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 harmonise “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 does not 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 has become more fragmented. Or maybe the audience has grown to include additional profiles. There is 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.
Correcting the gut
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 did not 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 modelling 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 realised 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 return on investment that translated across not just digital channels but traditional ones as well.