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How Big Data Changes the Marketing Paradigm

Blogs about Big Data from me and others have usually focused on the benefits, the competitive advantages, and the potential to increase revenue through better understanding of existing customers, and the use of this business intelligence to find new customers.  There have been other blogs that have talked about the software and methodology for implementing the capture and analysis of that data.

But, less talked about have been the changes to the whole marketing paradigm, and the impact on marketing departments that Big Data is bringing about.

Scott Brinker, CEO of “ion interactive”, and a frequent writer on marketing technology, says that to make the best use of Big Data, Marketing needs to do Big Testing.  He says that while marketing has always utilized data, their “management and culture have thrived more generally around gut instincts, creative concepts, and compelling communications”, and it has been more about “big ideas, big thinking and big budgets”.

For marketing to fully realize the benefits of Big data, it needs to change and learn to follow the scientific method of proposing hypotheses, testing those hypotheses, and then checking the results.  The payoff is that doing testing right can gain visibility into smaller circles of customer segments than was previously possible.

Brinker says that, “With the new tools that are emerging, marketers can crunch their petabytes of disparate data, pulled from owned, earned, and paid media, mingled with transaction histories, mixed with profiles from third-party exchanges, and combined with public and industry statistics to divine all kinds of interesting correlations.”

But, he cautions against assuming that correlation means causality.  Rather, these correlations suggest possible relationships that should be the bases of hypotheses.  One cannot assume that any of the correlations can directly influence customer behavior.  For, even though there is now access to far more data than ever before, we will never have all of the data to explain human behavior.  So, this process cannot be completely automated, but will always require a level of experienced judgment to sift through and distill the results.

What we seek are testable customer experiences.  Testing in marketing must now be elevated from a minor scale, small staff,  niche practice, to a major role, “broadly embracing testing and controlled experimentation as the new ‘operating system’ of marketing”.

The answer, says Brinker, is big testing, which means three things:

One is experimenting with big ideas. Learning can be more important than optimization.  For example, you could test what color “Register Now” button customers prefer on a web page.  You don’t learn much that way.  But, instead, what if you tested a completely different value proposition on your landing page (linked to from social media or online advertising)?  Now, you are learning something meaningful about your customers/prospects.

Another big testing element is a bigger testing group.  More people are needed to get “the training, the tools, and — most importantly — the mandate to test new ideas”.  More people are needed to run the controlled experiments that can yield the intelligence.  (As an example, Google runs about 10,000 experiments like this per year.)

The final element is “making a big deal about testing from the top down, fostering a culture of experimentation”.

This is perhaps, the toughest one, because it requires buy-in from the executive level and a commitment to change the culture.  It needs to be accepted that customer testing is a good investment, and an understanding that good experiments may “prove or disprove hypotheses, but that either way, the information has value”.  The testers in marketing need to know that they have the support of their leaders to do things the right way.  And, if they do Big Data can lead to big success.

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