Why Market Traction is important Phd/Postdoc innovators

by Eoin Galligan

Terminology needs explaining. Source: @alex_tsl at unsplash.com)

In innovation, words matter. The deep tech segment of innovation is complicated enough — so universities need to support their innovators in understanding commercialterminology. I enjoy working with PhDs, postdocs and professors on operational “deep tech” innovation projects and I’ve noted that some struggle with the concept - “market traction”. Naval Ravikant of Angel List has defined this as: “the quantitative evidence of market demand”. For non-deep tech cases such as consumer digital startups, traction is typically related to managing the process to early customers’ purchase. But deep tech is different. With long development times, customer purchase is years away. Here, I dig into this concept, offering a new definition and adapting it for deep tech innovation cases at universities. I explain why it is important and I’ll look forward to any online feedback.

I start with my own definition of market traction:

“a pro-active, managed process to acquire quantitative evidence that validates the problem definition, value proposition – and creates initial customer relationships.”

Lets break that down. The first part of my definition is focused on the manager. Due to the high level of uncertainty in university cases, the manager needs to control project risk, rather than just react to events after they happen. In many university innovation projects, innovators do not hold a sufficiently deep understanding of the problem or the value proposition of their approach. They may have a solid understanding of the research and the scientific literature – but this is not enough for innovation.

Therefore, the innovation manager needs to create a process to acquire a type of knowledge – not from the university library or the literature, but from interacting with stakeholders.

Focusing on different types of knowledge

I continue with Ravikant’s use of “quantitive evidence”. The process starts with a target list of stakeholders: users, companies and can eventually include seed investors. The goal for the manager is to create a sufficient number of meetings to acquire knowledge. How many meetings? Well, it depends on many factors. Everyone is busy and getting these meetings is difficult. How much knowledge is needed from the market? Do the researchers have a robust understanding on how industry perceives the problem already? As a guide 3–4 meetings is a good start after which the team can reflect.

Once a meeting is booked, what happens? Lets imagine we’re working with a quantum computing (QC) technology. The innovation manager created a target list of contacts, a non-confidential pitch deck and now a couple of companies have agreed to meet. Everyone is excited.

The first meeting is with an organisation that is piloting the use of QC algorithms to improve analytics. At this early stage, partnership may be possible – but challenging due to the technology development status. Therefore, the core purpose of the meeting is to learn the company’s perspective – or their ontology. How do they “see” the problem? What are their key pains? Who is their expert on such pains? Why is the company starting to look at QC technology as a potential solution? Next, the university innovators would offer their value proposition – a statement that describes the value (as they see it) that their approach creates. In turn, the company offers critical feedback. Is the innovators understanding of value flawed? Or does the company wants to learn more?

A key point to emphasise is the quality of communication. The meeting enables learning via “iterative feedback”. The innovators get an opportunity to understand the problem from the market’s perspective – meaning they have to adapt. Companies get an opportunity to observe technologies coming through the pipeline, but also to meet a new university research group. My definition states a goal of validating the problem definition and value proposition. This is ambitious for a first meeting – but it is the eventual objective. Typically, companies need to reflect and discuss these questions after the meeting ends.

The knowledge obtained via market traction is important for 3 reasons. First, the university manager is responsible for a portfolio of technology cases and needs to determine where to spend time and university resources. Importantly, the manager may not have the luxury to focus on a specific industry. For example, my portfolio is dominated by life science technologies, but I also have to manage the risk on quantum computing, material science and food technology projects. I must acquire market knowledge to help me de-risk the portfolio — otherwise, I’m not doing my job. If a number of stakeholders disagree with the problem definition and value described by the innovators, the manager has to discuss the risk level with the innovators. This external feedback either reduces or increases the project risk — i.e. typically defined as the likelihood of a licensing deal. Should the innovation case be closed or supported?

Risk is a key part of innovation. Source: Cristofer Maximilian @ Unsplash.com)

The second reason this is important is because of money. If market feedback is positive, then the university manager and innovators can utilise this knowledge within a future funding application. Many funding instruments have been created to enable “Proof of concept” (PoC) activities for university innovation. Market traction knowledge is “gold dust” for such university PoC funding applications. Acquiring this knowledge demonstrates an innovation mindset that manages both risk and technology development.

Lastly, this activity affects the innovators themselves. After experiencing critical feedback from industry business developers and scientists, they are able to realise the limits of their perception, and how adapting their future development plan could dramatically increase the value of the project. This is why the last component of my definition is building early stakeholder relationships. As these relationships evolve, the university innovators can continue to learn and consider what needs to be achieved in order that their future spinout company could return to company contact to discuss deeper partnership.

I finish as I began. Explaining these concepts of “deep tech” innovation raise everyone’s performance. Acquiring stakeholders’ perception can dramatically affect the risk assessment of an innovation project and can help acquire PoC funding. I look forward to your feedback and wish you well as you seek critical feedback out there within the deep tech world.

Eoin Galligan





I work within university innovation, where I work with researchers to create partnerships or spin-outs.

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Eoin Galligan

Eoin Galligan

I work within university innovation, where I work with researchers to create partnerships or spin-outs.

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