Big Data Analytics: What will you do next?

Written by Sherri Hammons

Big Data Analytics is all the Buzz.  Google it and get over 43 million hits.   New companies are cropping up to deal with the vast volume of data being created online.  Annual spend is trending toward billions of dollars.  Clearly big business.  But what is it?  Really?  At the end of the day, it’s about what can be learned from the mass amounts of data everyone is collecting.  And for most businesses, it’s specifically what they can learn about you.

I grew up on Big Data back when it was called data.  I joined Abacus Direct in 1996 as a software engineer in 1996.  It was the largest cooperative database in the country and is now a part of Epsilon.  They did data and lots of it.  Catalogers and retailers sent them your purchases (you paid $50 for a black jacket in October) and Abacus added that information to your household.  They compiled hundreds of purchases onto your household from all kinds of places.  Then, they tried to figure out what you were about to do.

Were you currently buying anything?  If so, from where?  How often did you buy things?  Did you only buy during holidays?  Or year round?  The questions were endless and your mailbox was stuffed full of catalogs and retail offers from companies with finger’s crossed you might purchase something.  All told, for every 1,000 catalogs mailed, only about 20 people purchased anything.

That was data.  Now let’s talk Big Data.

Facebook has trillions of pieces of information.  So does Google (maybe even quadrillions or quintillions).  And Twitter.  Amazon, anyone?  In the past few years, businesses have added mountains and mountains of data about you, about your friends, about your company, about the world.  Businesses are gathering information on what you searched for, what you purchased for yourself, what you purchased as a gift, where you are in the world and where you’ve been, who you are trying to find in a restaurant, what you had for lunch.   Businesses are tracking how you are driving, your blood pressure and how many calories you ate.

Scary?  Yes.  Predictive?  Depends.

Facebook is struggling to monetize their buckets of data.  Why?  Because that data in isolation may not matter.  In order to sell it, they need to prove it is worth something.  It may be interesting to your family that you just posted pictures from your vacation, but probably not that interesting to a business trying to sell you cookware.  And just because you searched for a Maserati doesn’t mean you can afford it.  Or even that you want to buy it.  It may mean you heard about the newest one at happy hour and decided to look it up when you got home.  And even if you’ve purchased expensive cookware in the past doesn’t mean you plan to continue the trend.  You might have just started saving for your new baby and cookware isn’t that important anymore.

What’s missing from all this mass of data is your intent.  And intent is not easily predicted, especially when data is silo’ed in many different companies.  Google knows you have recently been searching for colleges in the Southwest.  Facebook knows you are 45 and have a child graduating from high school.  Chase knows you recently moved some money out of a CD into a checking account.  Amazon knows you are buying small appliances.  In isolation, not that interesting.  But, what if all this data was shared?  Then there is a high likelihood that pretty accurate predictions could be made about what you intend to do next.

Mental note:  Privacy policies really do matter.

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Sherri Hammons

a mostly well-informed, technically savvy, sometimes extroverted introvert