Consumer Insights have evolved from an intuitive, gut-based, “trust me” kind of discipline to a data-led, rational and programmatic one. It’s a welcome development, but there’s also a problem … Big Data has been hijacked by incrementality. It’s being used primarily in analyzing what is happening, in order to do “more of this” or “less of that”, but is not helping marketers understand the why: why something works, why it behaves the way it does, & why some brands become superstars while others wither away (click-to-tweet).
In other words, we are stopping short of discovering the causes for causality.
Here are two critical reasons why this story must be told:
1. Marketers are struggling for creative solutions in markets where product parity is the norm and strong brand relationships based on genuine differentiation are difficult to come by.
2. A whole generation of young marketers are coming of age unaware that there are truly profound consumer insights to be obtained from data.
We all know, or at least intuit, that such capabilities exist within the discipline of data analysis. But why aren’t they being used? The answer lies, as in most things, with talent recruitment and management: there exists an unnatural divide between the people wanting to know the “why” and the people actually doing the analysis. For truly breakthrough consumer insights, humanistic, softer talents need to closely interact (or even potentially meld) with data analysis talents to produce truly breakthrough insights and creativity.
So, how do we begin to confront this knowledge gap, this divide between the left and right brains of marketing? How can we nurture a culture of creativity within an increasingly data-driven environment?
Here are three recommendations for helping marketing departments transcend the Incrementality Trap:
1. Lead with Insights
Diving into data without knowing what you are solving for is like proverbially, “boiling the ocean.” We all have experience in dealing with marketing issues and, let’s face it, many of them are pretty much the same. So, rather than wade through reams of data not knowing what you’re looking for, take a little extra time to identify the correct problems (or even the general problem areas) before diving into data. That way you’ll be better equipped to understand the “why” behind the mere correlations/causalities that you end up with otherwise.
2. Roll with it
One of the delights of working with data is that you don’t know what you’ll find. While focusing on validating or qualifying the insights you started off with, keep your eyes open for nuggets of insight (or even major new breakthroughs) that you may find. I have personally had so many occasions when, looking for something in one direction, I have found a truly valuable insight into consumer behaviors or attitudes. These discoveries have opened me up to a whole new way of looking at WHY something is happening.
3. Create a new cadre: Analytical Creatives
The old division between left-brained and right-brained people is so – well, old-fashioned. Hire people who can not just commission and conduct data-based research, but can also weave hard numbers into stories. Foster a culture that insists on a diagnostic approach not just on analytical, sterile reportage.