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How to be a Data-Driven Investor

How to embrace Data-Driven Investments decisions and say goodbye to guesses and hunches

The tech investing industry is undergoing a massive transformation. Smart private investors, venture capital firms, and leading private equity and hedge funds are beginning to realize that the days of relying on the old ways are over.  

Once upon a time, it was enough to have money and a good reputation you would “spread your net”, people who know people would approach you, and deals would flow your way.

You would sit in your meeting room together with your team, view entrepreneurs’ pitches, and take your time reviewing them.
You make decisions based on “rules of thumb”, also known as heuristics: take shortcuts to make decisions based on past experience instead of with data, analytics, or math.
But in today’s hyper-competitive environment, that’s getting more and more difficult.

 

Many of the great deals don’t even show up on your radar. Meanwhile, your team is busy going through cold emails filled with enthusiastic entrepreneurs claiming to have the next billion-dollar idea.
Suddenly, almost everyone invests in tech deals, and that means big-name serial entrepreneurs don’t come to you for money – they are flooded with it.  

Where can you gain a competitive advantage that will separate you from the crowd?  What do you need to do?

You already know the answer: become data-driven.

Technology and data are transforming the way we make investment decisions. The Data-Driven Investor capitalizes on the power of data to pre-filter investment opportunities with superior potential.
Making money is no longer viewed simply as the result of the insightful decision making of geniuses and wizards. Rather, creating returns from tech exits are seen to follow from rigorous research and the use of advanced tools. Investing is becoming increasingly evidence-based. That has important implications for anyone in investing.


While some people feel that investment is more of an art than a science, innovative investors understand that technology is here to help them, rather than replace them. Just as MRIs, CT technology, and various medical diagnostic tools make doctors better, investment algorithms should save investors precious time scanning and pre-filtering opportunities. They could also provide an easy way to check whether those ventures that you’ve already invested in are on track or not.

 

It is quite evident, at least to most of us, that the winners in 10 years will be data-driven investors who incorporate their experience and intuition with hard data and qualitative research to develop a superior approach to decision making.

When examining the alternative approaches in the market, one can see that a data-driven approach in private equity is very private.
Many leading venture capital firms have their own data analytics tool, but very few, if any, are inclined to share it.  

Correlation Ventures, Google Ventures, Kleiner Perkins, Deep Knowledge, Ironstone, E.Ventures, Right-Side Capital, Follow[the]Seed, Signalfire, Ulu Ventures, Y Combinators, WR Hambrecht+Co, and Venture Science are among the venture investing firms that are using algorithms and / or data science as part of their decision making.

Obviously, taking the approach of developing an algorithm or a data science department in-house could be quite a risky endeavour. For most professional investment firms, it would actually make more sense to partner with a firm that is already doing it.  

While a minority of these firms will be open to discuss co-investments, most of them typically will not share their methodologies or even consider allowing other firms to use their tools for better investment decisions.
Actually, one of them would be willing to share its algorithm as a service.

Follow[the]Seed, a venture capital firm active in Silicon Valley, Tel Aviv, Sydney, and Beijing, is (at least for the time being) allowing professional investors to use its algorithm to scan investments.

The algorithm, aptly named RavingFans®, is designed to detect products and services that have managed to create a strong emotional connection with their customers. It processes usage data in the product/service, looking for patterns of irrational behaviour—obsessive, compulsive, and addictive behaviour—by a critical mass of users.

It is focused on habitual products and services that we use often, typically on a daily or weekly basis (games, music, social media, eCommerce, food delivery, content, etc.), rather than things we buy or use only once every several months or years (travel, gadgets, etc.)

Virtually all investment firms developing algorithms have a very finite, competitive view of the investment space, and this is why they are not willing to share their algorithms and know-how.
The Raving Fans® open approach is that one can generate much more value by sharing, rather than limiting access to, its platform. Raving Fans believe that there’s a huge attainable market of many funds and professional investors who are interested in deploying such an analytical framework but cannot afford to develop it on their own, and even when they do have the capital, they don’t have the skills and competencies to do so (or the legal authorization to do so, for that matter).

Allowing cooperation and co-investment will open a world of opportunities and allow for a win-win solution.

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