Venture investors are always looking for new projects. The question is how they find them. They market themselves and wait for a response, or they are the first to contact, searching for candidates by a variety of methods. The use of modern tools for the generation of a pipeline — large and local databases of projects — at first glance, may significantly reduce the time spent on search, but for any investment analyst, working with databases becomes a boring routine that requires significantly more time than he usually has the chance to spend on the generation of pipeline opportunities.
Originally published at https://medium.com by Gleb Davidyuk.
“Where do you look for your deals? — is the question that I am most often asked. The search for an answer does not lose its relevance, no matter how big the market is. Using the example of the world’s largest venture capital market — the United States — it’s clear that the percentage of startups that find their investors hasn’t changed much in the past five years. 1.2 thousand startups out of 600 thousand that appear annually find venture funding. The web has hundreds of publications with tips on finding an investor, finding an investor during a crisis, and presentations describing the search stages and methods. It is noteworthy that it is more difficult to find such instructions for a venture capitalist. Some teach you how to identify signs of a promising project. The main ones are well-known: a strong team that knows what problem it will solve with its product and proof of its market value. You are advised to build good relationships with the founders and work hard on your exit strategy to find them. But before getting to the process of searching and evaluating the prospects of a project, you need to first find out about it.
Two main project search strategies
When fishing, you throw a fishing rod and wait
I see two main avenues of project search for initial selection. They are like hunting and fishing or push and pull in the language of methodologists. When fishing, you throw a fishing rod and wait. In the context of a project search, it means that it is necessary to spread information about your investment strategy as widely as possible among potentially interested parties. After some time, you check the email@example.com mailbox to check for leads. Every day there are 5–7 different applications. I personally constantly receive letters inviting me to invest in one or another company. There are rather simple messages in which the author names himself, the company, the basic financial indicators — and offers to participate in the investment round. It is quite enough for a start. Ten years ago, we used to attend conferences for this purpose. You go to the conference, leave with a couple of dozen business cards, patiently answer everyone, and one word after another, projects, ideas, and contacts are born. Today offline conferences have lost their former popularity. However, there are still events worth going to to tell about yourself and your investment strategy and wait until they approach you. However, frankly speaking, the probability of finding a super interesting deal this way is extremely low. The best deals are already picked up before they ever make it to the conference floor. That is why there is “hunting.”
“Hunters” represent professional value in the investment team of any investment fund
“Hunting” can be conducted in parallel with “fishing,” and it is “hunters” that represent professional value in the investment team of any investment fund. You hunt for the most interesting projects, ideally those that do not need money but rather your human capital. In many ways, this is a very delicate and manual job: keyword queries, viewing corporate websites of relevant investment strategy players, reports, lists of participants in industry events. That is a conscious and thorough search for companies that are interesting from an investment perspective. It is necessary to admit that all methods are time-consuming and effort-consuming. If they can be, best to try and automatize them.
Modern lead generation tools
Today a part of the work on data generation, which an investment analyst can use for the initial selection of projects, is undertaken by large information portals. The most popular ones are Pitchbook, Crunchbase, CB Insights, Mattermark, Dealroom. There also exists local portals — by region as a whole, for example, Europe, or by country, that may be interesting. It makes sense that startups are interested in adding information about themselves to these databases, hoping to be noticed by potential investors. You can afford to set up filters that make it convenient to search for projects, but customizing these filters in the context of an investment strategy is not easy and sometimes impossible. A separate story is a search for projects in a region far from the heart of venture capital activity in the United States. There may be even less information about them in a large database. This significantly complicates the work of a fund’s investment analyst, who has to use local startup databases, which wastes precious time and increases the chances of overlooking a promising opportunity. Local databases do not offer search filters, as a rule, and instead offer to download the entire database. There are no filters, no notifications about new deals or companies, which means that the analyst should not be lazy and enter the database with a certain periodicity, and compare what there was with what it has become. This means that the level of efficiency of such a search falls rapidly.
In the four largest databases — Crunchbase, Pitchbook, Dealrooom, Parsers VC, there are 8.5 million companies and 550 thousand investors. It is impossible to manually sift through large volumes of information at a speed sufficient for a timely generation of the fund’s pipeline. This is a huge amount of work. That’s why we created our own product AIRR Leads, which automates and organizes companies’ primary search, stores everything in one place, and allows us to connect the team to the work process in an efficient way. If you search in databases manually, the results will be different for every analyst because each uses his own personal filter to create a query. When the filter is formalized in accordance with the fund’s investment policy, the initial selection is based on objective criteria. The process is fair at the very start. Automation of search is relevant for “hunters” in any industry. For example, in the mining industry, by connecting software to a database of mines and arranging the requisite filters, you can search for suitable targets by location, the volume of reserves, cost of extraction, or other specified parameters. A similar scheme works with the companies’ databases if the purpose of the search is, for example, the manufacturer of medicines. By setting the required filters automatically, we have learned how to significantly narrow the selection while increasing the search output’s relevance and uniqueness. By robotically generating the process, we have significantly reduced our investment team’s labor costs while improving quality. Time is our main and most precious resource, and in my opinion, it is silly to spend it on reading hundreds or thousands of irrelevant queries.