Data-driven VC #11: Why you need a strong firm and personal brand
Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
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The future of VC is augmented. Why? Well, I’ve described throughout the past ten episodes (see here for example) that the historic purely human-based VC model has been inefficient, ineffective, subjective and non-inclusive, eventually leading to on average sub-optimal returns and unfair distribution of capital. Remember that talent is distributed equally but capital is not, and VCs as gatekeepers are responsible for it.
As a result, data-driven approaches have started to change the industry to become more efficient, effective, objective and inclusive so that capital gets allocated to those who deserve it most and have the highest likelihood of success. However, independent of the benefits of data-driven approaches, I do not believe in a fully automated VC either. Not today and not in the future.
Why VC won’t be fully automated today or in the future
“VC is more art than science”, this is what many VCs told me when I initially started exploring data-driven approaches and automation more than 5 years ago. Today, I see what they meant and like to highlight four major areas across the value chain where data-driven approaches are insufficient and where it’s crucial to have a human in the loop/lead:
Inbound deal flow: I discussed in detail why deal flow generation should be automated, leading to comprehensive coverage and a holistic picture of every company top of the funnel, see my previous episode here. While this certainly helps to see every company as early as possible, we rely on a proper screening algorithm to cut through the noise and trigger a reach out to the most promising companies at the right point in time. On our little evidence today, this seems to work quite nicely, specifically in B2C/D2C-focused and open-source businesses.
VCs need to be top of mind for entrepreneurs
Sometimes, however, it is difficult or impossible to identify inflection points outside-in, specifically for B2B startups. For example, assume a B2B company converts a pilot customer into a lighthouse recurring contract customer which in turn creates a potential domino effect for subsequent customers that see the new logo and are thus more likely to convert. If neither party publishes the news somewhere online, data-driven approaches would struggle to pick up the initial conversion signal and likely miss out on the right point in time for outreach. Therefore, data-driven VCs would either need to wait for the success signal to be picked up (which might take too long) or rely on founders to reach out.
“A VC fund needs a strong inbound strategy and this explains the rise of bat signals from venture funds — blogs, podcasts, newsletters by funds and VC investors” by Sajith Pai in his “Narrative Capital” post here
This is what VCs call “inbound deal flow”, meaning founders reaching out to the VC which is the opposite of “outbound deal flow”, meaning VCs reaching out to the founders. Data-driven approaches are outbound only, but in reality, VCs need to complement these efforts with inbound deal flow to overcome the above-described information asymmetry. VCs need to be top of mind for entrepreneurs within their coverage.
Assessment: Creating a single source of truth across publicly available data but also privately collected information (like pitch decks or notes from founder meetings) increases efficiency a lot. Moreover, success scores and automated competitive landscapes, among other features, help investors to put things into context and draw their conclusions more effectively. As a result, VCs can assess more companies in greater depth and consider more data that eventually put them in a better position to make the right investment decision.
Investors need to spend time with the founders to see the “fire in their eyes”
Equally important for the assessment, however, is the interaction with the founders. Although there exist some explorative studies that examine how founders’ facial expressions, gestures or tonality can be recorded and used to predict the likelihood of success, I strongly believe that investors need to spend time with the founders to see the “fire in their eyes”. Assuming all “hygiene factors” and general business metrics are on track and boxes are ticked, the ultimate call to invest or reject depends a lot on the human interactions with the team. This part of the assessment process can and will not be automated anytime soon.