The consumer of today is bombarded with information, the demands on their time and attention is only increasing – "buy this!" "read
that!". Think instead of what a brand or marketer might have to gain by putting the consumer first. Connect each consumer with the most meaningful and relevant piece of content and they in turn will have a higher regard for your brand. Think of it as a value exchange, by honoring your consumer's engagement level and speaking to their interests they are receptive to your communications and will have a more positive association with your brand. Provide consistent value and you build brand loyalty.
Only recently have marketers made the move to "personalization" by using Big Data sets to inform their decisions. Yet, a consumer's engagement level could change in an instant and if you are working off of exported and old data, how would you notice? How can your brand remain relevant with multiple variables in flux?


A few weeks ago a shift began in the conversations around Big Data – reporters, companies, and contributors started characterizing that "unwieldy mass" as having the potential to be not only viewed, but also actually leveraged in real time as Smart Data. It seems like a natural progression, the process to put big data sets in action to deliver relevant results that improve a user experience – perhaps it is online or a user's
interaction with a product – a smarter browsing experience or smarter home library that knows your preferences. Over the last year we have seen Smart Data transform from what most
considered a pipe dream into real, actionable intelligence that allows companies to better understand, predict and engage with their
individual customers.


It is rare to come upon a company that is not
struggling with masses of data from every department's internal and external channels and attempting to, essentially, turn that information into revenue. As John de Goes pointed out in his contributed post at VentureBeat, Smart Data is emerging as companies, "look to monetize their vast troves of machine-captured data," In my view, the smarter the data, more effectively it can better an end-user experience. And, if you focus on delighting the customer and providing them value, the greater the monetization that
can occur. This is what companies should be focusing on, the overall customer lifetime value. With a clear understanding of a user's interests and engagement level, brands can
provide their customers with relevant experiences and communications at every touch point; this is how companies will retain a user
and create brand loyalty and the way to do that is through Smart Data.


De Goes also made the argument that Smart
Data is essentially a niche or carve out within Big Data that is accompanied by Data
Science, Predictive Analytics and NewSQL. I see Big Data as a predecessor to Smart Data especially as it solidifies its position
as the foundation upon which all of those other
pieces play a role. The best data scientist will
provide better analysis and recommendations if the data they are working off of is Smart.


It is worth noting the other opinions that are cropping up online when talking about the Big Data evolution as they are interestingly
divided. One camp feels strongly that the automation of data processing and decision-making is getting more sophisticated, nuanced and beneficial for businesses. The other feels that even the biggest of Big Data cannot
paint a truly complete picture and alternately can be manipulated to only paint the picture your bosses want to see. Joe McKendrick at ZDNet has outlined the debate well, and proves
that this conversation is just beginning. The great part of being in this initial Smart Data dialogue is that we can see how various industries can benefit from the application of
relevant data - possibly before they can even see it. For many eCommerce brands and publishers I see everyday how personalization is transformative to their bottom lines and how the knowledge gained from Smart Data can build long term, meaningful customer relationships.


Data is not going anywhere – the feeds and streams that our minds cannot process alone are only increasing in number. Yet without

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