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Hi there!
I recently got invited to present some of our DDVC work in front of a group of seasoned VC investors from traditional and corporate VC firms. As I always encourage participants to jump in with questions and remarks to rather create a conversation than a lecture, it didn’t take long before a senior partner from one firm jumped in and asked:
“I’m confused by what you refer to with ‘data-driven investors’. Isn’t every investor data-driven?”
Excellent question and something I take for granted too often when speaking about this topic. It was a great reminder to always start with a simple definition and framework before diving into details.
So before I share my answer to his question at the end of this post, let’s get the basics right.
Definition of ‘Data-Driven’
Here’s how ChatGPT defines the term:
Data-driven means making decisions, strategies, or actions that are guided by data rather than intuition, opinions, or personal experience.
In practice, being data-driven involves:
Collecting relevant data – from internal systems (like sales or customer behavior) or external sources (like market trends).
Analyzing the data – using tools, statistics, or machine learning to uncover patterns, trends, or insights.
Deciding based on those insights – rather than relying on gut feeling or anecdotal evidence.
A data-driven approach is often contrasted with being opinion-driven or experience-driven. It’s about letting facts lead, even when they challenge assumptions.
Isn’t Every Investor Data-Driven?
Let’s look at traditional VC investors, how they fit into above definition, what their constraints are, and how data-driven investors compare.