The question of “art vs. science” in advertising has finally largely been agreed on, with smart marketers leveraging both to execute great campaigns. But figuring out how to
harmonize “gut instinct” and “data,” subjective experience and empirical evidence, remains a nagging problem for marketers and agencies.
For one thing,
there’s no clear formula for marrying instinct and research points. But there is a framework for how to think about it when it comes to the general process of planning media spending and budget
allocation.
On a basic level, data is intelligence. The greater insights one has, the stronger and more secure one’s gut-level decision-making is. That holds true whether
someone is “awash in data,” as many in marketing note these days, or if the consumer data appears relatively thin. Either way, marketers and agencies need to begin with a data-driven
approach that is designed to help determine and inform the precise target audience.
What The Gut Doesn't Know
For example, a marketer could rely on her gut
telling her the target audience is women aged 18 to 24 who live in urban areas. While that certainly is a clear target, leading with what experience suggests (but not what the data tells you) can
cause one to overlook how the audience segment has evolved. Perhaps it’s become more fragmented. Or maybe the audience has grown to include additional profiles. There’s no way the gut can
know these things -- not without the data.
The data can uncover niche markets and other details about the audience that past experience alone would never consider. It helps you find
more consumers who are like your ideal target, and reach them with the right message at the right time, across channels and devices.
Marketers used to develop audience
personas based primarily on gut instinct with minimal use of data. Now, we help create that audience segment with sophisticated algorithms and tens of thousands of data points. So the balance between
the interaction of instinct and data has necessarily shifted. To be clear, both remain important to the conception, planning and execution of a campaign. On a fundamental level, the way we approach
the development of a targeting plan involves significant refining of that algorithmic result coupled with marketing expertise and a strong sense of brand history.
A great
example of data “correcting” the gut involves a financial services firm recruiting new staff. The marketer assumed the best audience for this program would be recent college graduates.
After all, the job market was particularly depressed and people starting their careers would seem to be the most receptive. An audience was manually constructed created on our software platform based
on a profile definition that combined age, gender and life-stage information.
But the campaign didn’t reach its goals. We ran a look-alike model on the converters -- using
data rather than gut -- and created an audience that resembled who was converting.
One of the eureka moments in the look-alike modeling was when we identified the 55-and-older age
group as targets. This audience had produced greater conversions because it included many who had incurred losses in their savings or retirement accounts during the recession, and needed to find a new
career to make ends meet. The financial services advertiser used this data and overlaid their knowledge on top of the science. We worked with the agency to generate new creative that spoke to
this audience and the campaign performance quickly exceeded expectations.
The marketer realized that following the data first -- as opposed to going with the gut -- helped them
reach their ideal target audience. As a result, they not only gained new insights, but achieved a better ROI that translated across not just digital channels but traditional ones as well.