Let’s spend a little time on big data, a term that Forte CEO Jeff Thorness sees as one of the more important current trends in payments.

First off, what is it? SAS considers it “a popular term used to describe exponential growth and availability of data, both structured and unstructured.” But I much prefer this definition, from Forbes’ article, where it is described like this:

“Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.”

Good? Good. Nicely put.

Big data isn’t necessarily all “big brother” terrifying, the ever-watchful eye carefully tabulating every single step you take, but it’s also not just another iteration of marketing data businesses have been collecting for decades. Big data is new, and it goes hand in hand with the kind of enormously powerful all-encompassing nature of other trends, like omni-channel. It is spawned from the same train of thought found in the new customer experience, which pushes the importance of an all-inclusive, uninterrupted, seamless narrative. While the customer might be getting a seamless narrative about a business from an omni-channel strategy, a business might get its seamless narrative about its customers from big data.

But where did it start? Well, a new book by Thomas H. Davenport (reviewed by Forbes) called Big Data at Work: Dispelling the Myths, Uncovering the Opportunities points to “online firms” like Google and Facebook, who developed technologies, methods, and tools related to data analysis, but also created a whole new attitude to the idea of mining for data. These powerhouses starting not only collecting big data, but positioning themselves and their products with respect to and based upon their findings. This has radically altered the way businesses think about big data and enabled the creation of many data mining and analysis firms and resources.

Big data can really come from just about anywhere: social media, web behavior analysis, financial records, emails, and point of sale. The Forbes article goes further to define two specific types of big data. According to the source, the information that is “not organized or easily interpreted by traditional databases or data models, and typically, it’s text-heavy” is considered unstructured. This includes social media. The alternative, multi-structured data, is particularly interesting, as it refers to the great variety of data to be collected from any interaction between machines and people. As the omni-channel trend continues to evolve and more methods of tracking information are created, multi-structured data will be able to pull insights from every single channel – in ways we never imagined. And the amount of data we have to analyze is astounding: it’s doubling every two years, according to IDC research from this article in The New York Times.

All of this big data can reveal interesting and helpful trends about customers and their behavior, as well as the efficacy of business products, systems, and programs. But, as Davenport points out, you better figure out what you’re looking for: “Sifting without a purpose can become very expensive and time-consuming. It’s far better to have a hypothesis in mind – particularly before gathering a lot of data, and even before analyzing it.”

So what to do now? Maybe start with something like capturing data from the point of sale. Cloud-based payment terminals that create reports for omni-channel businesses operating are actually holding stores of helpful data: transaction and customer information that is collected at the point of entry (or beyond) can prove highly valuable. Collect this data and find a numbers guru, unless you already are one yourself. Establish a hypothesis, crunch away, and use this data to see trends and make important choices.

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Photo credit: Tinou Bao

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