This past week, I tweeted the following: “the data itself isn’t overly interesting. the application of data is what is fascinating.”
This wasn’t the first time I tweeted something along these lines and if you’ve heard me speak publicly (or inside the agency) over the past few years, I’ve probably touched upon the topic, if not spoken all about it.
A few people reached out and asked me to write about where I see this playing out – as to illustrate the point about the application of large data sets to make decisions. I thought I’d use this post to do just that – give 3 sites that you can check out to see what I mean. In no particular order, they are listed below.
Numberfire is a fantasy football GM’s mecca. If you are managing a fantasy team and want to compliment (and/or replace) watching ESPN Fantasy Football Now, reading all the blogs, etc, why not apply large data sets worth of performance data to predict performance of players? If you can aggregate plenty of data sets, normalize them, and run regressions/etc, then you can figure out which players have a higher probability of performing better each week. I used Numberfire last year, which was their first year and they continuously outperformed the ESPN and Yahoo! rankings (7/10 times). What’s nice too is that Nik, the founder, has an eye for design and made his site very usable and IMHO, probably the best site within this space.
I read last week that a site named TRUEcar raised $200MM for vehicle-data related purchases. Anything that has a nine figure capital raise and data related to it immediately got my attention. What TRUEcar does simply is help people decide what to pay for a used or new car, based on historical information. Seems simple, right? Have you ever tried buying a used car and all you had to rely on was the KBB value of the car (kelly blue book)? See the image below, as it illustrates a search I did for the 2011 Range Rover Sport, a car I fancy. Their visualization of large amounts of data is what is extremely important and will help separate them from forthcoming competitors.
I did not realize that Bloomberg launched Bloomberg Sports and it includes a decision making program for fantasy football rosters. Essentially, Bloomberg is leveraging it’s data infrastructure and visualization tools to help make informed decisions of whom to sit/start each week for your fantasy or handicapping needs. This product certainly competes with Numberfire (and vice versa) but it’s not as robust. However, this is a great start for Bloomberg Sports.
PaidContent recently re-posted a vision I had regarding the Bloomberg Terminal for Advertising. This is an area that is ripe and one I’m currently exploring. Would be really interesting to bring advanced visuals and analytics to the world of real time bidding and media trading.
I believe that just having data or access to data will be table stakes in the next few decades. The organizational winners will be ones who can apply the data to whatever they might be working on. These are early days for this now, but I believe this will play out over a long term vision. Data scientists + Data visualizers = data visioneers = people I’d like to meet.