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“Analyzing Consumer B ehavior ” (Segment 10 of 15) Transcript The world of finance has been changed forever by the data revolution. The effects have sp illed over into everyday life, a nd 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 t o 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 wa nted to find hints of what people might want to buy even before they ’d realize it themselves. He needed to find a collaborator.