We already know that the roles of the CMO and the CIO are evolving. We also know that the use of content and data to enhance consumer experiences is one of the primary drivers of this evolution. Big Data just might be the big idea that hastens the alignment of this purpose; but just like content, it won’t deliver it on its own. Advancing our success with data-driven content creation will only come with the evolution of a new role in the organization — something I’m calling the “Manager of Meaning.”
Big data is a big box of nonsense
There’s no doubt Big Data is this year’s “Gangnam Style” of business — it’s the tune that all the “kids” are dancing to. Of course, the practice itself isn’t new. From the tabulating machines of the early 1900s to the keypunch department of a 1940s business organizations have been using methods to elicit value from large data sets for far longer than computers have been around. Even the term “big data” isn’t new — according to some sources, it goes back some 20 years, to when John Mashey, Chief Scientist at Silicon Graphics, used it in a (still surprisingly relevant) presentation called “Big Data and the Next Wave of Infrastress.”
What is new is that the quantity of content being created, the capabilities of technology, and the rate of change in business have all increased exponentially. As Gordon Evans, Vice President of Product Marketing at Salesforce.com, said when we spoke with him for this article, “The opportunity for marketers is we can now listen for any kind of topic or subject, across any social network. Marketers can analyze that and use it to deliver better engagement. The key is in how you actually do that analysis. How do you make the data small again?”
In a recent study, the CMO Council found that two-thirds of both marketers and IT executives now feel Big Data can surface customer-centric business opportunities. But, simultaneously, half of both groups believe that functional silos still prevent the accumulation of data, and therefore hinder any kind of customer-centric strategy.
At the Content Marketing Institute, we’ve certainly observed this happening at large enterprises. Basically, marketers are reading the scads of articles and research reports about how Big Data might be the best thing since sliced bread; yet, they still have no idea how to “bake” it.
Are marketers hard-wired to get it wrong?
In 2008, science historian Michael Shermer coined the word “patternicity.” In his book, The Believing Brain, he defines the term as, “the tendency to find meaningful patterns in both meaningful and meaningless noise.” He went on to say that humans have the tendency to “infuse these patterns with meaning, intention, and agency,” calling this phenomenon, “agenticity.”
So, as humans, we’re wired to make two types of errors that have relevance here:
- Type-1 errors, where we see the false positive — a pattern that doesn’t really exist.
- Type-2 errors, where we see the false negative — we fail to see the real pattern that exists.
Today’s marketers are particularly prone to making Type-1 errors. Because so many marketers use analytics to serve as a “proof of life” in support of the particular strategy they’ve put forward, their measurement methodologies have become predicated on making sure they capture anything that looks like success.
In other words, a data-driven marketing mindset has pushed many marketers into scrambling to find patterns of success that may or may not be there. We see increased time-on-site and call it engagement — without considering that it may actually be due to frustration because users can’t find what they’re looking for. We see “likes” as an indicator of success on Facebook, disregarding that people actually have to “like” your page before they can comment on how much they hate you. This tunnel vision has marketers focused on using data solely to optimize transactions instead of viewing it as insight on how to deepen engagement — as evidenced by a recent IBM study, “From Stretched to Strengthened,” which found most CMOs use data in hand to optimize transactions and not to deepen the relationship with consumers.
Gordon Evans from Salesforce.com further framed this disconnect by saying, “There’s this whole notion of being able to identify and convert people in a different kind of funnel — where you take them from strangers to friends to fans to advocates. That’s all done through engagement-focused experiences.”
Put simply, marketers have got to start looking for meaning, using content and data to deepen the relationship with consumers, rather than always focusing on more transactions.
Marriage of the rational and the emotional
Wilson Raj, the Global Customer Intelligence Director at SAS, frames the issue quite elegantly, by explaining, “The data, while powerful, is only half the story. The other half is an understanding of the emotive needs of our customer. What are their aspirations, fears, dreams, desires, etc.?”
So how do we start to balance both of those things and extract value in our content creation efforts? Wilson advises, “CMOs must ask, ‘Do I have the data?’ If the answer is ‘yes, but I can’t get at it,” [they] don’t have a Big Data problem, [they] have an analytics problem. But if the answer is ‘no,’ then the CMO must start to examine where they can get it, and add in the missing linkages.”
And this is important for us as marketers, because in order to properly ask, “Do I have the data?” we must first answer this question: “What small data is needed?”
Learning to ask better questions
Marketers must understand the data we have should always be embedded as part of a context. Our data has inherent biases precisely because it is our data.
For Big Data to have any value beyond the information we already have, we will need to move beyond using analytics as a method to prove success or ROI, and instead use data and measurement as a method to improve the continuing process by which we derive more meaningful insight and develop deeper relationships with customers. Yeah, we marketers have been talking about this for years — but this time we really need to do it.
We will need to add new roles to our teams (ones that, I would argue, don’t exist yet) so that we are equipped to peel back the layers of Big Data and make it small. These players aren’t necessarily scientists or mathematicians, but they will have the necessary talent and ability to ask advancing questions of our data, our customers, and influencers, and apply the art of listening, conversation, and synthesis to transform facts and results into meaningful insight.
Who are these people?
The above qualities sound a lot like those of journalists, or perhaps talented researchers? Or maybe our data scientists must add new skills? Perhaps this may even be the future role of the influence marketer. Quite candidly, the road has yet to be paved.
What I do know is that if Big Data is to mean anything more to content marketers and creators than just a big box of nonsense and distraction, the “Manager of Meaning” role must come to pass.
Cover image via Bigstock