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PRESENTER: Human evolution.
All right, get comfortable.
I've noticed JP and Mark are the only ones brave enough to
be in the splash zone.
So that's good to see.
Big data.
I'm sure some of you have seen that term
thrown out quite a bit.
And you're left wondering, probably like me,
how big is big data?
What is big data?
Couple quick stats.
Can everybody hear me OK?
We're good?
OK.
So the reason we have this graphic--
from the beginning of time to 2003 we've created 5 billion
gigabytes of data.
In 2011, that same amount of information was
created every two days.
By 2013, that time will shrink down to 10 minutes.
Another quick stat.
We consume more data on a daily basis than a person
living the 16th century would consume or
receive in their lifetime.
And then final stat.
10% of all photos taken were taken in 2011.
You can think Instagram, you can thank all the different
smart phones that you're using now and taking pictures of me.
So where does big data live right now?
2011.
A Homeland Security agent was gunned down
on a Mexican highway.
The authorities and investigators had an idea of
the Mexican cartel that might have been the
bad guys behind it.
They had interrogation notes, phone calls, wiretaps, emails,
video surveillance.
But they didn't have any way to compile this information.
So they looked to a company, Palantir, a big data company,
that took all this information, compiled it.
We're talking terabytes of information.
And then a week later, a suspect was arrested from that
same Mexican cartel.
So big data has an infinite number of reasons or contexts
and purposes to actually be used.
Mad Men.
I'm sure everyone's familiar with the
program on AMC, I believe.
Golden age of advertising.
Back then, the advertising agencies controlled
everything.
They were in the driver's seat.
They controlled what the messaging was, how to display
it, who to send it to, and what channels to use.
Today that's not as much of the case.
They saw audiences as mere consumers.
The audience today has much more than
just purchasing power.
They're leaving traces of what they want.
They tell the brands exactly how they want to be
communicated to, where they want to be communicated to,
and what channels and at what time.
And all this information is compiling into that big data
for us as marketers.
Gartner puts forth what they call is the hype cycle of
emerging technologies.
And this is what we see here.
This hype cycle is a graph that'll display the common
pattern of any new innovation or new service
that's brought to market.
First you start with the to markets, or concept of it,
followed by a period of enthusiasm, excitement.
I'm ready to go.
Awesome, let's jump on it.
And then there's a little bit of a disillusionment, like, I
don't think this is going to work.
There's no way.
And then it plateaus into realism.
Gartner states that big data is right about to peak.
And they also forecast that big data is going to hit the
plateau of productivity in another two to five years.
So how do we get the game?
Where do we look?
How do we compile this big data for a big end result for
ourselves and our customers and consumers and company?
You're going to see a lot of familiar faces that provide
big data services.
You have your Google, Oracle, Microsoft, Amazon, and a
couple other ones you might not have known about.
So you have Pentaho, Hadoop, and Couldera.
If I butchered their names I'm sorry.
I apologize.
But these fees and pricing models range from yearly fees
to, if you're familiar with cloud services, they're
utility based.
So per query--
I know Google's API for big data is per query, and it's
something crazy like 0.005 times however many terabytes
you want to consume, and so on and so forth.
So as marketers, what do we want to do with this big data?
Well first, the holy grail of customer analytics and the end
result of things.
We know that metrics matter, results matter.
It's not the golden age of advertising anymore where we
could throw a message, craft it, and just look at it, as
beautiful it may be.
So what we have to achieve is that right mix of being able
to find a need, be it predictive, forecasting,
descriptive, diagnostic, and then work backwards and find
out exactly how much it's going to cost for us to
achieve that end result of the direction.
So we could ultimately achieve marketing messages for our
consumers that have the right offer at the right context,
which this is clearly not, at the right time, and then using
the right channel.
So to recap, big data.
It's out there.
It's about to peak in enthusiasm.
We're going to be able to start using it.
There's tools.
There's offerings for it.
It's impacting our life today.
And always want to attach some kind of ROI to it.
Just like everything else, results matter.