Enhance Your Big Data Marketing Analytics with a Hype-Free Approach

Related Topics: Data & Analytics, Digital Engineering, Digital Strategy

by Damon Samuel – 

When it comes to marketing analytics there are really only 4 things you want to analyze:

  • Who are your customers
  • What they want and do
  • The effectiveness of your marketing efforts
  • How you can optimize future marketing efforts

For years there have been established methods and data sources to address these points. Recently the promise of Big Data has been to provide a silver bullet to all your informational needs. Last I checked, silver bullets cost more than lead, do all the same things regular bullets do, and there aren’t any werewolves to shoot at.

According to Gartner, there’s a typical hype cycle for technology that’s comprised of these steps:

  • Technology Trigger
  • Peak of Inflated Expectations
  • Trough of Disillusionment
  • Slope of Enlightenment
  • Plateau of productivity

Big Data moved into the “Trough of Disillusionment” in the past couple years as companies began to realize that accepting the various sources of Big Data at face value leads to spurious correlations at best and costly decisions at worst.

So yes, there’s been lots of hype with Big Data. But it’s not all hype.

A New Age of Marketing Analytics

Though the reality hasn’t lived up to the hype, Big Data offers plenty of real-world benefits – benefits that no company can afford to ignore. Big Data can provide a wonderful toolset for enhancing marketing analytics, adding value to traditional methodologies such as digital attribution, marketing mix modeling, A-B testing, surveying, and ROI measurements.

Traditionally, customers have been segmented based on a few key differentiators such as age, gender, ethnicity, and income. All are certainly helpful in devising audience-appropriate marketing methodologies. But Big Data can boost our understanding of our audience in a big way.

Getting to Know You

Even though many sources of Big Data are unstructured, underlying elements of structure still exist, waiting to be teased-out with the proper approach. Let’s consider a classic source of Big Data: Social Media. That source of data provides tremendously valuable insights:

  • Meta data on the posts
  • Tags, hashtags, links
  • The text itself
  • Image recognition
  • Shares, likes, and views

From that data we can glean a far more insightful understanding of our target audience by analyzing the customer’s behavior – the structure that lies hidden in the ‘unstructured’ data.

The many sources of behavioral information that Big Data provides – wearable technology, web streams, social media, geolocation, and more – offers an opportunity to understand our customers based more on their behavior than on their innate characteristics or stated preferences.

Get Away from Guesswork

The enhanced observation of behavior enabled by Big Data also helps with measuring the effects of our marketing efforts. Consider two classic examples: TV audiences and billboard audiences.

Before Big Data, Nielsen extrapolated the viewing behavior of the national TV audience by sampling an extremely small portion of the audience. But now, Big Data enables the collection of actual viewing habits via set top box.

And before Big Data, the effectiveness of outdoor advertising was similarly limited. In the past, we might have had a vague notion that 50,000 cars passed a given billboard on a daily basis, according to DOT. But now, insights sourced from inputs such as geolocation data from cell phones can tell us how many viewed the billboard, who viewed the billboard, and even when they viewed the billboard.

(The impact of this segment of Big Data is such that the Traffic Audit Bureau (TAB) recently announced a name change to Geopath, as a more accurate reflection of the impact of Big Data analytics upon that market.)

Get ‘Big’ Or Get Left Behind

Though it arrived to the accompaniment of trumpeting fanfares of over-hyped expectations, the age of Big Data is here. It’s here to stay.

And the ‘Big’ is only going to get bigger as technological advances continue to create more streams of data – even the dust floating in the air may soon be contributing to your incoming data stream.

The key to realizing the true potential of Big Data lies in handling the data properly – applying structure, coding, categorizing, quantifying, transforming, and aggregating the data into a form that your traditional methodologies can accept.

No, Big Data does not offer a cure-all panacea. It is not a silver bullet with which you can slay all marketing problems. It doesn’t permit us to toss away all the old tried and true principles of marketing analytics.

But even so, the true potential of Big Data is really rather staggering. It’s a potential that no company can afford to ignore.


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