Marketing, as we have repeatedly emphasized on our blog, begins with a fundamental exercise to identify a high-value pain or need that you have the potential to address, and then building the right product to meet that need.
It is by necessity a process of dialogue with that target audience to determine what features, functionalities and price points will make your solution a must have.
So I read with great interest a recent article in the Globe and Mail titled Why your DNA is a gold mine for marketers.
“There’s little doubt that human genomes could be a marketer’s dream,” wrote journalist Carolyn Abraham. “A six-billion-unit code brimming with nothing but personal data, pointing out people at risk of obesity, or cancers and high cholesterol, or even those with dead-straight hair, making the carriers of these gene variants prime targets to receive tailored ads for, say, discount gym memberships, weight-loss programs, antioxidants, cholesterol-lowering drugs or even home perms.”
Recommended for YouWebcast: Your Viral Voice: How to Create Conversations that Convert to Sales
Carolyn’s article when on to focus on the various ethical and privacy issues raised by the mere thought of such a thing coming to pass. However, my first thought was if this kind of data mining might not in fact be counterproductive for a brand that puts it to use.
Granted, there are obvious differences between the kind of consumer products-oriented marketing that Carolyn references, and the largely B2B technology-focused marketing that is our stock and trade at Francis Moran and Associates. But I contend that there is still a common denominator in that truly effective marketing does not rely on quantitative data to the exclusion of the qualitative.
This entire argument is a fresh spin on the old nature vs. nurture debate – are our behaviours, preferences and predispositions shaped more by our genes or by the sum of our experiences?
The short answer: it’s half of one and three-quarters of the other. What our genes say we need is quantitative. What our personal tastes, shaped by experience, say we want is qualitative. Both data sets must be integrated for an effective marketing effort.
Take for example a demographic identified as having straight hair. Does this automatically mean these people are interested in products for adding body and curl? What about their interests in colouring products? At best, the DNA profile narrows down a target demographic to engage with via a telephone survey, a focus group or a social media channel.
I would also expect that profiling individuals predisposed for certain health issues could backfire to the public embarrassment of the brand in question. Regardless of how it is presented, the underlying message would be, “You’re fat, or you’re going to be fat, so you’d better get to that gym now.”
Some people may react poorly to that.
Carolyn’s article reminded me of an OCRI Zone5ive event from 2009 that is still as relevant today as it was then.
Speakers Mike McGuire, principal and creative director of Wingspan Design, and Dennis Van Staalduinen, founder of Brandvelope Consulting, talked about how we tend to buy on emotion, regardless of how we may attempt to rationalize the utter logic and objectivity of our purchasing decisions. How we perceive a brand, rather than how we judge the features and benefits of a particular product, often decides our willingness to put cash on the counter. There is often a disconnect between what we want and what we need. Further to this, we seldom like being told what we need.
So can our interest in a certain product or service be predicted solely by looking at our genetic profile? Not likely.
Effective marketing does not rely on predicting what people need, but on asking people what they want. Researching DNA is a form of personal data-mining that could become another useful tool in the marketer’s tool box, but data mining of any kind will never be a substitute for just talking to your audience. The danger here, in the ongoing push to commoditize and automate aspects of the marketing role, is that practitioners come to spend too much time looking at data and forget there are actual people behind the numbers.
Image: University of North Texas