By Sergei Mosunov
The concept of data-driven VC (Part 11)
This week witnessed an excellent report by Dr. Andre Retterath and his team on the ongoing changes and dispositions in the Data Driven VC market. The report clearly shows how an army of foundations is building their systems for collecting and processing disparate data, improving their awareness of technologies, founders, market niches and much more, which can significantly affect the success of potential investments. Such developments will allow in a couple of years to significantly change the way of analyzing projects and forming pipelines within funds (non-obvious deals will be enriched with data), build competitor buying strategies, identify the best matching co-founders and promote more accurate marketing campaigns. These trends will become an integral part of Venture 3.0.
Even now we see that in The Garage Syndicate most of the business is going to be automated, for example, screening and sourcing, DD, investor communications, deal updating and, of course, we would like to become the industry standard in this emerging trend as well, as this contributes to the development our Data DNA and improves the profitability (ROI or TVPI) of every syndicate trade. To realize this ambition, the project was launched, which promotes the massive use of AI technologies in investment decision-making not only by The Garage Syndicate, but also by other funds, syndicates and private angel investors, as well as in the transformation of startups themselves.
The report clearly shows how an army of foundations is building their systems for collecting and processing disparate data, improving their awareness of technologies, founders, market niches and much more, which can significantly affect the success of potential investments
So, what can we expect from the introduction of AI in venture capital investment?
  1. Openness of data about companies and investors, both public and more closed, will become ubiquitous and there will no longer be a question of who does what and whose investment thesis it is, or how much this company earned from its clients, and who those clients are - all this will be available especially in the early stages, when the founders will seek to disclose their performance to potential investors in order to get on the radar of desired funds, and automated scoring systems will notice certain market signals and signal partners to contact a specific company.
  2. Fundraising will become super automated, as the funds themselves will talk about their preferences and issue public APIs so that companies can upload their metrics and data for analysis. Such robots will evaluate the focus, stage, publications of a specific founder, match with the right partner or investor, and help find a common relevant background and experience.
  3. Do you remember how public stocks of companies were traded thirty years ago? There were faxes and landlines, people wrote notes or made decisions based on some expert’s belief in economic macro indicators. Now, most retail terminals look like a NASA mission control center, with built-in robots and scrapers and much more. The same path will be trodded by private capital markets. Soon the best deals will be on the radar of trading terminals, and the accounts of companies will be automatically replenished based on the allocations opened by the company, and if one can, he/she will become an investor either through a system of automated robots tuned to a specific type of company, or through distributed investment evergreen funds.
  4. Big platforms, data carriers like LinkedIn, are changing the rules for collecting information. So, for example, if you read their T&C, it becomes immediately clear that you get a ban for automated data collection. Other large aggregators will protect their information even more strongly, because it will become the main source of business insiders.
  5. Predictive models that evaluate company performance, market segment sizes and potential opportunities will also become ubiquitous and will describe the sales volume of both a small company and a corporation so that founders and CEOs can write in their presentations more accurate market numbers and sales potentials for these markets, for example, to determine the most accurate TAM/SAM/SOM and due to this, to better see the startup business itself.
  6. A company's M&A strategies will change completely as end-to-end data will match companies that are best suited in terms of business and size, and cumulative effect when combined, so that they can merge and build a more meaningful business. There will be no need to grow super-fast on your own, it will be possible to find companies that are most suitable for specific tasks, and buy them, thereby closing more and more niches and building potential synergies, which will provide faster returns to investors (exits).
  7. Diversification with automated investment decisions will increase, which will give a new impetus to the development of entrepreneurship, because every company that is able to provide a certain set of potential successful triggers or market signals can receive its share of investments. This will allow even the most inexperienced entrepreneurs to launch their craziest ideas and skillfully manage their sales by seeing the market and potential customers.
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