When context brings sense to the big data mess

By , 13 September 2016 at 17:30
When context brings sense to the big data mess
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When context brings sense to the big data mess

By , 13 September 2016 at 17:30

Building context on data will allow us to make in-the-moment conclusions and patterns that allow us to make real-time decisions and recommendations. And by “us” I really mean the machines we will control.

Big data—which will soon be an understatement—is the amalgamation of information we’re getting from all of our mobile devices, and then adding to that soon the information we’re getting from all those other devices soon from the Internet of Things. Now the debate is if big data is valuable at all. Soon this insurmountable amount of data will become nonsense, unless we add context. Big data will enable machine learning that can in turn enable contextual outreach and context-based marketing.

So what is context? First and foremost it’s the real-time pairing of the when and where you are. Next it’s the patterns of what you are doing and how often you’re doing it. And then it’s taking data from your own devices and recognizing what you like and gaining a sense of your demographic history.

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Then all that info—in a matter of seconds—turns into actionable, personalized context-aware marketing and recommendations.

Scary, right? Well yes, it can be. After all, personal information is, well, personal.

Richard Jarvis, head of threat analytics engineering at BAE security and defence, says measuring the success of leveraging big data monetization hinges on three things:

  1. Trust — when is it OK to share what private data?
  2. Control — what’s being shared on their behalf, with whom and when
  3. And they need to feel that they get that value back — note, not feel like they’re being spammed

“The goal of data monetization should not be money, but customer engagement.” said CTO of VimpelCom telecom Yogesh Malik. And then of course by creating value, you are creating customer loyalty, and it’s much cheaper to keep a customer than to attract a new one.

This is exactly what Ford, the founder of our original “mobile” world, has in mind when it doesn’t just call itself a car company anymore. Ford has officially rebranded itself as both being in the vehicle industry and the mobile one, looking at T-Mobile and Amazon as much competitors as Mercedes. Five years ago it introduced the first connected car and Ford Sync, and then, last year, Ford Smart Mobility. Smart Mobility is their plan to be a leader in connectivity, mobility, autonomous driving, and customer experience, including a fidelity program that offers points to even non-Ford customers, reminding you when you need an oil change or when you have accumulated credit for a free tank of gas. It will offer deals based on partnerships, that trigger based on your location—like instead of your idiot light just beeping reminding you to fill up, it will remind you that you get a free soda if you pull off at this rest stop to fill up.

The next step is to break down silos between networks and app providers to share data in a safe way for mutually gained value between services that are usually competitors.

Of course most companies don’t have data scientists in-house, but the demand will grow for this role. In the meantime, if you want to get use out of big data now, there’s a rush of business software that helps us marketeers do it without having to be from math at all. (Thank goodness!) Even without the element of geography, marketers are looking for ways to use analytics to better understand what you as the customer wants and how to better manage your personalized customer experience.

But we must first focus on what made us want to monetize data in the first place. “The industry was created early on to do nothing about producing data, but to make phone calls,” Rima Qureshi the strategic VP at Ericsson reminds us. “As a telecom industry, we’ve had access to the same data for years but we haven’t accessed it. We are trying to now because we have lost the value of our service.”

It’s up to us to make sure monetizing big data makes sense and we don’t lose the sense of the purpose of our business either.

 

How are you adding contextual value to your business by monetizing big data? Tell us below or tweet to @JKRiggins and @TefDigital!

 

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