Data-driven VC #24: An Emerging VC's Tech Stack
š„Inside Hustle Fundās data-driven VC journey
šĀ Hi, Iām 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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I ended last weekās āIf you canāt measure it, you canāt improve itā episode with the following summary:
āConclusions will be different for every fund and so should the prioritization of your initiatives. Next episode, weāll dive into various avenues to become more data-driven based on different starting points.ā
To explore these different avenues as tangible as possible, I decided to finally incorporate your feedback and meet your wishes by launching a series of guest posts. Thankfully, there are incredibly kind VCs in our community who are willing to share their story and learnings from different starting points across the VC Digitization Journey.
One of them is Will Bricker from Hustle Fund, a pre-seed venture capital firm investing in software and service companies in the United States, Canada, and Southeast Asia. Itās the perfect example of an Emerging VC firm that has very limited resources but runs on a highly effective and modern tech stack. Relating to my āVC Digitization Journeyā episode, Iād classify Hustle Fund as a āProductivity VCā on the verge to becoming a āData-driven VCā via automated deal assessments and more. Thank you, Will, for sharing your journey with us in the guest post below šš»
VC Tech Stack Approaches
When it comes to building your VC tech stack, there are two available options:
The choice of which approach to take will depend on preference and requirements. Some factors include:
How unique are the features you require?
How much do you want to pay?
What resources do you have to run your platform?
Keeping all this in mind, letās talk about Hustle Fundās setup.
The Hustle Approach
When designing our platform, we went with the bespoke approach from day 1. A couple of factors went into our decision:
Who we are: our partners are entrepreneurs at heart ā the desire to stay lean, learn and iterate is in their DNA
How we started: as a small fund ($11m), we didnāt have much money to spend on big-time software
How we invest: we see a lot of deals and write a lot of checks. Without the ability to automate what we do, the only way to scale is by adding salaries
For some additional context, letās get specific on that last point:
We see ~700 deals a month
We write ~15 checks a month
We have ~400 Portfolio Companies across three funds
We have written ~550 Checks
Our companies have had ~800 investment rounds
In short, we are a high-volume firm: we see many deals and write many checks. The high volume presents a core challenge in balancing efficiency and effectiveness in getting, synthesizing, and acting on information when investing and supporting our portfolio companies. We believe a bespoke platform is the best approach to tackle this challenge. I say that because it enables us to create and apply logic and automation that
Helps us identify whether or not we think a deal is a good fit based on the information they have provided
Enables us to have all the information for our portfolio companies across platforms, including their live value
Allows us to automate our most common actions across platforms
Provides flexibility that facilitates us iterating and evolving our platform as we grow
Ok, enough setup. Letās talk about our stack.
Our Tech Stack: App Overview
There are a lot of apps we use as a team ā depending on personal preference, role, etc. However, below are our most universally used and adopted apps (apps that MORE than two people use):
Our Tech Stack: Investment Stack Design
Generally, when I read these pieces, I always wonder, āok, I know what you use, but how do you use it?ā So, I am providing some simple diagrams to show the outlines of our platform for our deal pipeline and portfolio management. The idea is to show you where and how we use each piece to make and monitor investments.
In brief, I would argue that the core of our platform has three layers:
DB
Airtable ā as our central source of truth for information about all investing entities (companies, investments, etc.) and operations info (actors, status, actions, etc.)
Glue
Zapier ā to connect our apps, run our logic, and execute predefined events via triggers
UIs
Airtable: to view information about deals and investments & intake data
Pipedrive: to author and review communication
Process street: as our investment execution workflow (central/standard data intake + event orchestration)
With these three layers, we can build a set of features that fulfills our needs and bolt on other platforms (Carta + Box, Typeform, DocuSign) as we see fit. Below you can see in a little more detail how and where we use these pieces to invest and manage our portfolio.
Our Tech Stack: Investment Stack App Breakdown
In this section, I want to provide an overview of how we use each app and my thoughts on how satisfied we are with it currently (on a 1ā5 scale, with 5 being the best) and how well we think it will scale with us going forward (using the same scale).
The Big Pieces
Database: Airtable
CRM: Pipedrive