Do You Speak Big Data?

If you’re reading Razorfish 5 (or R5 as the cool kids call it), then you likely walk the technology walk and talk the technology talk. You’re also probably no stranger to the current buzz around Big Data — it’s everywhere. But to help the tech-lingo flow, here’s a quick Big Data primer to keep you in-the-know. P.S. If you really want to impress your techie friends, there’s a lot more detail in last year’s R5.

What is Big Data?

When you search for information these days, Wikipedia is the standard go-to; however, when it comes to “tech-know,” O’Reilly is the source. The media company defines the origins of Big Data as follows: “Big Data is when the size of the data itself becomes part of the problem. At some point, traditional techniques for working with data run out of steam.” [ Read article ]

So if the growing size of data creates the problem, Big Data is the term coined for the techniques used to manage these vast amounts of data — transforming data into actionable insights that give business leaders the ammunition they need to make smarter decisions. But where does all this data come from?

Big Data origins

There is no single source to the petabytes of data that are now accessible to us — data comes from just about everywhere. (Everywhere = big, thus, Big Data.) Anytime a customer interacts with a business or service and a piece of information is captured in a data store, that data element can be used to better understand a customer. This is both exciting and daunting.

So Big Data is comprised of data touch points: CRM, ERPs, customer databases, the Internet, digital behavioral data, consumer-generated content, transactional data, and service center records, to name a few.

Who is thinking about Big Data?

From the headlines, it seems like everyone is playing the Big Data game — but we think there are two key types of problem solvers out there:

  1. Faster data processing heroes. Consider Google, Yahoo! and Amazon. These players break down the walls of traditional silo server-based computing and embolden data integration through distributed storage systems. This means businesses, or even the guy next door, have the ability to quickly and cheaply process heavy amounts of data. If you’re a data geek, here’s the geek-out history:
  2. Big Data meaning makers. So you can process the data, but then what? Enter the role of the data scientist. This is not your average data analyst, simply aggregating and reporting on what data is telling us. As O’Reilly points out, data scientists are really in the business of creating data products. They are the wizards who can analyze data, build reusable, predictive learning algorithms on top of the mountains of data and, most importantly, explain the “so what” of it all — how your business takes action. You will hear this term a lot in the next five years. Why? Because there will be 1.5 million new roles for these folks. [ Read article ]

What are companies doing with Big Data?

In short, companies use Big Data to become better businesses for consumers — to help their customers engage with them more efficiently, deeply and meaningfully — and of course, to encourage more spending and brand loyalty. Companies want to be more responsive to consumer needs, so they’re gathering all the information customers provide, codifying complex algorithms quicker than ever, and churning out robust analyses that allow them to speak more directly to those consumers. They create “learning” algorithms that continue to compile and crunch new data, providing new opportunities for businesses to move from the traditional MBA 101 version of segmentation to personalized, micro-segments with an almost infinite number of ways to customize experiences. (Think: personalization and 1:1 relationship marketing.)

Who is innovating in Big Data?

The whole field is a pool of innovation, and data scientists are already doing cutting edge work. You probably aren’t surprised to learn that Google is taking Big Data analysis into the cloud. Google’s App Engine platform provides an on-demand prediction API that takes a data set, learns from what you teach it, and then makes it available for you to use in real time.

How does this play with R5 and the idea of technology?

Technology is the enabler of Big Data — it collects factoids, gives data scientists the tools they need to add context, and allows smart businesses to fuel customer experiences with this dynamic insight. In order to translate all this information for targeting, many organizations are pursuing Big Data strategies — enabling high velocity learning and sophisticated interactions across human and digital touch points, using technology such as:

  • HTML5, JavaScript and CSS, which have enabled a responsive design capability. That means a smart, customer-centered design can be created and optimized across any device in a consistent way.
  • Customer optimization tools like Adobe Test&Target, which can be used to determine what kind of content produces the most benefit for target groups of customers.
  • Big Data unification like Elastic MapReduce, which allows organizations to aggregate all of their multi-channel touch point data about their customers quicker than ever before for their new segmentation models.

I’m hungry for more Big Data info — where should I go?

  • Razorfish Global CTO, Ray Velez, and Consumer Insights VP, Mark Taylor, in a conversation on customer analytics using Amazon Elastic Compute Cloud (EC2). Read interview ]
  • Amazon’s case study on how Razorfish uses Amazon Web Services (AWS) to give data more meaning. Read case study ]
  • Vivaki’s CTO, Pradeep Ananthapadmanabhan, talks about marketing in the age of Big Data. Watch video ]
  • For more information than you know what to do with, check out the GigaOM Structure: Data conference from 2011. View library ]

So what?

In five years we won’t be talking about Big Data being the future — Big Data will be the way that companies do business. So if you’re ready to get going, a good place to begin is to start thinking about what you’re currently doing to capitalize on the data you’ve already got.

Written By

Cory Cruser Director, Consumer Insights Twitter

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