Big Data: The Big White Whale for Brands
In retrospect, it is ironic that the Obama campaign named their master database Narwhal, after the fantastical horned whale. In many ways, that is also how brands view the concept of 'big data': fantastical. They see it as a magic formula that everyone keeps telling them is the smart way to run their businesses.
What is Big Data & What Does it Mean for Brands
The Idea: The dream of big data is real. We as companies interact with our customers every day, from social media to the checkout line. And in each interaction we can learn something – what does a customer care about and buy, how and when? Likewise, what does the customer choose NOT to care about?
Particularly with the rise of mobile and electronic commerce, the dream is the ability to talk to customers about exactly what they want at precisely the right time. This could mean showing coupons to those who are price sensitive on products that are bought only sporadically, or saving money by not showing coupons to someone who is not price sensitive. Or it could mean knowing how to differentiate two demographically similar parents between the one who is moved by price and the one who is moved by the new fashion line or the environmentally sustainable materials. This personalization of communications cuts waste and increases marketing ROI. But how close are we?
The Reality: The myth of big data is that we have a data problem. In fact, most companies have a listening problem. People are communicating with us every day, but our internal structures, agencies and technology remain structured by channel. If someone at a store tells us they are buying a product for their new house, would the next communication they receive (an email, direct mail piece or ad) offer suggestions for a new home? Very likely not.
The Problem: The funny thing is that we actually have so much more data than we know what do with. The real limiting factor for brands becomes whether they can create enough content to be relevant to what they know their audience is interested in. No matter how big our teams are, content creation is largely a manual process. And we have data on far more topics and permutations of interests than we will ever be able to cover. Thus, the key is to identify which segments and drivers are really causal factors that will provide the biggest increase in the effectiveness of the communication.
The First Step: The good news, then, is that we need not let the perfect be the enemy of the good. While the goal is a dynamic marketing tool that helps automate segmentation and targeting at the individual level. We can get there. But there is no reason we should not start with our largest and most influential target groups. If we have content that is interesting to even a small subset of our audience, let's at least ensure that they see it. Because there is no such thing as too much content (though we have tried hard to find out), but there is such thing as too boring.
Shameless Promotion: We will be debating this question of what brands can learn from big data, particularly political big data, down at SXSW this weekend. Please come and join Zac Moffat – Romney Digital, Daniel Wagner – Obama Analytics, Tom Serres – Rally, and myself on Sunday afternoon. All questions welcome.