Fundraising has always been a relationship-building exercise, limited by whom you know and how you get to know them. It is only in the recent past that we are seeing broader technology enablement of fundraising.
Problems to consider while building relationships
Let us take a step back and understand how fundraising works in the real world. You may engage an investment banker or create a role within your company for engaging prospective investors or DIY (Do-it-yourself) as a founder.
- You will begin by creating a pitch deck covering your team, traction, value proposition, and opportunity sizing, followed by the usage of the funds raised to achieve better outcomes.
- You will start with an initial list of known prospects within your network or of the investment bankers’ network. You will float your pitch and await feedback evaluation and some decision to move forward with the deal.
- You will soon run out of people to pitch. If there is an investment banker in play, the deal gets around to a larger number of people who are on their go-to list.
- You will take any and every incoming interest from investors without clearly having an idea about their investment preferences and past commitments.
- You could possibly then begin stalking/connecting with people on social media like Twitter or LinkedIn. Here the starting point is still zero trust base deal with no responses and ghosting.
There are 3 main considerations with this approach:
- Are you able to reach out to appropriate investors?
- Are you able to cover the broader universe of investors within your reach?
- Are you able to leverage relationships for getting warm intros that give you a better jumpstart on building relationships?
Role of Intelligence in Investor Relations
The first problem in fundraising is the lack of intelligence about the investors themselves. Here tech should be able to help you in finding investors who fit your valuation range, ticket size, whether your value proposition matches with an investment thesis, dry powder with the investor, and recency of investor-deal activity.
Relying on popular media or social feeds only provides a partial picture of the investment landscape, pushing what is interesting but not immediately relevant to your needs.
The second and third problems are related to relationship intelligence assuming you were able to find the investors. For example, your team member possibly has an alma-mater connection with a relevant investor, your sales head is already pitching to a businessman who also happens to be an angel investor, or your own investor has co-invested with another prospective investor.
If we generalize the solution for both these problems with tech, we could solve this with a massive graph database of nodes, and relationships that exist between parties. Nodes can be investors or companies. While relationships can be shareholding, directorships, alma mater, sales-client connect, and family relations, among others. As a founder, this will solve your need of filtering investors who fit your criteria and are within your extended network.
Relying on such raw and relationship intelligence comes in handy, especially when you cannot engage an investment banker in the early stages. Founders can then get a jump start charming the relevant investors, finding the right fit, and moving the needle on both building relationships and getting investment commits.
Best early-stage founders fill in at least three buckets after they have built the trust base with a set of investors. The first bucket is for investors coming in immediately (possibly even at the last round prices or at a small discount to the next round). The second bucket is for the upcoming round. The third bucket is for a larger next round for which timelines are not known currently.
Engagement styles and reporting vary for each of these buckets, covering the urgency, preferences and fit. Fundraising can then become a fruitful exercise of building meaningful relationships, rather than futile conversations with investors who are neither relevant nor will ever commit.
