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1.8 Zettabytes, or to put it another way, 31 billion fully loaded (64gb) iPad’s – an incomprehensible amount of data that represents the estimated size of our digital universe today. To give this a little more perspective, it has been estimated that if we stored all the words ever spoken since the dawn of time, by every human, we’d need 0.0048 of a Zettabyte - just a smidgen of what we’ve already created to date.

You’re probably getting the message. Data is big, abundant and no doubt duplicated numerous times over, in the cloud, on your phone, your laptop and even the thumb drive on your key ring.

So how did we get here? It has not exactly been a steady ascent, more of an explosion on a nuclear scale. In fact, we now create as much data every single day as we have historically, from the beginning of time, up until the end of 2003, what’s more, it is estimated to grow forty-four-fold by the end of the decade – astronomical growth - tantamount only to the industrial revolution which saw production grow by 6,000%, over the more subdued timeframe of 100 years. It is no wonder why we label this phenomenon as the digital revolution.

This rapidly evolving universe requires a significant shift in the way we think as marketers. Not only because we have locked up value within all of that data, but also because we can no longer think about marketing and performance measurement as linear processes – customers now have a plethora of choices, channels and influences, which makes it that much harder for us to truly understand what drives the desired outcomes. No longer can we push consumers through a funnel, we must consider instead, a conversation, within a cloud of events.

In theory, increased data availability should make it easier to measure, interpret and respond to what we do. At the tactical level, this is very true, we can easily answer questions such as, did my search media spend increase site traffic? However, when we begin to think multi-dimensionally (cloud-like), we should consider more complex questions such as:

  • Did our search media spend drive engaged visitors who made social expressions about our brand/product, and how did those expressions go on to influence sales?
  • Which channels drove the social expressions that influenced sales the most?
  • Based on this, how should I adjust my spend mix to impact sales most effectively?

To find these answers, we must first find a way through the data-noise to turn all of that abundant data into action. A sound methodology, is to place an intrinsic value on all our outcomes (there are a number of methods to achieving this), whether this be a site visit, an app download or a tweet - anything that would be considered as a relationship building action or event.

This standardised ‘currency’ helps us interpret performance and becomes a relative point to measure success, facilitating decisions on marketing investment and driving change to our strategies and tactics.

In view of the fact that we can no longer solely rely on linear action, we also need to give way to the fact that not all dots can be connected, and as such, we also need to put some of our faith into inferred correlations, which means making decisions on which levers to pull (representing our marketing investment) using test and learn to find the right formula. In this way, over time, with evolution, more and more dots will be universally connected.

Ultimately, the process of valuing and correlating our drivers and outcomes within a cloud of channels, metrics, events and actions, allows us to continually blend investment to deliver the optimum impact – and if you’re a results driven marketer, this is a fundamental mind-set and practice.

The same school of thought also applies to modern marketing strategies – no longer can we just create linear path communications and campaigns, we instead have to influence and converse, integrated across the numerous touch points which exist in our digital universe, to steer consumers in the direction to find what they are looking for (you!), more on that subject at a later date.

In short, when you put your head in the clouds, you can often achieve clarity.

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Tags: analytics, data, measurement, optimization, performance

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Comment by Theodore Omtzigt on October 27, 2011 at 1:56pm

Love this topic but over the past six months or so I am starting to question the 'deepness' of the solution. Case in point: why is no tablet able to seriously rally consumers away from iPads? All the chatter on all the channels about the pros and cons of these competing tablets does not take away that they are not competitive products. Analyzing this chatter with deep computes on sentiment analysis, or SEO, or A/B testing, or marketing mix optimization won't add one dollar to the coffers of the competing tablets.

All you need to do is go to your local Staples or Best Buy and hold any of these tablets up against an iPad and you quickly realize that the look and feel of these products is not sufficient to entice an early adopter market. Deep analytics on the content of the different marketing channels will not be able to overcome these fundamental shortcomings of the product.

To me, this all confirms that new product development is a team sport where all the divisions in the organization need to work together. Isolated deep analytics in the marketing channel will not overcome the backlash of a bad product.

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