Data Analytics – It Will Change Your Approach to Raising Capital

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More than thirty years ago, a mathematician named James Simons founded a hedge fund that employed statistical models to make predictions on financial instruments. Renaissance Technologies proved without a doubt that there is money to be made identifying non-random patterns in large amounts of data.

 

Today, you would be hard pressed to find a financial institution that doesn’t employ teams of “quants” and programmers to isolate trading opportunities.

 

Data

 

Likewise, similar shifts have occurred in most other industries. Take marketing – traditionally, advertisers targeted its prospects using highly generalized data such estimates of demographics based on ZIP codes, magazine subscription information and other factors.

 

Today, location-based marketing pinpoints prospective customers as soon as they enter a buying zone in their store, and provides them with relevant offers delivered at precisely the right time to impact their purchase decision.

 

When you think about it, practically every sub-sector of practically every industry in practically every major country employs tools to process “big data.”

 

For some reason, though, this has not been the case within the Alternative Asset space. So, the obvious question…

 

If marketing firms use information to predict consumer behaviors and hedge fund managers use information to make investment decisions, why don’t the marketers that represent hedge fund managers make better use of information to profile prospective investor interest?

 

What is particularly puzzling is that all of this can be automated. In an industry so heavily focused on ROI, why wouldn’t you do this? Particularly if all of the hard work can be done in the background. Just wind it up and let it go until some prospective investor pokes his head up.

 

This is not “either / or” stuff but rather, “also” stuff. Do what you would normally do to market your fund and then pick-up the phone once a prospect “self-identifies” with interest.

 

It’s pretty straight forward…Investors, just like everyone else, interact with lots of data and information all day every day. “Simple” Google analytics allows you to see that someone hit your website. Slightly more sophisticated software allows you to identify their IP address and hence, gather even more relevant personal information.

 

This enables you to see not only who interacts with say, an email but specifically how they interact. You can know where on your website they spend their time and how long they are there – you can even see what site they are coming from to know if they are comparing managers or just doing background on your fund specifically. If you use video, you can identify who watches, what parts they watch, how much they watch and when they watch. You can actually watch them watch.

 

All the while allowing technology to register every click.

 

By capturing this click activity, you can begin to glean behaviors. And of course, what do data scientists in every other subsector do when they realize that behaviors exist in piles of information? They look for patterns.

 

Over time, these patterns start to become predictive.

 

However…

There is a massive difference in identifying patterns of stock price tick data versus the click data pulled from a hedge fund’s website or email activity. Particularly if you are attempting to discern any real meaning.

 

The good news: achieving statistical significance doesn’t require collecting thousands of data points. But what it does require is a reason for people to interact with you digitally. Simple stuff like putting a LinkedIn button on your bio page or a “read more…” extension on a news article, writing thought leadership pieces or curating other interesting articles that reflect your philosophy all provide easy ways to start.

 

But you do have to start.

 

To be clear, none of these processes are designed to replace a conversation or anything you do day-to-day (yet). They are merely designed to aid in directing you to the highest probability conversations.

 

And when it comes to measuring ROI, isn’t that really what you want?

 

By JD David

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