Funding marketplaces or VC data analytics: why not both?
Finally, FinTech is arriving to the world of VC, private equity and corporate finance, spurred by at least three major trends.
1) Venture capital firms have started to embrace software to become more efficient
2) The traditional lines between LPs and GPs are blurring. The type of investors is diversifying: corporates, super angels, investor clubs, micro funds, SWFs, …
3) Growth trajectories of tech companies are shortening, creating a need for real-time actionable data and intelligence
Many promising tools for VCs have been launched in response to this. In particular we’ve seen the emergence of two types of software models:
(a) marketplaces as platform for funding (many-to-many)
(b) tools to discover and track startups (one-to-many)
a) Marketplaces as a platform for funding
Marketplaces are in theory a logical way of matching supply and demand for startup investing. Marketplaces bring transparency, market discipline (the invisible hand), and create a level-playing field. Once critical mass is reached, marketplaces tend to grow stronger and stronger thanks to positive network effects. Taken to the extreme, they could eliminate proprietary deal-flow, although I have expressed some skepticism about proprietary deal-flow completely disappearing.
One of the hurdles for marketplaces is the adverse selection problem: the best companies often won’t list themselves on any platform because they enjoy already plenty of love and attention from VCs eager to invest. Secondly, professional investors do not like the idea of investing in companies via platforms. VCs and angels like to take the initiative. They generally don’t like the idea of being pitched or passively being fed deals.
b) Tools to discover marketplaces
Some data analytics tools have been created to discover and track winning tech companies. These services were built on top of free sources like CrunchBase but massively improved them. Using data-crawling technology to filter out the noise and find growth is a great value proposition. Such tools sit much better with what VCs want, allowing them to be be in the driver’s seat, be the hunter so to speak. It allows them to discover “hidden gems” (= proprietary deal-flow), as well as filter out the noise (= low quality businesses).
There are caveats however. Firstly, there are negative network externalities: more users make the product less valuable (aka “congestion”). Secondly, private company data is not easy to find and often stale. And the public data that can be crawled is fairly easy and cheap to find, making it harder to justify a subscription fee. Indeed, many VCs have built their own in-house technology at low cost.
This begs the question: why not both?
So where does dealroom.co fit into this?
Dealroom’s model is a little different: we’re neither a marketplace nor a data provider, but a hybrid.
Killing the adverse selection problem: we track the growth of all companies, not just the ones seeking capital. The way we organised our data is very much about finding context and connecting the dots. For example, if company A is raising capital, what other activity is there in this space, and how does their performance compare with their peers?
Avoiding negative network effects of data: we realise that data is power, but data is also ubiquitous and therefore not that valuable by itself. So we decided to offer most of our data for free, and also enable the crowd to further improve our data. Company data can be edited by its founders and investors requesting editing rights. The owner of the data has control over who can view it (all dealroom.co users, or only invited parties). Why would companies publish their own company data? Improving the data we have on your company improves its ranking in our recommendation algorithm. And those who have growth to demonstrate, have an incentive to display it.