What’s the difference between Big Data analytics and consumer collaboration? And can these two very disparate approaches to consumer insight and innovation play well together?
Let’s
start with a definition provided by one analytics firm, which describes its software as “a secure and flexible Big Data analytics platform that extracts powerful signals and insights from
massive amounts of data flow, and then streams analytically enriched guidance and recommendations directly to the front lines of business operations.” Now this is a heady claim -- and quite
likely a valid one -- but it’s a description lacking a human pronoun. There are no people in this process.
But in the business world, in the political world -- everywhere that
people like us are engaged in ongoing conversation with consumers -- we’re doing it with the ultimate goal of not just gathering facts, but of moving people, of changing people’s
minds and behaviors. That’s what marketing is.
The huge promise of Big Data also lies in its biggest limitation. In some respects, it is so useful becauseit’s entirely
passive – it doesn’t rely on the self-reporting of flawed, biased and forgetful respondents, but on observable behavior. It doesn’t ask people what they’re going to do; it
measures what they’ve already done. It doesn’t rely on sophisticated statistical analyses because there’s so damn much of it that algorithms and extrapolations aren’t
necessary. In short, Big Data stands a good chance of replacing large-scale survey research in many domains, and we’re actually pretty excited about that.
But while Big Data can tell you
what, it can’t tell you why. While it can tell you what people do within the realm of what’s available and observable, it can’t help you create the future. As David Brooks -- someone
with whom I rarely agree -- observes, “If you are relying just on data, you will
have a tendency to trust preferences and anticipate a continuation of what is happening now.”
Big Data can render traditional quantitative research methods obsolete, but it
simultaneously underscores the need for empathy and insight, for a human voice to make meaning and tell a story that moves the people behind the brands in a way that simple data, however beautifully
visualized, cannot.
The risk that we always run -- even with the best of intentions -- is that when we turn actions and words into data, behind the numbers and visualizations we tend to lose
what’s shifting, what’s subjective and what’s human.
This is not a polemic against Big Data. On the contrary, there’s a very complementary and synergistic
relationship between that methodology and the kind of intentional, interpersonal collaboration many companies are working to foster. After all, data alone doesn’t move people. People move
people.