Big Data in The Age of Consumer Privacy and #Prism


One of the biggest misconceptions surrounding the big boom around big data and its implementation is the idea that in order to be effective, the more data the better. The reality is that generating big data is a game of quality, not quantity.

The Golden Rule of big data has little to do with how big it is—it’s how well we analyze it and what successes we can garner from implementing plans based on that analysis, regardless of how much data we collect—and whether or not where it’s coming from is a legal source consumers have agreed to.

While many will argue that there’s a major difference between structured and unstructured data, what we see is that today it’s a lot easier to understand unstructured data than ever before. Big data gathered from social platforms like Facebook are technically considered unstructured data.

Some big data pundits suggest it cannot be easily understood or analyzed as part of the bigger picture that ties it into structured data: what we get from sales transactions, our overhead and how it’s affects our bottom line, or how much web traffic we had that converted into sales.

But the truth of the matter is that Facebook user data—which includes how many visits, how many likes and comments, how many click-throughs we’re getting to the website associated with Facebook posts, and what our Facebook demographic based on age and gender are, can quite easily be worked into reports that once only included structured big data. What’s more, it’s big data that consumers have agreed to share.

According to the Stanford Law Review, the risk of infringing on people’s privacy to create more reliable big data is no minor issue. The major concerns the Stanford Law Review asks that we consider involve national security, credit risk analysis, and medical research, to name just a few.

The US government and other public and private sector entities use big data that is based on private consumer (or patient) information every time a situation reaches critical mass (consider what the current administration went through after the WikiLeaks scandal or the more recent leak from Edward Snowden that revealed the use of phone records collected by the National Security Administration).

It is when the lid is blown off of these secret surveillance missions that the public becomes concerned, even outraged, and often, rightfully so. Collecting big data when consumers have signed terms and agreements like those on Instagram, LinkedIn, and Facebook allow data mining that is completely legitimate, and consumers (by and large) are aware their information can be shared.

But when we begin to harvest big data regarding patient information and cellphone records, the public backlash is very real, as the information gathered about phone records and patient records isn’t something consumers or patients gave their permission to access by anyone but their cellphone carrier or medical professionals, respectively.

So the big question is, which is more important: collecting big data to serve public and/or private entities, or the right to privacy that consumers have come to rely on? In some instances, this is an easy question to answer, while in other circumstances like national security, the debate is white hot with controversy.

The idea that collecting big data is a matter of “what they don’t know won’t hurt them” has become a void argument—in the Internet age, fraught with hackers with both the best and worst intentions, it’s not a matter of whether or not the public will find out, it’s a matter of when.

Because of these serious challenges in big data collection and analysis, we have to start to make better use of the data we can find in places that don’t neglect the consumer’s right to privacy. Understanding the supposition that more data is better isn’t a true tenet of data collection effectiveness is a great place to start.

Instead, trusting that the big data we are able to legally and effectively collect truly does tell us all we need to know about consumers, patients, and citizens is an important consideration—if we lose the trust of those we serve, they are likely to leave the fold, heading off to other service providers that have reputations for keeping consumer information confidential.

And the best part? Keeping consumer information confidential doesn’t mean it can’t be used internally to make decisions. It can still help shape sales plans, inventory, and much more—as long as it doesn’t throw consumers under the bus.

Article contributed by Nathan Roberson of The Marketing Robot, Follow Nathan and his co-horts on Twitter @robthemarketer or add him to your circles on Google+

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