Connect the Dots
Facebook’s master plan isn’t a social destination; it is a connected backbone to everything else we do.
From the first time I saw Facebook’s timeline, I understood where they were going. As the IPO came and went, many investors focused on the number of people using the service, visiting their pages each day, and quibbled over how many more people the social service could/should support. This doesn’t matter.
That isn’t true. Facebook needs members to track, and data to crunch… but showing up to facebook.com doesn’t matter. What matters is understanding how data is connected, and what that means on a larger scale.
Let’s take three fairly normal use cases and start to build some scenarios. I have a Nike+ account, I listen to Spotify, and my friends and I regularly upload pictures to Instagram when we go out. Could any of this be connected? Facebook has the answers.
What if you learned that the days you listened to Kanye West, you happened to run faster?
What if you learned that the nights you went out (pictures uploaded with friends after 10:00 pm) you were less inclined to work out the following day.
What if you learned that the later you stayed up, the later you woke up.
Some of this would be completely obvious to you, and other things might provide insight into your own personal behavior… but things get even more interesting when your individual data gets compared to a billion other people. Using this same scenario, you might be able to deduce the most inspiring song for runners on the planet. Maybe you would discover a new artist based on similar characteristics of people like you around the world… Or maybe Nike would start selling you play lists it knows you will find compelling? Data can be used in many ways.
23andme is an awesome example of learning that can come out of databases. Using a vile of saliva, they will break down your genetic code and give you a new way to look at yourself, how likely you are to get Alzheimer’s, how likely you are to be obese, your eye color, and dozens of other characteristics like oily or chunky ear wax. By comparing their database and surveying members, they are able to make new discoveries… my favorite is the propensity to have smelly urine after eating asparagus. Why does this matter? It probably doesn’t, but comparing databases can lead to important discoveries. The things GE is doing with cancer research, for example, are amazing.
More data, more patterns, more math, more analysis… all happening in real-time.
I’m in the middle of The Signal and The Noise, and so far I think the book can be summarized by one excerpt:
The human brain is quite remarkable; it can store perhaps three terabytes of information. And yet that is only about one one-millionth of the information that IBM says is now produced in the world each day. So we have to be terribly selective about the information we choose to remember.
Think about that for a while. Facebook isn’t building a new search engine to go up against Google, they are building a platform to analyze data patterns from millions of users, to predict human behavior, and ultimately to monetize that.
Right now Facebook is simply feeding the addiction. With apps like Nike+ and Spotify, users forget that they are sharing. As this continues to grow, so does Facebook’s knowledgebase. Several years ago Facebook made news because they could predict when people would break up. This was before timeline, before the like button, and before all of this data was connected. Now it is less about observing patterns, and more about making predictions.
Medicine, the stock market, marketing dollars, traffic, waiting in line, prices will all be analyzed, compared, and predicted. With universal access to most information, the person who can decode it all will rise to the top.
Today wasn’t about Facebook search, it was about connecting the dots.
