the institutes and peers render credibility to the product and technology, the grants are non-dilutive and peer-reviewed. These are strong indicators that the startup’s technology has promise, that the product they are building can evolve into something big. In two of the quantum companies we have worked with, we saw all three running at once: paid orders, beta projects and grant-funded work. A grant funds the pilot, the pilot produces a result worth publishing, and the publication brings the next institute.
Growth drivers
The next key difference is in the growth drivers. In traditional SaaS, growth came from building a team of marketers, sales reps and customer success managers. There was a strong correlation between spend and growth. More marketing meant more pipeline, more account executives meant more closed deals, and a good customer success team meant higher net retention. An entire science was built around using sales approaches, marketing measures and customer success metrics to drive growth.
In deep tech, however, the key growth drivers are the technology breakthroughs, product milestones and peer endorsements. You don’t need an army of sales reps, but a select few sales engineers that come from the same field and can have a deep, meaningful conversation with the customers. You don’t need an army of marketers, but a few that can communicate the technology and product at different layers. Likewise, you don’t need a customer success team whose job is to renew the contract, but success engineers that can ensure the end customer use case is realized.
Same bet, different signals
Like any other startup, you are still betting on the people behind it and you are still looking for the right signs. There is a lot of learning from the SaaS industry that are still applicable to deep tech. ICP (ideal customer profile) discipline, for one, is highly relevant in deep tech – you need to select who you to sell to and who to avoid. Founder-led sales followed by sales hiring is equally important as the initial validation and PMF (product-market fit) will come from the founder’s network. Deep tech is an interesting bet. Picking the right signals for evaluation helps ensure the bet is a calculated one.
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