VIII Consumer Behavior Case Study

“Analyzing Consumer Behavior” (Segment 10 of 15) Transcript

The world of finance has been changed forever by the data revolution. The effects have spilled

over into everyday life, and the data revolution is set to become even more personal. The fastest

growing data set of all is the one being created by you. Every time we call, text, search, travel,

buy, we add to the data mountain. All told, it’s growing by two and a half billion gigabytes every

day. All that data is valuable. And it’s brought out the data hunters, like Mike Baker.

The volume of it, the dynamic nature of the data, is changing how we live our lives. And, if you

collect this information over millions of people, you can start to guess what they may be

interested in next.

He saw an opportunity to bring the data revolution to the world of advertising. Instead of relying

on customers seeing a billboard, it was now possible to beam the adverts directly to them. We

started to look and think about all of the data. If we collected enough about past behavior, could

it be predictive in a way that would be useful for a business in terms of trying to connect to

people.

Mike wanted to mine this data to predict what people might want to buy. His first hurdle was

how to search through the vast amount of data we produce every day to find the tiny signals of

our consumer interest.

I quickly realized that a big part of the problem was actually the math. It was clear there were no

systems, not even really mathematical constructs, where you could capture the information,

make sense of it, and then turn around and create actions across hundreds of millions of people

simultaneously.

[PHONE DIALING]

As if capturing the vast data set created by mobile computing wasn’t challenge enough, Mike

also wanted to mine it virtually instantaneously. He wanted to find hints of what people might

want to buy even before they’d realize it themselves. He needed to find a collaborator.