Data science is becoming a cornerstone for innovative data-based technologies. As the managing partner and co-founder of a venture firm that invests in data-focused entrepreneurs, what are the most promising innovations you see in the startup landscape today?

In the longer term, there is real promise in some exciting areas like quantum computing that I believe could create a massive shift in how data is processed that will be felt across all industries. Shorter term I think we will see more products deliver on the promise of AI and machine learning. The industry has made a lot of progress in the areas of testing AI/ML applications but to in order to build scalable, mission-critical, systems that have reliable outputs, every layer of the infrastructure needs to be built out with robust technology and sound data science principles. It seems that the world has figured out that AI isn’t magic—it’s math which requires the right technology and processes to implement properly, creating tremendous opportunity in every corner of this massive market.

In a world that is permeated with nascent startups focused on data technologies, how do you identify the truly revolutionary innovators to invest in?

There are a couple of things we look for depending on the type of solution we are evaluating but, at the end of the day, we are looking for what is commonly referred to as ‘founder/market fit.’ This holds particularly true when we are looking at deep technology or platforms that enable AI/ML functions within an organization. For these products, the technical and/or professional experience of the founders is critical. Ideally, the founding team will have very strong technical talent coupled with business acumen to help identify go-to-market opportunities.

"Understanding the dynamics of a sector and working with founders who have expert knowledge of a particular problem is the best way for us to invest in companies that have the potential to realize the outsized returns we look for in the venture world"

For applied AI solutions that are specific to an industry or particular job function we look for applications that 1) add significant value on a transaction-by-transaction basis 2) collect a unique and valuable dataset through the deployment of their application, and 3) aren’t necessarily doing something technically revolutionary but implement AI/ML technology in a scalable and repeatable way. Too many pitch decks reference AI, but when we dig in a little deeper there is very little technology underlying the application.

It takes an experienced eye to sort through the noise in this industry, and fortunately our team has a lot of experience as practitioners, not just as investors. My partner, David Magerman, has a PhD in Computer Science from Stanford and spent 25+ years building extremely successful trading systems that used data science and NLP, so his experience helps us to substantially reduce early-stage technology risk.

As the leader of the venture firm that has launched dozens of companies to success, what are some of the strategies that you follow in guiding the startups in their growth journey?

The simplest answer is to stay focused on what matters most at various stages. Every company is going to be a little different, but there are also a lot of similarities across sectors and stages of growth. For example, a lot of early-stage companies try to replicate what they read and hear about Product Led Growth [PLG] or other growth efficiency benchmarks that pertain to much more established companies when, in reality, the most important growth metrics to watch are: how many leads do you have? How many are marketing qualified leads [MQLs]? How many MQLs become sales qualified leads [SQLs]? And how many convert to paying customers? With that data you can start to predict the health of the business and identify bottlenecks in your GTM motion.

John Doerr, from Kleiner Perkins, wrote a great book called ‘Measure What Matters’ that covers the topic of setting ‘Objectives and Key Results [OKRs]’ for your organization. As an investor, I think it is our job to help founders get out of the weeds a bit and set OKRs that are meaningful and then focus on the tasks that are going to be most impactful to the business. Most entrepreneurs are either very good at knowing what matters to the business but struggle to “get out of the Excel spreadsheet” to generate activities that will impact the numbers, or they are very action-oriented but can sometimes get too bogged down in the day-to-day details to monitor trends in how they are performing relative to where the business needs to go.

Before co-founding Differential Ventures, you have worked at several other venture capital (VC) firms? What are some of your experiences that empowered you to enhance your business model at Differential Ventures?

My past experiences in venture capital and as an operator led us to some core principles that I think are important to our business model and our success as a fund.

• We can’t be experts in everything so focus on the markets with huge opportunities where we are also well-informed. Understanding the dynamics of a sector and working with founders who have expert knowledge of a particular problem is the best way for us to invest in companies that have the potential to realize the outsized returns we look for in the venture world. As we mature as a fund, do more research, and add new people, our areas of expertise will expand. There will always be some markets where we have to be comfortable letting other people make money, and focus on the areas where we have the highest likelihood of success.

• Invest early in the people, processes, and technology that will make us dependable investors and fund managers. At the end of the day, we are stewards of other people’s money whether it be our LPs capital or co-investors who are relying on our diligence and leadership to make an investment decision. We invested heavily into our operations, well beyond our management fees, to ensure that we run a mature and buttoned-up operation which is surprisingly rare for a lot of newer seed funds.

• Speak when we have something important to say. Using social media and aggressive marketing campaigns is a great way to get started in venture capital, but not necessarily a great way to be successful in the long run. Without question, the most important and impactful things we do as investors take place in boardrooms and in 1:1 sessions with founders and others in our ecosystem - far away from VC Twitter and LinkedIn. Certainly, there are topics we address and speak to frequently that help us build credibility with the founders and partners that are most relevant to us, but there isn’t much value for us in writing the 328th blog by a VC about how to manage a startup through an economic downturn or hire a ‘platform’ person who spends most of their time organizing happy hours. With some exceptions, we believe in staying quiet and letting our performance speak for itself.

As an ending note, what is your advice for other senior leaders and CXOs working in the VC sector?

Double down on your strengths, be painfully honest with yourself about your weaknesses, and have the confidence to fill those gaps with people who are more knowledgeable than you. I am technical enough to ask the right questions about technology, but I’m never going to be as technical as my partner David; and that’s a good thing. Our partnership makes us a better company.